17. Internationales Stuttgarter Symposium

„Finding the right candidate. The one that fits.“ Human Resource Managers are permanently faced with this problem within the recruiting process. And the recruitment of talents is becoming more and more difficult. Poor candidate selections are expensive and such misapprehensions can put a company into an existentially threatening position. If, however, the right candidate, who is in the right place at the right time, can have a positive and prosperous impact for the hole company.

70 billion euros annual revenue in 2015. 375,000 employees develop the networked world of the future with us. 5 billion euros is Bosch’s annual investment in research and development. 440 subsidiaries and regional companies belong to Bosch in over 60 countries, employing people from 160 nations. 100 work time models allow flexible work hours and make it easier to achieve a work/life balance. 200 million euros is what Bosch invests annually in further training and in the talents of its employees. 3 out of 4 smartphones worldwide are equipped with Bosch sensors.

Since end of the last decade the battery technology has experienced significant improvements. The combination of high power ability and good energy density enables forestry and garden tools at a comparable level to many gasoline power tools.So far, electric tools could not break through for real outdoor applications as the cord limited the maneuverability or heavy and expensive batteries yielded non-attractive products. For example battery chain saws of seasons 2015 and 2016 delivered comparably high power as small gasoline chain saws and exceeded easily about 50 cm²/s cutting performance. However, most applications still target for homeowner use. Now, more and more professional applications come into reach. But compared to gasoline fuels there is still a significant gap in energy density of a factor 50 to 100 to the best Li-Ion battery cells. Therefore, smart technologies for efficient power conversion and energy efficiency are required.

The growing electrification within road traffic increases the demand for energy efficiency, especially for battery electric vehicles. In addition, they face the challenge to be suitable for daily use and to be able to compete although having a smaller vehicle range as combustion vehicles. A reliable prediction, weather you reach your desired destination with the energy available or not, is essential from the driver’s point of view. The basis for an automatic ancillary unit regulation is the exact prediction of the total required energy. In this paper, we present a model that calculates the energy demand of a battery electric vehicle for any route including the energy for propulsion and electric ancillary units. This model is tested on two example scenarios, which show the importance of taking environmental data into account while predicting the energy demand. This work builds the foundation stone for further investigations.

During the project SaxMobility II of the BMVI a Car and More Sharing of e-vehicles on campus with data monitoring was established. This was the basis for analyzing the use of electric vehicles of the project partners in the energy supply sector and in transport companies (43 vehicles of the project partners).The project is based on data monitoring, i.e. data collection and utilization. For this purpose, the booking tool “CaMS” was realized on a web server. In addition, a database for vehicle data loggers, the determination of the minimum data records and the evaluation of the data records on the web server as well as a transfer to IVV (thinkstep) is implemented.The long-term use of CaMS in the university and comprehensive, interesting insights regarding the usage by students / employees is reported. Furthermore, the outcome is an own evaluation tool to reconcile all results.Over all CaMS offers a unique feature.

Rapid development of advanced driver assistance systems tends not only to use full grip potential, provided by pneumatic tire, but also to use a tire as a sensor. First required step on this way is understanding the physical background of tire behavior. This research is an attempt to decompose the handling tire properties into particular physical effects, which determine them. With help of optical measurements there was analyzed carcass deformation behavior. Using in-tire acceleration sensors there was measured the shape of the contact patch in different conditions. These relations were considered in a physical simulation model. The result is enhanced understanding of the most important physical processes and effects of a rolling tire and their influence on its transient handling behavior.

The force transmission characteristics of high volume agricultural tyres have been extensively investigated at the University of Hohenheim during the last decades. One result of this research is the ongoing development of a physically based tyre model for agricultural tyres. In contrast to commercially available tyre models, the Hohenheim Tyre Model was developed with respect to the differing behaviour of agricultural tyres in comparison to automotive tyres. In this paper the structure of this model is summarised and different alternatives for the parameterisation process are presented. The tyre model has been fully validated using single wheel test stands and total vehicle road tests.

The most significant operation limit prohibiting the further reduction of the CO2 emissions of gasoline engines is the occurrence of knock. Thus, being able to predict the incidence of this phenomenon is of vital importance for the working process calculation – a tool widely used in the engine development. Common knock models in the 0D/1D simulation are based on the calculation of a pre-reaction state of the unburnt mixture (also called knock integral), which is a simplified approach for modeling the progress of the chemical reactions in the unburnt zone where knock occurs. Simulations performed at in-cylinder conditions using a detailed chemical reaction mechanism have shown that, at specific boundary conditions, the auto-ignition of the unburnt mixture resulting in knock happens in two stages. It is demonstrated that the knock integral is not capable of representing this behavior of the detailed chemical mechanism, meaning an improved approach for modeling the progress of the chemical reactions is needed for the calculation of the knock boundary. Furthermore, an enhanced approach for modeling the influence of various parameters on the ignition delay times of the mixture is presented. Additionally, thermodynamic investigations demonstrate the interrelation of engine proneness to knock expressed by the position of 50% MFB at the knock boundary and unburnt mass flowing out of the piston top land that is supposed to have an effect on knock.

The cold start and heating phase of passenger car Diesel engines is essential to comply with the actual emission legislation targets. The HC and CO emissions that are produced immediately after a cold start contribute to more than 70 % of the total cycle results. The initially low temperature level of the exhaust gas aftertreatment system components results in a very low conversion efficiency. With a further strengthening of the emission legislation, the first phases of the emission test cycles will become even more important. It is aspired to achieve the required, even fast heat-up of the exhaust aftertreatment without fuel consumption penalties to reduce engine-out emissions efficiently. Application of a variable valve train system (VVT) can be an additional technology to address this challenge. The FVV research project No. 1171 “Potential of Valve Train Variabilities on Gas Exchange of Diesel Engines II” analyzes potential valve train variabilities systematically in terms of pollutants and CO2 emission reduction as well as to support the regeneration and heating behavior by experimental and computational investigations. Within the experimental investigations, an extended engine speed and load range is considered for a cycle relevant engine map. The impact of an exhaust cam phaser in combination with different intake cam lobe profiles is analyzed on a full-size engine by means of an extended DoE campaign. To identify the heating potentials of the VVT system the DoE model prediction results have been transferred to a mean value model and analyzed by cycle simulations. Combing the three different intake cam lobe profiles with an exhaust cam phasing, six promising heating strategies have been initiated.

The development of the upcoming automotive diesel engine generation is predominated by the difficult challenge of reducing emissions while simultaneously improving efficiency. Near the use of alternative bio-fuels, low-temperature premixed combustion processes have been demonstrated to be a feasible solution for this problem. Increasing the mixture homogenization and reducing the combustion temperatures provide decreasing NOx and smoke emissions. However, the large attentions that have been given to this combustion process during the end of the last century have been lowered by drawbacks such as high combustion instability and poor fuel conversion of HCCI combustion (Homogeneous Charge Compression Ignition). Large difficulties have been also encountered in the application of these processes for commercial engine applications. A compromise has been found by providing only a partial homogenization of the fuel mixture by timing the injecting event towards the end of the compression stroke. This solution has shown greater potential for series engine applications, but problems related to the control of the combustion process still remain the major drawback of this technology. This is mainly due to the high system sensitivity to small changes in the charge composition. Moreover the use of this combustion process is limited at low to middle load ranges and a solution for switching to conventional combustion mode must be found. Particularly during transient engine operation, the realization of a torque-neutral switching procedure is a particular difficult task.

Megatrends verändern radikal und erfordern von den Unternehmen ein grundsätzliches Überdenken aller Prozesse im Unternehmen. Erkannte Megatrends bedingen umfassende Wandlungsprozesse, die tiefgreifende Auswirkungen auf die Unternehmen nehmen. Auf der anderen Seite tragen sie dazu bei, dass die involvierten Unternehmen und ganze Branchen sich radikal verändern.Beispiele hierfür wären Uber als „größter Taxibetrieb ohne eigenes Taxi“ oder „Airbnb als größter Hotelbetrieb ohne eigenes Hotel“.Oder es probieren bisherige Hightech-Firmen des IT-Bereiches sich im Automobilbau. Also völlig neue Geschäftsmodelle, die die „bisherige automobile Welt“ ins Wanken bringen können.Deshalb ist es von elementarer Bedeutung für die bisherigen Marktführer die Megatrends zu identifizieren, die mit dem bisherigen angestammten Geschäftsmodell korrelieren. In einem weiteren Schritt sind Abhängigkeiten und Zusammenhänge dieser beeinflussenden Faktoren im Hinblick auf das eigene Geschäftsmodell zu analysieren.Zu beachten ist jedoch, dass sich disruptive Entwicklungen nicht linear fortschreiben lassen: Es sind immer mehrere Zukunftszustände denkbar. Und es muss überlegt werden, welches Geschäftsmodell einem in die Zukunft führt oder wie lässt sich meine unternehmerische Ausgangslage verbessern?

The worldwide car industry is perhaps facing the most exciting time period ever. Driven by new safety and environmental standards and above all supported by a completely new thinking about mobility systems in general the car industries has to and will change in the next 10 to 20 years. Digitalization and interconnectivity together with an electrified drivetrain leads to new product architectures and therefore opens new ways for manufacturing of these products. New approaches for the product, the car, itself but as well as for the manufacturing system are needed. Coming from concepts like the IoT (Internet of things) in the US or the “Industrie 4.0” the car will become a smart, highly integrated digital platform in the overall mobility systems. The car itself will be seamlessly integrated in the mobility ecosystem and will optimize the way of traveling from A to B accordingly. This paper presents a theoretical approach for a “Cyber Physical Car”. The concept is described on a theoretical level. The transition of the, here described as “mechatronic car” to a “cyber physical car” is discussed and examples for needed subcomponents are shown.

For a long time the image of the Diesel engine was seen as a fuel efficient, but noisy and phlegmatic power source for passenger cars. With the introduction of turbo charging this turned around the first time. A second big step was the cultivation of the direct injection combustion technology, as it once again added a significant fuel consumption reduction opportunity compared to the in-direct combustion systems of these days. With the injection of fuel directly into the combustion chamber the control of combustion was shifted away from air motion much more towards the injection itself. As in former times pre- or swirl chamber concepts defined the course of combustion, the shape of the injection rate became the dominant parameter of controlling the combustion process. These new requirements now defined the boundaries for the next generation of injection systems. One of the important steps was the introduction of electronic controlled valves and software functions, which offered the opportunity to meter the fuel more precisely and drove the transformation of mechanical pumps into the first computer controlled devices. Another important topic was the need of higher injection pressure levels to serve the combustion process requirements with less support of swirl or squish. Last but not least the control of combustion required a higher degree of freedom in terms of injection timing and pressure level within the whole engine map of the engine. By stepping into this new exciting world of direct combustion the focus areas of combustion system developers at the OEM differed tremendously. As a result the requirements led Bosch to develop different injection systems serving all the new engine concepts. Therefore the start of passenger car Common Rail fuel injection technology is time wise strongly linked to the development of unit pump systems and different types of distributor pumps with a radial and axial plunger concepts. As this was an open race of technologies at the beginning, it is a must mentioning them as technical competitors of the early times of Common Rail. The content of the presentation will focus on the technical development steps of Common Rail injector, as it was and is today the interface to the combustion and therefore direct link to the engine performance being the subject of biggest changes from a spring controlled nozzle holder to a sophisticated high precision mechatronic component. Nevertheless it has to be underlined, that all components, a Common Rail fuel injection system is containing of, went through significant development steps contributing to the all over improvement of performance during the last 20 years [1].

The Audi 2.5 TDI in the Audi 100 marked the start of development of today’s direct injection diesel engines. The injection system has been and continues to be one of the key technologies for successful further development. The first TDI engines with CP37 and CP44 distributor-type fuel injection pump, for example, had attached pilot injection. 1999 saw the introduction of the first common rail injection system, which provided enough flexibility in terms of timing and number of injections that it was possible to optimise untreated emissions, acoustics and fuel consumption and to use modern exhaust aftertreatment technologies, from DPF to NOC and SCR. The system pressure was increased from a starting point of 1350 bar to 2500 bar for high-performance engines. Today, V TDI engines are used in derivatives from the Audi A4 to the Audi Q7. The Audi Q7 3.0 TDI e-tron quattro in 2015 became the world’s first plug-in hybrid with a six-cylinder diesel and quattro drive with fuel consumption of just 1.7 litres per 100 km or 50 grams of CO2 per kilometre in series production. The Audi SQ7 4.0 TDI quattro with V8 TDI engine delivering 320 kW power and 900 Nm torque followed in 2016. Model highlights include parallel charging, an electrically driven auxiliary compressor, variable valve control, a 2500 bar piezo-injection system and a combined exhaust aftertreatment system with NOC and SCR@DPF. Consistent evolutionary development makes the TDI drive train highly attractive in the future as well thanks to high road performance, range and eco-friendliness.

Modern downsizing engines with turbo charging and gasoline direct injection (DI) show in sum a significant improvement in fuel economy compared to naturally aspirated engines with port fuel injection (PFI). These engines in turn have advantages under certain operation conditions with respect to fuel economy and particulate number (PN) emissions. The combination of port fuel and direct injection (P-DI), gives the chance to utilize the advantages of both systems, and is in use in various current production vehicles.

The legislature is imposing ever stricter limits on emissions for the automotive industry. Added to this are the new test cycles RDE and WLTC, which exert even more pressure to reach the provisions and force the manufacturer to optimize every component on the vehicle. This also includes, in particular, the aerodynamics of the vehicles. If the proportion of aerodynamics in total consumption was already significant in the NEDC, it gained further weight in the new cycles due to the higher average speeds. This leads to the fact that the engineers have to be able to rely on development tools which are of high precision. The wind tunnel has always been the development tool of aerodynamic engineers. Its structure and its effects have already been studied in several studies [1]. However, the studies were often limited given by the measuring technology. For some years now, another tool has been added, the CFD [2, 3]. It allows the user to carry out investigations under the most demanding conditions. Also, the CFD makes it possible to carry out the numerous optimizations that have become necessary in today’s development. In addition, a further possibility of flow testing has recently been added with the PIV measurement technology. In this work, it is now possible to combine the advantages of all these development tools and thus to make detailed comparisons. The aim is to take a closer look at the impact of road simulation in the wind tunnel. For this purpose, the first test is to determine whether the simulation achieves a sufficient accuracy in order to be able to represent the flow phenomena. This includes the pressure profile in the measuring section as a general boundary condition and in the compartment the flow around the wheels. Subsequently, the individual elements of the road simulations will be discussed. In particular, the influence of the gaps on the wheel rotation units are the focus. The preliminary examinations were successfully completed and the interesting phenomena were presented. For this, the pressure profile of the wind tunnel without a vehicle was compared to the measurement. After that the flow topology around the wheels and in the wake of the vehicle was opposed to a PIV measurement. Subsequently, three different road simulations were compared in the wind tunnel using the CFD. Once the road simulation was presented in detail with all gaps and measuring instruments, the 5- band two-dimensional without a column and a single-band system. The comparison showed a great influence on the lower vortex of the wheels and then the inflow of the rear wheels and the wake of the vehicle. In summary, it can be said that with higher resolution of the road simulation the vehicle resistance increases.

Vehicle manufacturers increasingly rely on hybrid power trains, which especially places certain requirements on vehicle transmission. Here, particularly the independence of the internal combustion engine’s transmission of gearbox oil supply is paramount. In order to realize concepts allowing an independent and on demand transmission of oil supply in CVTs, BOSCH originated the AoD project. The idea behind the actuation on demand is to reduce the amount of the CVTs required energy to the minimally necessary energy needed for actuation. Doing so, the focus lies on those operating conditions in which a high surplus of energy occurs. Especially the inherent and diversified requirement area of CVTs poses a particular challenge. In the following, two principles for actuation processes will be shown: the leakage optimized concept with ratio hold function and the accumulator concept.

The request for constantly decreasing noise levels in the interior of modern vehicles leads to highest requirements in terms of their vibroacoustic performance. Here, the analysis of the transfer paths both of structural and airborne noise evoked by the tire/road contact is as significant as the characterization of the sound and vibration emitted by present-day drivelines and all its components. Regarding combustion engines, the application of direct injection systems is state-ofthe- art both in gasoline and diesel engines. Due to very high pressures, modern injection systems guarantee fine hydraulic atomization and better mixture preparation. In turn, these effects lead to benefits both in efficiency and emissions.

The implementation of the Paris Climate Agreement requires a continuous reduction of greenhouse gas emissions (GHG) by de-fossilization of our energy sources. The transport sector has to achieve near-complete independence of fossil fuels by 2050 an even stricter target than considered so far by the International Energy Agency models. In the long term, battery and fuel cell electric vehicles are essential pillars for decarbonizing the transport sector. Continuous improvement of vehicle efficiency and a strong increase of hybridization and electrification will lead to significant reductions in the required energy for the transport sector. Breakthroughs in battery and fuel cell technology and cost as well as the ramp-up of the charging/filling infrastructure are challenging but most likely manageable. Where locally produced regenerative electrical power is available, electrified transport will be the most likely approach. Nevertheless hybrid and plug-in hybrid passenger cars with an internal combustion engine (ICE) still represent a significant share of the vehicle fleet beyond 2040. In addition to continuous improvement of the vehicles and ICE efficiency, increasing use of CO2- neutral fuels are a strategy for GHG reduction. Biofuels and synthetic fuels based on renewable energies (eFuels) are necessary to significantly reduce GHG emissions of passenger cars. Biofuels and synthetic fuels are even mandatory in other transport sectors such as aviation, navigation and heavy duty commercial transport. In addition to technological improvements - introduced via new vehicles – eFuels have a direct and relevant impact on the overall fleet GHG emissions.

Confronted to new social, environmental and economic challenges, the automotive sector is currently facing a major shift of its history. To address them and without hindering the customers’ expectation, the solution are various and multiple. Among them, drivetrain electrification is currently a topic of high interest. The best utilization of the electrical energy is one of the core topics and influences the design of the entire vehicle. In the case of the electric drive system (electric machine and inverter), each sub-parts are concerned down to the resolver. Even small error can induce faulty estimation of the machine parameter which leads to torque and current deviations. These deviations will generate higher losses in the machine and therefore the system performance is reduced. To fulfil the automotive specific target of the resolver as well as the requirements of a sustainable mobility, a consistent knowledge of its principle is required. The focus of this paper is therefore set on the investigation of the angle error and particularly on its influence on the entire electric drive system. The paper presents thus models for the understanding of the resolver challenges before detailing the modelling approach to consider its influence on the entire electric drive system.

An efficient and highly detailed Noise-Vibration-Harshness (NVH) modeling and analysis workflow for electric induction drives in E-mobility and hybrid applications due to magnetic force excitation is presented. It is well suited for predicting the acoustic and structural dynamic characteristics and the cross-domain causal physical paths for electric induction drives with high reliability in an early phase of advanced engineering. A combined nonlinear analytic and Finite-Element modeling structure for the electrodynamic and the structural mechanic domain is developed to embed the entire NVH-simulation in one simulation environment. Separating physical quantities as magnetic airgap forces and operational structural deflections into design inherent generic vector fields and solely operation point dependent amplitudes within a modal space representation yields an efficient simulation workflow. The working point dependent E-drive behavior can be described by order reduced models. Hence the NVH-simulation is finally performed based on modal force response superposition. This allows an effective connection of the NVH-models to various E-drive and control topologies such as induction drives for simulating the NVH-behavior of arbitrary operation cycles. The entire modeling and simulation procedure will be shown by means of a squirrel-cage induction E-motor in EV and hybrid applications. All significant electrodynamic and mechanic noise contributions, influences and sources will be analyzed. Critical working points and speeds are identified and operational structural deflections at resonances are highlighted. The high reliability of the presented NVH-modeling approach will be verified by using numerical and measured acoustic run-up test spectrograms for the induction motor.

The automotive industry is currently facing major changes of its development due to new social, environmental and economic challenges. The sector needs to find sustainable solutions which do not hinder the customers’ expectancies. The solutions extend from combustion engine optimization up to vehicle electrification. Drivetrain electrification is currently a topic of high interest and in the case of hybrid vehicles, the design focus is set on the power density and the efficiency. Beside the electric machine technologies, the cooling system plays a preponderant to meet the requirements of the sector especially concerning the continuous power and the repeatability of the performance. Due to the complexity of developing multiphase cooling system, it is necessary to consider the topic during the early development phase to achieve the maturity required for the implementation in a vehicle. The increasing electrification of the vehicles sets higher challenges for the electrical as well as the thermal design of the machine. Hence reliable and accurate modelling approaches are required. This paper is focused on the thermal modelling of electric machine considering the automotive boundary conditions. The paper describes therefore the required models for temperature estimation before discussing the influence of the machine environment on its performances.

A multi-objective optimization of PMSMs (permanent-magnet synchronous machines) for electric vehicles is presented in this paper. Besides of typical KPIs (key performance indicators: e.g.: power, machine losses, torque ripple, etc.), the capability to control the PMSMs without a rotor position sensor is considered. The objectives for the self-sensing (rotor position sensorless) control capability are on the one hand to keep an adequate primary magnetic anisotropy of the machine up to the maximum torque. On the other hand, both the mean and the peak to peak values of the estimated rotor position error due to secondary magnetic anisotropies are kept small. It is shown that, the optimized design is competitive compared to an optimized design without considering the SSCC (self-sensing control capability). The good self-sensing control performance of the optimized design is confirmed by simulation results.

The certification of consumption and emissions based on the NEDC has been subject to substantial criticism not only because of so called “Defeat Devices” – in 2017 the implementation of WLTP and RDE into the regulatory framework is aimed at addressing this criticism with Europe taking the leadership on emission regulation. The introduced RDE regulation is therefore meaning to determine emissions based on a real-life operation of a vehicle by introducing the driving cycle itself as the unknown. This results in a significant increase of the complexity from a development and certification perspective.

The introduction of Real Driving Emission (RDE) legislation requires the review of pollutant emission of vehicles under varying environmental conditions and driving profiles. A specific challenge for light duty Diesel vehicles arises from low load driving profiles under cold environmental temperature conditions and/or reduced ambient air pressure (i.e. operation in altitude). Under such boundary conditions the component temperatures and gas temperatures in the combustion chamber and the exhaust aftertreatment system are reduced which impedes engine out emissioning as well as exhaust gas aftertreatment. To face this challenges innovative engine technologies such as variable valve train actuation (VVA), charge air heater, electrically heated catalysts (eDOC) and also hybridization concepts are under consideration. This paper investigates the potential of valve train variabilities (i.e. variable valve lift) more in detail. Strategies like cylinder deactivation and second exhaust valve lift (SEVL) are evaluated for RDE relevant low load driving conditions based on a 1D GT Power simulation. The coupling with a physical simulation model of the exhaust aftertreatment processes allows not only for the judgment of the impacts on NOX engine-out emissions and fuel consumption but also on tailpipe emissions.

This paper discusses the qualification of the AVL 492 Gas PEMS iS for RDE measurements. The Gas PEMS iS is a mobile measurement device for gaseous components in the exhaust gas of combustion engines especially under real driving conditions. RDE boundary conditions are varying ambient temperature and humidity and also atmospheric pressure variations due to altitude changes. Beside tests on the road mounted on the trailer coupling of passenger cars or mounted inside the trunk the device was tested during elevated ambient conditions in a climate chamber. The tests were done with calibration gas to maintain stable concentrations and the gas was humidified with a bubbler to a dew point of 51 °C in order to simulate real exhaust gas. The influence of sudden temperature changes between - 7 °C and + 40 °C and ambient humidity changes between 20 % rel. and 90 % rel. to the measurement signals of CO, CO2, NO and NO2 has been investigated. Furthermore a pressure change up to a sea level of 3000 m (700 mbar abs.) was studied. In summary the AVL 492 Gas PEMS iS performed very well under these elevated ambient conditions. The deviation of all measured concentrations remained within 2 % rel. of the measured value.

Passenger car manufacturers are currently facing the task of controlling the real-driving emissions of cars on public roads in spite of highly varying driving conditions to such an extent that these emissions deviate only little or not at all from the emissions established during standardized type approval testing. The legislation on real-driving emissions (RDE) primarily aims at the particle count and nitrogen emissions. The widespread use of particle filters in modern diesel cars has already brought particle emissions produced during combustion down to an extremely low level; however, effectively limiting nitrogen emissions is in focus. The Diesel Systems division of Robert Bosch GmbH is carrying out comprehensive studies in order to define technical measures that can support manufacturers by effectively limiting the real-driving emissions. Since these studies had not been completed yet when this paper was written, some of the results presented on the following pages are preliminary and may get updated during the actual presentation. As the authors of this paper wish to present the most up-to-date results during their presentation, they kindly ask for readers’ understanding for this procedure. The results of the studies, some of which are presented in this paper, indicate that the RDE requirements can be met through an intelligent combination of measures optimizing the engine and the exhaust gas aftertreatment system – without negatively impacting fuel consumption and driving performance. While the paper presented at the 2016 Stuttgart Symposium /1/ had focused on engine-related measures on the air system, this paper will primarily deal with temperature management of the engine and exhaust systems. Mild electrification, which is to be expected due to the lowered CO2 fleet emission limits applicable as of 2020, can contribute to meeting the emission targets but does not represent an indispensable prerequisite to meet nitrogen oxide targets.

Fast running battery pack electrical and thermal models were created from electrical test data and battery geometry. These fast running models were used in simulating lifetime battery temperature and cooling performance. These models include the battery, the pack structure, cold plates, and the electrical behavior. The models are capable of being integrated into either 3D or 1D models. These fast battery models allow design changes to be thoroughly evaluated at each step in a vehicle program. Thorough and detailed evaluation is necessary because packs are very sensitive to temperature. Extended periods of elevated temperatures or short periods of high temperatures can significantly decrease battery life. Additionally, the temperature of the battery affects vehicle performance and efficiency. To ensure batteries both perform and last, a battery thermal protection system is usually required. A properly designed thermal protection system is efficient and capable of cooling the battery under a broad range of driving and storage conditions. To evaluate how well a cooling system protects a battery, the lifetime of the vehicle may be simulated. However, simulating these long time frames are a challenge due to the limited time available. Fast running simulations solve this problem. These fast thermal models are generated from 3D models. These 3D models are used to generate the system models. The equivalent system model includes batteries, pack structure, heat sources in the pack, and cold plates. Several key assumptions allow these system models to be generated quickly and preserve accuracy. The 3D modeling step ensures these assumptions are satisfied. This fast thermal model is used to speed up the 3D models by replacing the parts of the 3D geometry. This fast running thermal system model also runs on common system tools. The fast electrical model is used to predict electrical performance and heat generation in the batteries. This electrical model is created from electrical test data. While there are many established ways to structure tests and extract electrical parameters, a unique approach was taken. This approach allows both lab data and vehicle data to be used. This fast model typically runs in dramatically less time than required by a 3D model while achieving with nearly equivalent accuracy.

Battery electric vehicles (BEV) are not dependent on fossil fuels. If electricity is obtained from renewable energies, the conflict between an increasing number of vehicles and finite resources could be mitigated. Further, the driving of a BEV is in any case exhaust-emission-free. A permanent operation in low-emission zones is thus possible. Apart from this, driving performance can be enhanced, e.g. increased acceleration due to the better torque characteristic of the electric motors.

This paper presents a fully coupled thermal 3D-CFD RANS simulation of a comprehensive and fully detailed car model for the Honda CR-V SUV model. The simulation mainly focuses on the thermal aspects within the underhood of the car. All relevant sources of heat are taken into account, including the engine, the exhaust system, the radiator and condenser, as well as the fans attached to it. The definition of the adjacent mesh blocks and the corresponding interfaces is done automatically by the unstructured meshing tool, which reduces significantly the engineering time required to set up the computation. The new meshing approach also ensures conformal connections between all blocks, thus eliminating inaccuracies typically caused by the interpolation due to non-matching block connections. To model the surface-to-surface radiation, a formulation based on the radiosity equation is chosen and implemented in the CFD code. The simulation has been conducted on different meshes with up to 400 million Cells.

Metal and ceramic powders are the basis for many technical and industrial processes and applications, such as powder metallurgy, thermal spraying, electronics and catalysis. Nevertheless, there is still a need for further developments, because the powdery raw materials eventually determine the properties of final products and may be the cause of the problems in the processing of these: Impurities or corrosion processes at the powder production (e.g. by the grinding processes) can have a disadvantageous effect or the particle shape leads to a greater abrasion or a rough coating texture.

The increasing use of hybrid lightweight structures in the automotive industry results in new challenges in the area of multi-material interfaces. Insufficient bonding quality between two different materials, especially in highly loaded structures, affects the component’s performance. Hence, it is very important to monitor the bonding quality during the multi-material component fabrication process obtaining a reliable save-lifedesign. Flat specimens, consisting of sheet steel and organic sheet layers were examined using air-coupled ultrasound transducers in reflection setup. By slanted incidence of the ultrasound on the profile’s surface, guided waves were excited in the specimen and delaminated areas could be visualized due to changed phase values in the received signal. Furthermore, a 3D-hybrid cap profile consisting of sheet steel, organic sheet layers and injection molded reinforcing ribs was examined using a special transducer setup. The received air-coupled guided wave signal reveals different signatures of bonded and delaminated organic sheets. Simulations of the guided wave propagation agree with the findings.

Am Institut für Fahrzeugkonzepte des Deutschen Zentrums für Luft- und Raumfahrt (DLR) wird im Rahmen des Verbundforschungsprojektes Next Generation Car (NGC) ein sehr leichtes Fahrzeugkonzept der L7e-Klasse als Forschungsdemonstrator mit einem Karosseriegewicht von nur 90 kg entwickelt, das gleichzeitig sehr gute Crasheigenschaften aufweist. Das Strukturkonzept beinhaltet die konsequente Anwendung von Hybrid-Werkstoffen in einer Sandwichbauweise, so dass sich eine leichte Struktur ergibt, die aus vergleichsweise wenigen, einfach geformten Bauteilen besteht. Diese Struktur wird durch FE-Simulationen sowie durch statische und dynamische Versuche für verschiedene Crashlastfälle untersucht. Die hohen Anforderungen an Gewicht und Crashsicherheit erfordern außerdem ein leichtes, auf die Crashszenarien abgestimmtes Fahrwerkskonzept, das ebenfalls simulativ und experimentell untersucht wird. Die Ergebnisse dieser Untersuchungen werden hier vorgestellt.

Automated Driving (AD) has significantly evolved during the last years. Starting with DARPA’s Grand Challenge in 2004 and 2005, as well as the Urban Challenge in 2007 with a clear focus on university research, we see today first AD systems on the market. Even more are being announced, both by traditional automotive OEMs as well as by startups and IT companies that have never built cars before.

The German government intends to increase the number of electric cars registered in Germany to one million by 2020. This ambitious goal is stated in its „national road map for electromobility“ [1]. At the beginning of 2016 the quantity of registered electric cars counts only 25.502 [2]. One likely cause of this discrepancy is the limited cruising range of electric cars in comparison to that of vehicles powered by an internal-combustion engine. This perception is empowered by the fact that the cruising range is reduced significantly during winter days due to the energy demand for cabin heating.

Recently, great efforts are being made to develop filter media which fulfill the requirements on a good cabin air quality. Based on the nonwoven technology new media concepts were developed. With the new generation of fine dust cabin air filters it is possible to achieve separation efficiencies of more than 80 % for a test aerosol (NaCl aerosol) at the most penetrating particle size (MPPS) by maintaining other important factors like pressure loss and filter life time. It can be shown that this new filter media concept is able to better maintain the particle separation efficiency over the filter life time under realistic conditions. Usually cabin air filter performance is measured according DIN 71460-1 under laboratory conditions. In order to improve the properties of the filter media towards their real-life behavior experiments were conducted with a test car. Here the corresponding particle concentrations in the cabin were measured under varying driving situations and environmental conditions.

At night, an unobstructed view onto the surrounding traffic is particularly important for safety. The eyes adapted to the dark are sensitive to light stimulus. When driving on a wetted road, water and dirt can be swirled up and wet the vehicle glass. Thus water accumulations of varying sizes and shapes arise and soil the window. The light can be refracted in these water accumulations and cause brightening. These brightening can lead to distraction and even glare. Therefore, a new evaluation method is presented which assesses the brightening of droplets on a horizontal glass plane depending on the light source and the water accumulation. It provides information about the brightening behaviour of droplets and the impact factors of the light source and the soiled window.

The evaluation of the ergonomic design of driver cabins is often done by asking subjects. This paper describes a motion capturing method that allows the objective analysis and evaluation of gripping areas and of the accessibility of control elements in driver cabins. A camera films subjects while they are executing use cases in a driver cabin. Simultaneously, the positions of their joints in space are measured. These positions allow calculating the angles of the joints based on the frames of the camera. Finally, comparing them with comfort angles from the literature allows the ergonomic evaluation of gripping areas. In particular, this paper explains the motion capturing process itself, the elevation procedures taken from literature and adapted to the method, and the statistical validation of the method by subjects.

In context of drive systems’ electrification, drive functions have to be fulfilled by new systems and subsystems. Thereby, various aspects could be differentiated. The first one is the substitution, which means: new subsystems carry over the functions of conventional drive systems. For example, an electric machine replaces the combustion engine within a central drive. Another aspect is a new kind of assignment of established functions to one or more subsystems. Thus, in multi-speed gearboxes the electric machine instead of frictional-locking elements like synchronisation and clutches should perform the synchronisation of speed. In addition, the electrification offers the realisation of new drive functions, which were not feasible yet. These functions are e.g. recuperation and torque vectoring. (s. section 2.2) Especially, if new drive functions have to be fulfilled – like combustion engine start in hybrid-electric vehicles –the consequences for the residual drive system and the user as well as the achievement of development objectives are not evaluable.Even serial production battery electric vehicles provide less complex drivetrain topologies, it is rewarding to have a look at alternative solutions using multi-speed gearboxes. Thereby, the fulfilment of established functions by new or established subsystems is sufficient challenging the development of electric vehicles regarding the changes in operation conditions.Manifold possibilities of function realisation in electrified drive systems result in a high degree of freedom within the development. Their benefit and effects have to be analysed considering the interdependencies in whole system context. This article discusses possible solutions of functions’ fulfilment and reorganisation in battery electric drive systems and their benefits. The associated effects on the residual drive system and its subsystems are derived and discussed.

Electrification of the vehicle powertrain is a possibility to comply with the legal requirements in carbon dioxide emissions. Hybrid powertrains, combining internal combustion engines (ICE) and electric motors (EM), are a potential solution to meet the requirements of emission limits, customer experience and brand-specific characteristics. Hybrid powertrains can be classified by their level of hybridization.

Hybrid vehicles provide an opportunity to meet the rising demands on modern vehicles. A central role plays the reduction of fuel consumption by using, for instance, appropriate control strategies. They specify the operating points of the built-in energy converters, of the electric machine and of the combustion engine.This article compares heuristic control strategies for parallel hybrid vehicles. To realize this, a fuzzylogic controller (FLC), as well as the Electric Assist Control Strategy (EACS) approach and the map-based Equivalent Consumption Minimization Strategy (ECMS) are employed. For calculating the fuel consumption, an empirical model of the power train is utilized. To assess the strategies’ performance in diverse driving situations, the results of six driving cycles are compared to the optimal solution based on dynamic programming (DP). Furthermore, the multiple approaches are optimized regarding their parameters. For this purpose, the Particle Swarm Optimization and the Bees Algorithm are employed as two natural analogue methods. This article demonstrates that heuristic approaches provide online-capable possibilities for operating hybrid power trains including a performance close to the global optimum.

Today, HEV operating strategies are optimized mainly in regards to the legal driving cycles. This leads to increased fuel consumption in customer operation, as this was not part of the optimization process. The paper shows, how learning algorithms can be used to extend a control unit applicable operation strategy, in the way that the operation parameters can be optimally fit to cycle as well as customer operation. Hence, the optimum of fuel consumption and CO2 can be achieved. Based on an adaptive operation strategy, best parameterization is chosen by a driving style- and driving environment identifier (from the DAS-sector), using identification algorithms, which are validated by measurement data. The parameter sets for different driving style and environment combinations have previously been collected. Thereafter, a concept to enhance the operating strategy by machine learning is proposed, which utilizes an individual adaption to the driver and achieves the global consumption optimum independent on the driving situation. The paper displays the CO2 reductions of the learning operating strategy in comparison to a basic heuristic operating strategy. The investigations show, that in real driving conditions on average 14% CO2, can be saved using a controlled learning operating strategy.

To design modern decision-making software applications, a large set of diagrams is required as prescribed by the SysML taxonomy. Such abstractions and related artifacts as test cases and requirements are a key enabler of Model-based Development. Thanks to them, each actor, no matter whether they are software architects, software developers or validation engineers, has access only to the right portion of an ever growing complexity while staying synchronized. However, in popular tools that support Modelbased Development, these artifacts are independent diagrams, connected at best through cumbersome links. To realize the full benefits of Model-based and Test-driven approach, all phases of development need to be seamlessly connected with each diagram being a projection of the underlying unified system. Further, traceability to requirements should naturally emerge from the workflow rather than as an additional activity to meet regulatory or process requirements. Definition, and front-loading of test activities, enabling Test-driven Development helps control code bloat and compliance to stated requirements. Language workbenches enabling design of Domain Specific Languages (DSLs), and projectional editing can make this vision a reality. mbeddr, an opensource set of DSLs, implemented on another open-source language workbench MPS demonstrates how this can be achieved though limited mostly to textual projections. However, the fact that it is open source makes it easier to design new abstractions and graphical projections to support true Model-based Development.

In today’s development processes of motor vehicles, the dynamics with which the software and hardware process passes the necessary iterative loops is very high. The influence on the reliability of the vehicle diagnosis is particularly great because of the combination of increasing networking and increasing diversity of variants. The resulting complex fault images have their origin both in on-board diagnostics and in offboard diagnostics. Error identification and analysis cannot be carried out absolutely and not reliably due to prototypical implementations or missing error experiences in the early phase of development. This paper presents two new and complementary concepts for analyzing, interpreting and stopping diagnostic-related faults in the powertrain in the early development phase. The first concept includes the safeguarding of complex and generic script-based off-board diagnostics. For this purpose, an adaptive framework is used, based on the standardized script language OTX (Open Test Sequence Exchange) according to ISO 13209. The second concept involves several methods for pattern recognition that form the framework for a heuristic knowledge base for DTC (Diagnostic Trouble Code) errors. The combination of the two concepts enables a holistic interpretation and safeguarding of the off-board diagnostics as well as the advanced analysis of the error memory entries in the on-board diagnostics.

Feature complexity in modern vehicles is continuously rising, requiring significant additional effort to assure the quality of the embedded software. An efficient and effective quality assurance strategy is central for deployment of a successful software product. However, test strategy decisions are usually made experience-based with poor documentation and scalability to large development teams. Hence, we propose to use the testers experience for quantifying quality characteristics as well as the impact of different tests and resulting bug fixes on the same. Then, optimization algorithms can be applied to derive a nearly optimal test strategy. This leads to an approach where test strategy decisions are transparent, scalable to different users and conserve testing experience. This paper takes the first step by examining the impact of strategical decisions on the resulting software quality. Quantification takes place using adequate software metrics. The impact of the quality assurance strategy on product quality is identified based on data of several industry projects using statistical procedures.

Blowby is an aerosol which is produced in the crankcase of an internal combustion engine. The root cause is a gas leakage, which occurs at the piston rings of the combustion chamber, at the valve shafts and at the bearings of the turbo charger. At the same time different kinds of atomisation mechanisms and also condensation cause a significant loading of the blowby with small oil droplets. The amount of dispensed oil and also the particle size distribution of the droplets depend basically on the engine design and the operating conditions. In general the particle size ranges from a few microns down to nanometres. Additional components of the blowby are fuel, water, soot and other products of the complete and incomplete combustion.

The subject of this article is the measurement of pressure signals in the hydraulic chain tensioner of a camshaft drive. For this, as well as other components of combustion engines, for example high pressure fuel pumps, oil pumps, hydraulic actuators and dampers, such measurements are essential for design considerations during the research and development phase. The interpretation of the pressure signals can provide insights about the function or the reliability of the respective components.The tests described here show that both the sensor design and the sensor adaptation have a significant influence on the recorded signal pattern. Differences of several hundred percent have been demonstrated on the same chain tensioner with the use of different sensors during highly dynamic oscillation. Based on the available data, we will discuss how – aside from system performance – influences of the sensor and adaptation contribute to this phenomenon.

The reduction of mechanical losses in combustion engines contributes significantly to the goal of reducing CO2 emissions. For several years, extensive parameter studies have been performed at MAHLE on passenger car diesel and gasoline engines [1–6]. It should be assumed that the CO2 emissions of commercial vehicles will also be strictly limited by future regulations. Fuel consumption has also traditionally played a decisive role for the end customers of commercial vehicle engines because it contributes to the „total cost of ownership.“ For these reasons, an additional friction power test bench has been set up at MAHLE to take measurements on a fired heavy duty diesel (HDD) engine.

In 2036, the automobile celebrates its 150th anniversary. For this occasion, numerous stakeholders from science and business work closely together in a public-private partnership called ARENA2036. ARENA is an acronym for Active Research Environment for the Next generation of Automobiles. Project participants include the University of Stuttgart, the Fraunhofer Society, DLR, Daimler, BASF, FESTO, Bosch, Hewlett-Packard, KUKA, Siemens, FARO and many more. ARENA2036 is a research and development partnership in the field of lightweight construction and innovative production technologies. ARENA’s main goal is to prepare the way for the automotive production of the future in order to maintain Germany’s world-leading location for automotive production. One lead project of ARENA2036 is called „Digitaler Schatten“ which is translated in this paper as „Digital Shadow“. [ARENA2036, 2017]

Arc welding is one of the main manufacturing processes in the production of body in white structures in the automotive industry. Typically, robots are used to perform the welding process automatically, as shown in Figure 1. However, a main drawback still is the need for precise fixturing of workpieces to enable a correct process execution with the once generated robot program [1]. Moreover, there might be geometric deviations between the manufactured parts to be welded due to changing conditions at the suppliers productions or the usage of different production technologies like casting or pultrusion. Therefore, the single parts of a welding assembly in the body in white production have to be manufactured with tight tolerances to enable reproducible joint geometries and constant welding process results.

Nowadays, industrial production is characterized in many areas by automated and machine manufacturing processes. Manpower is used when the complexity is high and the use is economically sustainable [1]. Procurement is often carried out statically, which can lead to waiting times for machines at high capacity utilization [2]. Due to the increasing variety of products, rapid technology changes and highly dynamic sales markets, there is a need to make static production processes more dynamic [3]. The research of „Industrie 4.0“ (I4.0) is based on the demand for increasing dynamic of industrial production [3]. One task in I4.0 is the generation of a complex network of plants, machines and people, in the industrial production of the future [4]. In control engineering, central control systems are used to enable intelligent communication between plants and machines. The goal is to create intelligent production.

Since about three years, DigitPro, a sub-project of the government funded research project Active Research Environment for the Next generation of Automobile (ARENA2036) works on the development of a Digital Prototype, a closed simulation process chain which not only covers different simulation disciplines such as crushing or process analysis, but also various material modeling approaches on the micro-, meso-, and macro level. Various software tools are being used by the project partners, namely the German Aerospace Center (DLR), the Institute of Textile Technology and Process Engineering (ITV), and the Institute of Aircraft Design (IFB) at the University of Stuttgart. The core of the Digital Prototype is a software tool called Envyo® being developed during the project runtime. It allows the project partners to exchange data from the different simulation programs being used, utilizing the open source HDF5 binary data format, and makes the data available for further analysis with an implemented data mapping process. This mapping algorithm allows for the transfer of information from the process simulation to the structural analysis, the homogenization and clustering of material parameter being generated with the use of representative unit cells (RUC) and the automation of predefined simulation processes including optimization loops for the most important manufacturing parameters. Within this paper, current developments of the Digital Prototype will be introduced and the influence of a closed simulation process chain will be shown.

Increasing customer demands regarding comfort and safety in the automotive sector lead to a constantly increasing number of driver assistance systems (DAS) in vehicles. The resulting expansion of the functional spectrum leads on the one hand to a incremental realization of Vision Zero, but on the other hand to an increase in the complexity of the overall system, FIGURE 1. The ultrasonic, camera, radar and the emerging lidar sensors, which are used to implement comfort and safety functions, usually operate independently resulting in a decentralized decision making process of the systems. A decentralized approach is applied successfully for traditional driver assistance applications, where the driver is usually being informed about dangerous situations by a warning signal. Higher automation, however, requires a combination of the measured data. This so-called sensor fusion and the resulting possibility to create an environmental model are seen as a necessary basis for the realization of highly-automated driving.

To achieve current and future emission targets, the systematic further development of the conventional drive system with internal combustion engine and exhaust gas aftertreatment is becoming extremely important given its high market penetration at Mercedes- Benz. The combination of the Mercedes-Benz spray-guided combustion system with third-generation piezoelectric injectors (BlueDIRECT) is already helping sustainably undercut not just the limits for gaseous emissions but also the particulate number limit for EU6c (09/2017). To meet the Green Technology Leadership requirements, Mercedes-Benz became the world’s first manufacturer in early 2014 to use a gasoline particulate filter in the S-Class with BlueDIRECT engine. In future, the company also intends to roll out gasoline particulate filter technology in other vehicle models in the market. This paper sets out the requisite development steps for the successful market introduction of the gasoline particulate filter in relation to the particulate filter design, testing and validation. The development of the gasoline particulate filter technology is essentially influenced in this respect by the filtration efficiency, the exhaust gas backpressure and the installation space in the vehicle.

During the early days of combustion engine development, inventors and researchers soon discovered that, among many other issues, high compression-end-temperatures and thereby induced uncontrolled self-inflaming of the fuel / air mixture (later called knocking) as well as mechanical failure of engine components due to excessively high combustion- and exhaust gas temperatures were a major challenge when it came to optimizing their engines power density as well as high load efficiency. The impact of these effects further increased, when first inventors started to add external compressors (later called superchargers) as means of enhancing the air density and thus oxygen mass inside the combustion chamber.

Fig. 1 shows a typical development process with CFD. For the left bank in this figure, an accurate predictive model, which does not rely on specific measured data, is required. 3D-CFD can be used for the prediction (1), however, most conventional (0D) combustion models (2) for 1D-CFD usually require calibration process for each engine. Although the calibrated model is applicable to the similar engine type, there is a limit to different new engines.

The prediction of the maximum resistant torque of the steering wheel is an essential part of the vehicle development process. The reference benchmark for the evaluation of this maximum steering wheel torque is the static parking manoeuver. Numerical simulations and experimental measurements, which predict and verify this torque, show a nonnegligible deviance. The current static parking manoeuvre measurement procedure shows a high variability in the measurements and the cause of this deviation is difficult to identify. Therefore, the current static parking measurement procedure needs to be more precise and accurate. In order to achieve this target, the work presented here reveals the main sources of results uncertainty and evaluates the influence of the principal boundary condition parameters. Based on the investigations an optimized measurement procedure, which can be taken as absolute reference benchmark for the prediction of the steering wheel resistant torque, is derived. This new method is then used to analyse the influence of the vehicle parameters on steering wheel resistant torque.

More and more cars available with active chassis systems have entered the market in the recent years. These systems are used to enhance driving dynamics or ride comfort. Over the years, they evolved from pure mechanical concepts over hydraulic variants to pure electromechanical types. However, from a different point of view, the vehicle itself has been subject to optimizations to further increase efficiency for even more years. The goal is to decrease the effort that is needed to move the vehicle. This is further encouraged by stricter laws concerning vehicle emissions all over the world.

The increasing cost-, competition- and time-pressure forces the vehicle design department of an automobile manufacturer to increase the digitisation level of their development processes. Therefore it is the target to economise cost intensive test carriers with the help of a valid and robust early development stage. The design of a suspension at the early development stage faces the challenge to solve a strong nonlinear, multi-criteria and overestimated optimisation problem. Thus, targets for the vehicle dynamics and vehicle comfort can be adjusted by a plurality of component properties, which have strong interdependencies and trade-offs. Therefore, a structured axle design method is required, which helps to quickly find a robust design of a vehicle’s suspension.

The charging interface between grid and electric vehicles is new. Energy and automotive industry have to co-operate for a successful introduction of e-mobility. There are plenty of challenges to provide a proper co-operation of these „two worlds“. From the view of the energy provider integration of e-mobility into smart grid is important, which includes effective dynamic load management and the use of the HV-Batteries in the vehicles to store and feedback energy. The user expects sufficient and reliable charging points to re-charge his electric vehicle everywhere and at any time. Keys for an infrastructure accepted by users are easy to use and secure data transfer of personal data.

With increasing demand of market and society for locally emission-free transportation, battery electric vehicles have gained significant importance, and an increasing number of passenger cars with increasing range and affordable prices becomes available on the market. One of the main concerns with handling of battery electric vehicles is the charging process. Charging of electric vehicles can be differentiated by use case and charging power. The charging time required for 100 km available range of the electric vehicles decreases with the charging power applied to the vehicle battery.

Bringing new unknown technologies and unique features into a market is one option to acquire new customers. Today, some electric vehicle manufacturers follow this strategy to conquer a market (e.g. gullwing doors of Tesla Model X, carbon-fibercarbody with coach door entry of BWM i3). This represents a considerable risk for Original Equipment Manufacturers (OEM)s and their suppliers since the impact of a totally new and unknown technology with extra charge to the customers is unknown. On the other hand, a new car model with unique stunning features may lead to a severe buying interest. In this paper, a new assessment methodology for electric vehicle technology concepts is presented on the basis of the Quality Function Deployment (QFD) method. This methodology allows a technical-scientific assessment concepts including energy storage and powertrain in the early development phase and also a comparison of variants. The principle of this methodology is explained by the example of a battery charging station. Subsequently, the evaluation process for an innovative electric vehicle with two complementary energy storage devices (lithium-ion accumulator and an additional flywheel storage device) is outlined. Both or a single storage devices can be in operation with respect to the power requirement in a specific driving situation (acceleration, braking, steady drive). This hybrid storage concept is implemented in an electric scooter prototype and is in a status of road testing. The paper shows how the method for integrating customer requirements and new technical features can be used in a concept evaluation.

In the field of Diesel injection systems of combustion engines, numerical modelling can be regarded as an essential approach to the dynamic in-depth analysis of the nozzle internal flow. Nonetheless, the low lifts process in numerical modelling that opens the needle from the closed state is usually neglected, leading to the incomplete numerical injection model which results in an incomplete analysis. In the following study, a more complete numerical injection model was introduced to resolve the problem of the needle opening, and a detailed comparative investigation was performed pertaining to the effects of the injection process at low needle lifts on the follow-up dynamic simulation processes. For this study, a conical-orifice injector nozzle was used. CFD (Computational Fluid Dynamics) was implemented to study the behaviours of the internal nozzle flow and the corresponding spray characteristics. An external library concept was introduced to link the process of the internal nozzle injection with the formation of spray. Additionally, several comparative dynamic simulations were performed under a double-axis system. In terms of the internal nozzle flow, the comparison of experimental result shows that the absence of low lifts process in calculation causes simulation error in the follow-up dynamic injection process. In terms of the corresponding spray behaviours, the absence of low lifts process further influences the atomization effect, to the extent of leading to more deviation in the spray angle. The conclusion is that the complete negligence of low needle lifts process in numerical injection simulation is considered not well-accepted. Besides, the processes at low lifts have been proven to be worthy of further investigation. Keywords: Numerical Modelling, Low lifts Process, Conical Diesel Injector, Cavitation, Spray

Commercial vehicles require continual improvements for meeting fuel emission standards, improving diesel aftertreatment systems and optimizing vehicle fuel economy. Aftertreatment systems are temperature sensitive for removing engine out NOx. Most diesel aftertreatment systems show a marked efficiency improvement above 250°C while efficiency generally improves above 300°C. This poses an efficiency issue for vehicles operated at low load. All commercial vehicles operate in low load operation for a portion of the vehicle duty cycle. Idle temperatures reside in the 100°C to 150°C range while engine torque ratings below 200 Nm (150 ft-lbs) have temperatures below 250°C where the aftertreatment system is below its peak efficiency. Vehicles that spend more time in low load operation need a means to increase the exhaust temperature to enable efficient NOx reduction in the aftertreatment system. Cylinder deactivation (CDA) has been shown to increase diesel engine exhaust temperature by approximately 100°C when operating in half engine mode and more than 100°C with less cylinders. The higher temperature improves aftertreatment NOx reduction performance which offers the potential to save vehicle fuel by increasing engine out NO_x levels where the engine operates more fuel efficiently. Additionally, there are inherent fuel economy benefits up to 140 to 180 Nm (100 to 130 ft-lbs) of torque which is independent of the aftertreatment benefits. These benefits can range between 25% and 40% at near idle conditions while slightly higher speeds showed benefits up to 49%. The benefits converge to nominal fuel economy values for normal engine conditions (all cylinders firing) at or around 180 Nm (130 ft-lbs) of torque. Implementing technologies such as CDA for diesel can be used to improve exhaust thermal management during low load operation, World Harmonized Transient Cycle and US Heavy Duty transient emission cycles. This paper will show the benefits of cylinder deactivation for meeting future emission regulations and improving vehicle fuel economy.

The Bosch engine ECU software calculates a model for the exhaust gas temperature at engine outlet valve. This modelled temperature signal is used as a virtual sensor for other software functions (such as EGR temperature model or boost control functionality) because the temperature sensor is not able to show fast temperature changes due to its slow dynamic behavior. Additionally, the sensor value is used for plausibility check of the temperature sensor.

The steady increasing cost pressure and reduced lead time of a car body development while having high quality demands to produce vehicle parts made of modern sheet components in the press shop forces the automotive industry to shorter product and process development times. Therefore numerical simulation methods become more and more important to meet such requirements. The finite element analysis (FEA) meanwhile became a powerful calculation method to assure successful product and manufacturing development. Method is used to generate data of die contact surfaces in order to predict the forming and springback behavior of the single components within shorter given timeframes.

Currently, the strategic use of Big Data is a challenge of utmost relevance for numerous leading enterprises. Following a clear management commitment, most companies have prepared themselves with a considerable IT infrastructure to meet the challenges of data-driven decisions. However, there is often a serious discrepancy between the technical possibilities for intelligent use of Big Data and its actual application for immediately available use cases for product development. This gap can very often be contributed to the lack of organizational development. In order to tap the full potential in the long term, it is not enough to rely on the know-how of data scientists in the short term. In the future, engineers will have to act as data scientists themselves. Hence, a mindset change and corresponding qualification measures are essential.

Standardization and modularization increasingly lead to the use of the same components in various vehicle applications. This results in a continuous increase of the amount of software that needs to be adapted for all variations of these components, since there are specific adjustments that are required for every single vehicle. This level of complexity requires the management of software versions and corresponding calibration data inventories in multiple-year processes. For example, in the drive train or also chassis area we are talking here about well over 350 calibration variations, which have to be calibrated, verified, and delivered in decentralized teams worldwide, based on varying local requirements. This is on the one hand the reason why the quality requirements for the calibration are increasing drastically, since possible errors in the calibration may lead to extensive recall campaigns, if they reproduce themselves in either all or a large majority of the calibration variations. Any potential legal violations resulting from this, such as for example the violation of emissions guidelines, are accompanied by additional requirements regarding tamper-resistant documentation processes.

Automotive industry changes rapidly. So-called Game Changers, like connectivity or piloted driving, do not only influence products, but organization structures and development processes as well. Complexity increases significantly, thus front loading in terms of creating early results, making essential product-decisions and developing validated concepts becomes more important than ever before. Furthermore, the need for using virtual tools in the concept phase increases, since hardware is usually not available in early process stages. The Audi chassis development process has been optimized constantly over the years to cover the above-mentioned challenges. The result is an attribute-based way to derive component design from overall vehicle attributes. This paper describes this process and gives an overview of key factors and requirements to establish such a process.

These days, engineering service providers (ESPs) are often an indispensable part of the automotive value chain. Working on behalf of their customers, manufacturers, and suppliers, ESPs play an important part in the development of vehicles and their systems, functions, and components. The close working relationships between ESPs and their clients are notable for their high level of trust, but rely on ESPs’ mostly not publishing their development contributions. It is a testament to how the collaboration among manufacturers, suppliers, and ESPs has grown over the years that it has become the proven and efficient collaborative network it is today.

When the commercial vehicle market is analyzed from a global perspective, it becomes obvious, that the requirements are significant divers in the various regions. No specific vehicle type or even modular system would be suitable for all markets. The main reasons for that are the following: Legal requirements especially in Europe and in the US, historically follow different rules and traditions, i.e. regarding gross vehicle weights, axle loads and outer dimensions. Moreover the metric system is different from US standards.

Distractions while driving account for about 68 % of all accidents (Dingus, et al., 2016). This is shown by a study from traffic researchers at the Virginia Tech Transportation Institute (VTTI) in Blacksburg. According to this study, especially distractions which include looking away from the road are the most dangerous. For example, the handling of a mobile phone increases the probability of an accident by a factor of 3.6. Consequently, the overall number of accidents in Germany has increased by 12.6 % since 2006 (DESTATIS, 2015).

Advanced driver assistance systems in modern vehicles have achieved an important role with the result that more and more new cars will be equipped with such a system. In addition to the demand of more driving-comfort, the needs for safer vehicles [1] also increases and results in comprehensive and complex assistance systems, which enables almost autonomous driving. On the other hand the manufacturers have to save time and costs in development, which is for example possible by „from road to rig“ approaches [2]. In this way time consuming road tests will be either transferred to the reproducible test environment of test benches or are replaced by early componenttests in a virtual environment, which validates the desired system behavior. Before that background, this contribution shows approaches how advanced driver assistance systems (ADAS) in the entire vehicle can be tested on the test bench under reproducible, customer-oriented conditions, like traffic jam, by using suitable stimulators. The focus of the solutions is on roller test bench testing environments with minimal interference with the test vehicle. Based on this, the stimulation of ultrasonic-distance-sensors for parking assistance as „automotive ultrasonic target simulator“ will gain knowledge on the development process and demonstrates it then on the roller test bench. In order to keep the development of increasingly complex advanced driver assistance systems manageable, the so-designed validation environment provides the developer an approach to be able to test highly in car networked assistance systems quickly and under controlled as well as reproducible conditions.

The document is dedicated to the functional development of advanced driver assistant systems (ADAS) and automated driving (AD) features respectively. The focus is on the importance of driving quality during automated manoeuvres and correlation to the perceived safety feeling of drivers. Further new approaches will be discussed, how this aspects can be considered in the development of ADAS / AD from application on public roads and virtual testing environment respectively.

BOSCH believes that Diesel technology, with its high efficiency, is an important tool to achieve greenhouse gas reductions. BOSCH offers technology that can enable manufacturers of Diesel vehicles to achieve their emissions objectives worldwide, including forthcoming real driving emissions standards.

The phosphorus content in engine oil additives or biodiesel once combusted can lead to phosphorus deposits on close-coupled catalysts and a subsequent irreversible deactivation. Inductively Coupled Plasma – Atomic Emission Spectroscopy (ICP-AES) analysis of catalyst samples showed phosphorus depositions on a lean NOx trap (LNT) that was aged in a car endurance run. Three new LNTs out of the same serial production process were poisoned by a wet impregnation method with ammonium dihydrogen phosphate solution ((NH₄)₂HPO₄), based on the detected phosphorus concentrations. Solely poisoned as well as poisoned and hydrothermally aged LNTs were tested on a synthetic-gas-test-bench. Light off tests were used to determine the poisoning effect on the oxidation behaviour in lean gas and on rich gas conversion. NOx storage tests were done to investigate the impact on the nitrate formation ability of the LNT. The poisoned samples were compared to a hydrothermally aged LNT at 750°C for 20 hours – an often-used aging treatment in literature – and 110 hours at 750°C as well as to the catalyst from the car endurance run. After wet impregnation with (NH₄)₂HPO₄ no significant aging effect on Light Off, water gas shift light off and NOx storage was noticeable. Additional hydrothermal aging for 20 hours at 750°C resulted in a deactivation in lean gas light off and a strong deactivation in water gas shift light off. A degradation in NOx storage was identified whereas the aging effect through hydrothermal aging was stronger than the impact of phosphorus poisoning. Phosphorus had a deactivating effect on the LNT performance but the concentrations found on the car endurance run aged LNT were identified as not critical. Higher concentrations would have led to a much stronger deactivation and should be avoided. The wet impregnation method with ammonium dihydrogen phosphate was identified as a proven method to selectively deactivate specific LNT mechanisms.

Despite stricter legislative emission targets, the provisions on nitrous oxides and fine particles are partially violated severely in European cities. Thus, comprehensive regulations are being prepared including the validation of vehicle emissions in real driving conditions by means of portable measurement systems. In contrast to an NEDC based procedure, the extended utilization of the engine operation map as well as the higher dynamics in real driving is leading to inherently higher engine-out emissions which need to be reduced by highly efficient aftertreatment systems. With a view to fuel consumption, diesel cars provide a distinctively better combustion efficiency compared to gasoline cars and are subsequently an important component to achieve the future European CO₂ fleet emission targets. The further improvements in the overall engine efficiency also induce significant reductions of the exhaust temperature causing additional challenges in the catalyst development. This paper comprises a comparison of different diesel aftertreatment concepts, focusing on urban NOx emission reduction, taking also account of the engine cold start phase. For that purpose real driving patterns, according to legal provisions, were simulated on an Engine-in-the-Loop test bench which allows a precise back-to-back comparison of the particular catalyst systems. The emission results were broken down in detail with regards to the contribution of each system component and finally conclusions on potentials and limitations were drawn.

This contribution presents the control strategy currently used to operate a hexapod as part of a Hardware-in-the-Loop (HiL) simulation environment for mechatronic vehicle axles. Using this control scheme on the test rig achieves high closed-loop position control bandwidth while keeping unwanted interaction forces and torques considerably low. Since the control algorithm includes a feed forward of the mounted axle’s kinematics, the contribution also briefly discusses the implemented model of the axle kinematics and the chosen identification approach. Furthermore, a description of the test rig as well as an impression of the achieved control performance is given by test rig measurements of a rough-road maneuver.

The objective characterization of modern vehicles on roads and test rigs regarding ride comfort delivers a key factor for an efficient vehicle development process. To completely understand the vibration phenomena of a vehicle, detailed information about the subsystem suspension in the relevant frequency range is required. This study presents a method to derive excitation spectra for a dynamic suspension test rig from full vehicle measurements or simulations while passing uneven roads. Hence a method to generate synthetic single-track excitation signals has been developed to simplify the treatment of excitation signals on the test rig as well as in the post processing. Furthermore the presented method has been extended to provide synthetic double-track excitation based on a modal decomposition into heave and roll excitation signals. Additionally, this methodology allows to integrate several vehicle setups, suspension types and ride speeds into the synthesis process to receive a synthetic excitation that is independent from the vehicle setup. In conclusion a recommendation for the shape of a frequency continuous (frequency sweep) excitation signal is given based on the identified excitation spectra.

This paper will present investigations and a methodology for the matching between the vehicle behavior on the road and on the powertrain test rig. The focus lies on the mathematical tire model of Pacejka [1], which is used on the powertrain test rig to describe the force between the tires and the road. If the model parameters of the tire manufacturer are not available, they are determined in an iterative process. For this purpose, the tire parameters are varied in a driving maneuver until the deviation from the road data is reduced to a minimum. In [2], a new methodology has been introduced. This new methodology uses an empirical black box model to describe the difference of the measured signals of the driving maneuvers between the test rig and the road. The inputs of the model are the Pacejka parameters, so that the optimal parameters can be determined with a numerical optimization. This methodology reduces the duration and the effort to calibrate the test rig. In some application scenarios it can be difficult to compute the Pacejka parameter in a single test because the influence of the parameters on the behavior of the transferred force varies with the level of tire slip. Therefore, it is necessary to split the parameter identification based on the Design of Experiment and black box modeling in two different tests with an operating point with a high tire slip level and an operating point with a low tire slip level. In the first test, the slope of the low slip range and in the second test the required Pacejka parameters will be determined.

Road skid resistance is an important functional property of road pavements and monitored on a regular basis by measuring the friction force between a measuring tyre and the wetted pavement. A method is presented to predict skid resistance from optical texture measurement using a rubber friction model. Optical sensors are comparably cheap and easy to combine with existing measurement equipment for pavement monitoring. They are independent of rubber properties and water supply and practically unlimited in range.

Precise knowledge of the friction potential is of great importance for safe longitudinal and lateral control of a car. While today it is mostly the driver who assesses friction values and adapts his driving style accordingly, it will be necessary for future highly automated vehicles to independently obtain information on environmental conditions. Analyses of accident records show that at least 3.6 % of road deaths are due to icy road conditions. However, this number is likely to be significantly higher, since the number of accidents in Germany occurring under icy road conditions without these conditions being identified as primary causes of the accidents, is around 20 % of the total number of accidents [1].

An ideal drainage of road pavements is essential to ensure road safety and to reduce aquaplaning risks; also damages to the road surface geometry ought to be prevented. A profound knowledge of the water absorbing properties of porous asphalt layers implicates the possibility to predict the water runoff capacities and the emerging water film thicknesses especially for critical areas with changing cross slopes as well as the optimal sizing of drainage facilities. Goal of the research and the presented mathematical modelling is the identification of the relevant infiltration parameters based on the special pore structures in the porous pavement layer and hereby the development of a three-dimensional description of the coupling between the free flow on the surface and the drainage process into the porous geometry and the implementation of appropriate conditions on the present hydrodynamic interface. The macroscopic numerical model provides saturations and Darcy velocities and can be linked to results from microscopic simulations based on real asphalt geometries via computer tomographic scans. Different pore size distributions and structural modifications such as soiling processes can be considered. Keywords: reducing aquaplaning risks, permeable pavements, 3D infiltration model, Darcy velocities and saturations in the porous medium, coupling concept by the Beavers-Joseph-Saffman interface condition

The digitization of the entire value chain – from design and development to production to sales and service – is one of the main goals of Daimler AG’s plans for tackling the Fourth Industrial Revolution (Industry 4.0). The Fourth Industrial Revolution will make production processes more flexible and varied. As complexity increases, so too will the individual solutions for automation and cooperation between man and machine (Buschmann, 2016). At the same time, we will get even better at satisfying customers’ wishes for increasingly personalized mobility solutions. That means that our current attempts to achieve a high degree of automation with a low level of flexibility are no longer adequate. By contrast, solutions that make use of future-proof technology and assist people with their individual abilities, flexibility and cognitive intelligence are becoming more important. Our objective must be to enable man and machine to work together efficiently. Individual technological solutions are intended to help employees perform repetitive or overburdening tasks. Individuals, however, must retain the power to decide for themselves. That is because, despite all the changes brought about by the Fourth Industrial Revolution, people – both our customers and employees – will continue to be at the center of what we do.

The prevention of work-related diseases is becoming increasingly important in industrial assembly and logistics. Musculoskeletal disorders are the most common type of disease for work disability days in Germany [1] and are particularly focused on demographic change in functional ergonomics concepts. Overhead activities, heavy lifting and working in non-ergonomic postures lead to diseases of the shoulder [2], which cause long off times of the workers [3].

The demographic change is a not to be underestimated factor on the labor market. For this reason the issues of occupational safety and health will become prioritized topics of labor market policy themes in Germany and Europe [1]. The goal of ergonomics is to implement occupational health and safety and productivity in the workplace and to prevent work-related musculoskeletal disorders (wMSD’s).

In 1893 Rudolf Diesel laid the cornerstone for the later triumphal procession of his engine concept at least in the heavy duty business. With the first serial production engine running in 1897, the huge benefit of this combustion system was demonstrated: 15 kW power out of 19.2 ltr. Displacement at a speed of 172 rpm – a revolution. The specific fuel efficiency (roughly 325 g/kWh) and the weight (almost 5 tons) – improvable from nowadays point of view.

The complexity of newly developed cars in the automotive industry has vastly increased during the last decades. This concerns hardware as well as software aspects. One main challenge is to maintain the established and common development cycles to be able to meet the expectations of the customers. That implies an efficient and effective development and production environment and the constant increase of the quality and the functional range of newly introduced cars.

In addition to the electrification of the powertrain, the automation of the driving functions via the various SAE levels (Techrepublic, 2016) represents one of the main challenges faced by the automotive industry today from both, a competitive and a technical perspective. As early as 2020, vehicles should be technically capable of driving on the motorway without further intervention by the driver. Autonomous driving in urban environments, however, is not expected to hit the market before the year 2030 due to the greater complexity of environment detection and situation analysis and not least because of unresolved legal questions.

The high simulation quality of today’s driving simulators enables investigations with a driving impression close to reality. The possibility of such a realistic vehicle simulation environment allows new test methods of driving dynamics related topics. While the driver immerse in the virtual reality his subjective impression is an important evaluation instrument for the development process of driving dynamics. Benefits of the virtual test drive include a higher reproducibility and a faster generation of vehicle variants compared to real on-road tests. These benefits lead to a better system understanding and can improve the process in the early development stages. Within the framework of this investigation, the Stuttgart Driving Simulator is used to analyze the vehicle’s lateral dynamics. In detail, the vehicle motion after overrunning vertical road unevenness on the autobahn is evaluated. For this investigation a five mass vehicle model including an enhanced damper-topmount model is implemented and used for the simulator study. The vehicle’s model complexity thereby guaranties a realistic impression of driving. Based on real test runs on the autobahn the vehicle’s body movement is measured after overrunning the road unevenness and exactly implemented in the driving simulator. In the virtual scenario a calculated excitation is used. The excitation consists of six impulses of forces and moments and induces a vehicle body motion which is similar to the measured vehicle motion on road. For detailed analysis the excitation can be divided into single impulses according to the vehicle’s degrees of freedom. In the present investigation the rolling and yawing movements are considered and analyzed separately. Drivers can modify the vehicle reaction with the control elements while driving on an autobahn track including road undulation. This approach provides an immediate subjective impression of the resulting excitation. The purpose of this investigation is the objectification of a subjectively harmonic and comfortable coupling of rolling and yawing movement. Here, a driving simulator study is conducted to generate subjective evaluations. A correlation process reveals strong correlations of the subjective evaluations and objective data. This work represents an example using the driving simulator for driving dynamics analysis efficiently and shows the potential of such a realistic whole-vehicle simulation.

As the demands of accelerating the reduction of global greenhouse gas emissions emerging, low-carbon transition in mobility is required. At the transitioning in the transport domain, adoption of battery-electric vehicles (BEV) is expected. In the study of reviewing effects of electrification to vehicle dynamics, difficulties associated with batteries layout and packaging yield lower flexibility of tuning pitch moment of inertia is suggested. If the battery locates at center of the vehicle, dynamic index of pitch moment of inertia α = r2/(a ₁ a ₂ ), where r is the radius of gyration in pitch, and a ₁ , a ₂ are distances between the CG and the front and rear axles respectively, decreases from conventional internal combustion engine (ICE) vehicles, which have large mass near axle apart from CG.

The driving behaviour of a sports car is characterized particularly by its driving dynamics features. Especially Porsche customers have extremely high expectations regarding the driving behaviour. To ensure everyday useability of sports cars, driving comfort is besides the performance another fundamental development target, which classically induces a trade-off. To circumvent this trade-off, mechatronic components are increasingly used while developing chassis systems. On the one hand this procedure enables a better resolution of the target figure concerning performance and comfort, on the other hand it exhibits more complexity and introduces additional test requirements. This stands contrary to the urgent desire to reduce development expenses and its required development timeframe. Within this context, increasing test rig analysis comes into the focus for development of air spring systems. This paper presents a new method to analyse and describe the system behaviour of multi-chamber air springs. On this basis, a statement about the expected driving behaviour can be given even in the early stage of the vehicle development process, although only few cost-intensive test vehicles are available. As a result, system awareness can be increased making use of test rigs to evaluate single components as well as the overall system. Furthermore, the organizational coordination effort during advanced development stages can be reduced.

Among other aspects, the development of combustion processes focuses on demands relating to cylinder charge and charge motion. The geometry of the intake port has a decisive impact in this regard. The aim is to achieve the optimum combination (as the best compromise) of characteristic gas exchange parameters required on the combustion process side under predefined package conditions. This makes it essential to know or determine the optimum (Pareto front) as well as the associated port geometries. This paper demonstrates how a combination of CAD model, CFD simulation and a mathematical substitute model can be used to identify the best possible compromise in terms of gas exchange parameters.

The performances of an internal combustion engine are usually evaluated on the basis of global parameters such as power, torque, fuel consumption, pollutant and acoustic emissions. These depend to some extent on the performances of the single stand-alone components of the engine, but above all are influenced by how the single components are assembled to form the system. For this reason, when engine optimization is performed in a CAE enviroment, the numerical simulation needs to be extended to the entire engine system, comprising cylinders, pipe system, plenums, silencers, aftertreatment devices. The main constraint for an entire engine simulation is the computational burden, therefore suitable modeling approaches have to be adopted in order to balance accuracy and simulation runtime, i.e. introducing suitable simplification in relation with the level of detail required by the analysis [1,2]. In order to simplify the problem, making it possible the simulation of the entire system, the 1D approximation has been traditionally introduced. In this framework, the modeling of the complex shape devices (e.g. air-boxes, plenums, silencers, etc) is addressed resorting to simplified approaches, namely 0D approximation and equivalent 1D pipe schemes [3]. These approaches, although simplified, generally allow, after a process of refinement, calibration and improvement, to build a reliable model of the engine, which can be applied for the investigation of the performance of the engine under different operating conditions and for the optimization of the pipe system.

The CHT-Simulation of heat transfer in radial turbine stages is required for different applications such as the parametrization of lumped capacity heat transfer models. The state of the art regarding the CHT-Simulation of turbine heat transfer consists of the iterative adjustment of a heat transfer coefficient on the turbine housing outer surfaces. The disadvantage of this approach is the need of three simulations per operating point. In the present work, a new approach is introduced which allows the CHTSimulation without defining a heat transfer coefficient so that the numerical effort is reduced to a single simulation per operating point. The new approach is based on an integration of the fluid region surrounding the turbocharger in the simulation model which represents the Ambience.

The new OM 654 four-cylinder diesel-engine is the first engine of the modular Mercedes- Benz engine-family and celebrated its premiere in 2016 in the new E-Class. One of the development objectives apart from optimized weight, emission and fuel consumption was the adjustment to a modular system between diesel / gasoline as well as four- / six cylinder-engines. As a result to the increasing electrification of the powertrain, this focus was indispensable for the engine-family, too. [1]

The Magma engine concept is characterised by a high compression ratio, central injector combustion system employed in a downsized direct-injection gasoline engine. An advanced boosting system and Miller cycle intake-valve closing strategies are used to control combustion knock while maintaining specific performance. A key feature of the Magma concept is the use of high CR without compromise to mainstream full-load performance levels. This paper focuses on development of the Magma combustion system using a singlecylinder engine, including valve event, air motion and injection strategies. Key findings are that early intake-valve closing (EIVC) is effective both in mitigating knock and improving fuel consumption. A load equivalent to 23.6 bar brake mean effective pressure (BMEP) for a multi-cylinder engine has been achieved with a geometric compression ratio of 13:1. Comparison of drive-cycle predictions for the downsized Magma concept versus a contemporary baseline engine indicates fuel consumption savings over WLTC and FTP-75 of 12.5% and 16.4% respectively.

Diesel combustion engines, due to their high efficiency, continue to be attractive powertrains to fulfill existing and future emission standards concerning carbon dioxide (CO₂) and fuel consumption. One main aspect for fulfilling emission targets is the use of highly efficient injection systems operating at high pressure levels of up to 2.500 bar and more. In order to ensure the safe and reliable functioning of these hightech injection systems, the reduction of contamination in the diesel fuel system using highly efficient filter systems is very important. This reduction of contamination consists on the one hand of the filtration of particles, and on the other hand in separation of water droplets out of the diesel fuel. Existing and upcoming highly efficiency filter media show outstanding performance results under severe test conditions either on the test bench, or in field conditions. In order to continue to be able to provide solutions suited to challenging installation packaging, either in the engine bay, under the floor, or near the fuel tank, the existing technology and designs for particulate diesel filtration and water-diesel separation have to be transferred and adapted to modular and flexible design concepts. The new particle fuel filtration concept consists of several small filtration cells where fuel is filtered in parallel through each cell. The small filtration cells allow an individual configuration, and offer the car manufacturer maximum flexibility in terms of packaging and positioning in the vehicle. In this paper an overview of the different new flexible particle filtration concepts will be shown. Furthermore some results from the simulation calculations and some first test results will complete the technical insight into the development phase of these new flexible filtration concepts. The second part of the paper focuses on the new horizontal diesel-water separation concept that is especially designed for underfloor installations spaces where the existing and very well established three-stage diesel water separation shows limitations in terms of packaging. This underfloor diesel-water separation concept is intended to be used as an option for regions with bad fuel quality or high water content in the diesel fuel distributed in the market. The use of diesel fuel filter systems with a very high performance protects modern injection systems and can therefore also be used in areas where the quality of the fuel is poor. Consequently the availability of highly efficient fuel filter systems is an important key factor to the global entry of modern diesel motor technology in growth markets such as Asia, Russia or South America.

To effectively use Computational Fluid Dynamics (CFD) for engine emission development it is necessary to be able to simulate the scavenging flow in the engine. The CFD model for a stratified charged two-stroke engine is even more complex. This model have been tuned and validated with engine tests. Then a procedure has been developed to increase the efficiency of these complete engine CFD simulations. A CFD model has been made of the Husqvarna 560XP two-stroke stratified charged chainsaw engine. The model contains piston, cylinder, inlet system ducting and exhaust muffler. The simulation runs with moving deforming mesh with all ports active. The airflow levels have been fine-tuned with inlet restrictions similar to those that is caused by the air filter and air filter holder. The results and behaviour of the CFD model has a good match to the measured values of the finished product. This gives us confidence in the model and several aspects can now be studied that is virtually impossible to capture by other means.

Briggs & Stratton is the world’s largest producer of gasoline engines for outdoor power equipment and a leading manufacturer & supplier of power equipment including: portable generators, pressure washers, standby generators, jobsite products, residential and commercial lawn and garden equipment.

Today, hand-held power tools are used in specific jobs in many application areas, e.g. garden/landscape maintenance, construction industry and forestry. The market demands a high variety of special tools, which are optimized for each application purpose. Most of them are driven by two-stroke SI (spark ignition) engines equipped with a carburetor. High specific power, simplicity, low weight, low costs and compact design are characteristics of these two-stroke engine powered tools. The use of piston control or reed valves, oil-in-gasoline lubrication and loop scavenging is well established. Significant improvements regarding emission behavior have been achieved in recent years due to stratified scavenging systems which have become a standard.