23. Internationales Stuttgarter Symposium

Automated driving systems can be helpful in a wide range of societal challenges, e.g., mobility-on-demand and transportation logistics for last-mile delivery, by aiding the vehicle driver or taking over the responsibility for the dynamic driving task partially or completely. Ensuring the safety of automated driving systems is no trivial task, even more so for those systems of SAE Level 3 or above. To achieve this, mechanisms are needed that can continuously monitor the system’s operating conditions, also denoted as the system’s operational design domain. This paper presents a safety concept for automated driving systems which uses a combination of onboard runtime monitoring via connected dependability cage and off-board runtime monitoring via a remote command control center, to continuously monitor the system’s ODD. On one side, the connected dependability cage fulfills a double functionality: (1) to monitor continuously the operational design domain of the automated driving system, and (2) to transfer the responsibility in a smooth and safe manner between the automated driving system and the off-board remote safety driver, who is present in the remote command control center. On the other side, the remote command control center enables the remote safety driver the monitoring and takeover of the vehicle’s control. We evaluate our safety concept for automated driving systems in a lab environment and on a test field track and report on results and lessons learned.

The development of autonomous vehicles has been accelerating in the last years. Especially vehicles designed for ride-pooling and ride-hailing are tested in pilot projects and are getting more mature. These autonomous driving Mobility-as-a-Service (AD MaaS) vehicles pose new technical and organizational challenges for the automotive industry: The technological complexity is growing, and new concepts are needed. Furthermore, today’s AD MaaS vehicle projects are characterized by the involvement of different independent organizations. These must agree on a common working mode, overcoming organizational boundaries. To manage the resulting complexity of these projects, new approaches are necessary to modify traditional development processes.This publication presents an approach based on Model-Based Systems Engineering (MBSE). The system of interest is complemented by a superior system level, representing the mobility system. Besides the vehicle, other systems such as the self-driving system, a fleet operator and mobility provider are considered subsystems of the “SoS AD MaaS”.This article is structured into five chapters: A brief introduction, followed by the current state of the art of AD MaaS projects and the relevant basics of MBSE. The methodology and the associated reference system model are described in the third chapter. The application of the approach for an autonomous ride-pooling vehicle is presented in Sect. 4, followed by a discussion of the results and an outlook.

Almost all manufacturers regard lidar sensors as a necessary extension of the environmental sensors already in use for the safe operation of automated driving functions from level 3 (highly automated). Recent developments provide a variety of information and also offer different detection patterns. This enables an extended and situation-dependent optimization of the environment recognition. However, both the different measuring principles and the physical limitations of the measuring principle pose enormous challenges for function development. The better the resolution of the systems, the more extensive the necessary algorithms with the corresponding requirements for real-time processing. Therefore, various examples should be used to explain how basic elements of the traffic infrastructure can be reliably and efficiently detected using lidar. In the field of object detection, the vehicle color is the limiting factor. The need to adapt the vehicle design to the sensor requirements is discussed.

The automotive industry is facing the challenge of gaining knowledge from large datasets—originating for example from the research and development process, IT systems, production, or from fleet data. Problems most likely become manifest in data and result in increased costs. Examples can range from problems in the on-board electrical system to virtual validation of autonomous driving functions in R&D.Hence, one important use case is the automatic detection of anomalous behavior in the data to forecast and identify potential problems as early as possible.We demonstrate new mathematical methods from Topological Data Analysis (TDA) that can help to address these kinds of problems. TDA is a rather new field in mathematics that combines techniques from geometry and topology to analyze noisy datasets. Beside academia, it has been applied successfully to various fields including medicine (identification of tumor cells), finance (fraud detection), and materials science (structure analysis).We highlight two main methods from TDA: the (ball) mapper algorithm and persistent homology and illustrate potential applications in automotive industry. We illustrate these abstract methods and show that they can produce valuable knowledge about potential problems—for example in the automotive context—giving an added value to the customer and the OEM.

Immersion-cooled batteries are gaining more importance when it comes to fast charging, high performance and modular battery design. This is also a challenge for emergency degassing. Which materials and designs are suitable for asymmetric pressures? Negative pressure during filling, high working pressure, even higher burst pressure. At the same time, the component should have a very low overall height. Ideally suitable for modular applications. Particular importance is attached to accelerations in the X, Y and Z directions. A good solution are gas-tight membranes.Gas-tight membranes are made of different materials. In the case of membranes made of metal or plastic, predetermined breaking points are required for opening at a defined overpressure. This requires additional processing steps and here the diaphragm thicknesses are most often weakened to the previously calculated material thickness by means of a laser. The media resistance can be impaired especially at these tapers, and the tolerances are also subject to large fluctuations. This effect is more pronounced with plastics than with metals. Especially if the IPx7 test (1 metre water column) is to be passed. If this type of diaphragm is to be used in liquid-cooled batteries, this “predetermined breaking point” is heavily stressed, since the filling vacuum of over 1 bar is usually far above the bursting pressure. End-of-line testing during the production process is also difficult. A gas-tight PET membrane provides a remedy here. Konzelmann’s engineers have developed alternative gas-tight bursting rings made of plastic. A simple component? Not at all. In contrast to common membranes, e.g. made of PTFE, a PET membrane has no fibre or sponge structure. Thanks to the back-injection technology in combination with a special embossing, the injected plastic binds the membrane securely in the hybrid composite. An innovative rupture sensor can be designed in such a way that the membrane can withstand the high filling vacuum on the one hand and allow a low bursting pressure on the other. Ultimately, a plastic ring is married with a diaphragm in a single process step. Another advantage is the simple 100% end-of-line testing by means of air pressure and optics. Due to the simple design and the low cycle rate, very large quantities can therefore be produced.

Battery thermal runaway is a serious safety concern while catering to high power requirements and faster charging abilities of electric vehicles (EVs). Two different battery cooling concepts, cold plate and immersion cooling are investigated to address the challenges of thermal runaway through numerical simulations. Thermal runaway is a complex 3D multi-physics problem that requires large computational efforts. Therefore, it is desired to have not only accurate but also a faster solution. A synergetic 1D-3D modelling approach is implemented to reduce the simulation time. Pseudo-two-dimensional (P2D) electrochemical battery models along with chemical kinetics model derived from Arrhenius equations are used and coupled to thermal and flow domain to predict three different phases of thermal runaway, namely, initiation, ignition, and propagation. The chemical kinetic reactions driving the thermal runaway with heat generations and venting gas phenomena are embedded into GT-AutoLion, a battery simulation tool of GT-SUITE. In certain extreme operating scenarios, thermal runaway triggered in one cell is seen to propagate to other cells in the case where the cooling was based on cold plate, whereas in case of immersion cooling the propagation of thermal runaway is contained. In summary, the presented simulation strategy found to be effective in choosing and designing the right cooling concept from the safety point of view.

The P3 Charging Index (P3CI) was developed to compare the real charging speed between various battery electric vehicles (BEVs). With the combination of the consumption and the charging curves of BEVs, the recharged kilometers can be mapped over the required charging time. This enables an accurate assessment of the fast-charging behavior of battery electric vehicles. The ideal value of the P3CI of 1.0 corresponds to the ability to recharge 300 km of range within 20 min, enabling a practical long-distance mobility from the customer’s perspective. The current leading edge ranges from a P3CI of 1.03 to 0.91 and the progression of BEV fast charging capability can be inferred by looking at the P3CI over time as follows: While the peak values were ~0.7 in the first release in 2019, the ideal value of 1.0 is now in 2022 exceeded for the first time.

The communication between electric vehicle and charging infrastructure is standardized in the several documents of ISO 15118. One of the recently published parts is ISO 15118-20. In combination with part ISO15118-8 further charging options such as inductive and automated charging can now be implemented in professional solutions. For wired charging solutions extended functions are available. Especially for bi-directional charging with AC or DC current and intelligent load management (dynamic or scheduled charging) valuable and future proof solutions supporting energy transition are provided. In this document the extended potential supporting charging solutions using ISO 15118-20 including a prospect for further developments of the standard, i.e. support of megawatt charging systems is presented.

1) IntroductionThe first approach towards a regulation of Brake Emissions by PMP (Particle Measurement Program) under the United Nations Economic Commission for Europe (UNECE) with a dedicated cycle, defined indicators to be measured and a procedure has been confirmed, the first GTR draft has been presented. The influence of recuperation on Brake Emissions shall be taken into account via so called Friction Brake Share Coefficients—depending on the degree of electrification.2) ChallengesIn the end all measures and vehicle systems that contribute to a reduction of Brake Emission shall be taken into account, which means a huge peak of development on this topic with a respective high demand on test bench capacity.Affected components will not only be software and functions, but also new brake system hardware like Electro Mechanical Brakes, with “true zero drag” and better controllability for brake blending—or integrated lamella brakes with no external emissions.Brake development will reach a new summit to get clean AND customer-friendly systems in the end.3) Next stepsIn the following amendments a method will be released how to generate a vehicle specific Friction Brake Share Coefficient.Truck brakes are the next to be regulated.Another topic to be approached is the procedure for aftermarket parts.4) OutlookAnother level of engineering will be caused by Brake Emission RDE Measurements.Truck regulations will be still more complex than passenger car ones as trucks have got a much wider range of applications.The first investigations on tire side have been kicked off—starting with abrasion.

Modern steering systems feature an electric servo motor to provide the necessary assistance force for comfortable driving and have successfully replaced hydraulic steering systems in passenger vehicle cars. Besides their advantages in terms of consumption reduction and improved control possibility, one major disadvantage is the reduced feedback information originating from the tire-road contact to the driver. To evaluate the feedback behavior of steering systems, steering system test benches are utilized, wherein harmonic signals are introduced into the steering rack, while the resulting steering torque is measured. Current state-of-the-art investigations differentiate between a clamped and a freely swinging steering wheel. This contribution motivates and derives a human grip model, which allows the inclusion of the human driver holding a steering wheel for steering feedback evaluation. Therefore, a 2-DOF spring-damper model is implemented which is able to mimic the driver’s grip performance. This includes a parameter identification procedure and experimental investigations which demonstrate the superiority of the 2-DOF model compared to a classical 1-DOF model reported in literature. Furthermore, experiments are conducted wherein the transfer function of the steering system with a driver holding the steering wheel is derived. It is demonstrated, that the 2-DOF human grip model successfully reproduces the results. Due to its simple implementation, efficient parameterization and its validated performance, the human grip model represents a valid tool for these investigations on a steering system test bench.

Reducing residual drag torque of disc brakes is an increasingly focused topic during the brake development process. Since a few newton meters of residual torque can lead to an unneglectable increase in road load and therefore reduce the range of BEV. In the light of the upcoming rollout of EU7-emission-standards (approx. 2025) the avoidance of every unnecessary brake-pad to -disc contacts is also reinforced for combustion-engine-vehicles’ brakes. As EU7 introduces brake-dust emission limits which are more challenging to meet by vehicles lacking the ability to brake by recuperation. The major research on brake drag is based on subsystem investigations using brake-inertia-dynamometers. While guaranteeing an appropriate accuracy, the laboratory test conditions impede the transferability of the results to vehicle-level since important driving conditions especially wheel-forces are excluded. Against this background this paper is based on a full-vehicle approach determining brake-drag behavior of a series production car on a 3D-vehicle-dynamics test-bench. The main purpose is to analyze the impacts of the entirety of vehicle dynamics on brake-drag using one full-vehicle measuring setup to obtain maximal transferability to real-driving use-cases. Therefore brake-drag is continuously measured by piezoelectric force sensors mounted to the vehicle’s calipers. In addition, brake-fluid pressure, brake disc movement and driving parameters are observed to comprehend the drag causing mechanisms. Beside maneuvers like cornering, cycles derived from real-driving data are implemented. In doing so the influence of certain vehicle dynamics on brake-drag is analyzed since the bench’s variability allows to exclude or add certain driving-dynamic parts, like road excitation.

Several factors are influencing the comfort in passenger cars, some of them belong to vibrations which exert upon the passenger. Usually, typical point of contacts for transmission of the vibrations are considered, i.e. the seat, the driver footwell and the steering wheel. The vibrations are induced from the car itself and from external sources, where uneven roads are on the most important ones. The focus in the paper are vibrations induced by crossing single obstacles. These vibrations are integrated in a driving simulator (hexapod- and viewing-system) by means of additional electrodynamic shakers. The shakers are responsible for the frequency range from 13 Hz to 80 Hz, the hexapod-system partially for frequencies lower than 13 Hz. The system is tested by implementing measured oscillations from a passenger car crossing single obstacles. These real-life oscillations are evaluated on the one hand by a professional test driver in the real car, and on the other hand by drivers (with no special experiences in evaluating comfort in passenger cars) in the extended driving simulator. The results of the evaluations are compared and show good correlations.

The Automotive OS is a software concept that all major carmakers currently pursue with the goal to align the software between all ECUs in the vehicle. However, concrete definitions of this concept are lacking, and each carmaker is following its own strategy. In this article we are providing a definition for the Automotive OS concept that focuses on the targeted abstraction level of the interfaces and the functional scope of this platform. We explain how the concept evolved from current vehicle software architectures and describe its relationship to modern E/E architectures like the zonal architecture, where the decoupling of the function from the underlying hardware is a key element. As this architecture contains central high-performance ECUs as well as traditional real-time ECUs located at the vehicle zones, we present which software is best suited for which purpose. Besides, we discuss how the Automotive OS approach affects the software lifecycle of its components and the interfaces and the challenges that still lie ahead.

To improve the product characteristics of a traction machine, sensors, providing internal measurements, are an important tool during development. Sensors in the rotor of the electric traction machine, are monitoring the behavior of the traction machine during operation and can as well be used for process control while manufacturing. A major challenge is the electrical powering of the sensors on rotating parts of the machine and the transmission of the measured data, therefor methods for contactless power and data transmission are necessary. In this paper, a contactless power transmission track, supplying the rotating sensor, is investigated. The energy is transmitted orthogonally to the axis of rotation. The primary coil is located tangentially to the rotor and is fixed to the machine housing. The secondary coil is placed on the cylindrical outer side of the external rotor. That means that during rotation the coupling between the coils is partially lost. It is investigated whether such a system can transmit sufficient energy, so that the supply of a sensor is guaranteed. As an example, a temperature sensor is implemented in the rotor to monitor the temperature of the magnets. The measurement data is transmitted via Bluetooth Low Energy. The improvement in product properties that is being examined in this process will contribute to the use of TFMs in the context of e-mobility and the digitization of future vehicles.

This study deals with the development, production, and use of a cost-optimised solution for the media-tight separation of the rotor chamber from the stator chamber for use in direct-cooled electric machines. This results in a considerable cost optimisation regarding existing liner concepts. In addition, the use of a liner, manufactured in a transfer moulding process, offers advantages because the electromagnetics are not influenced, as is the case with metallic liners. The liner is manufactured with the help of a thermoset plastic in a single stage moulding process. Due to the integral design, a wide variety of functional assemblies, such as the seal, the end plates, and the sealing surfaces, are reproduced in one plastic component, which means that there are no separation points, and no finishing work is required. This increases the tightness and insulation strength and reduces the production effort. By making ideal use of features of the sheet metal package, wall thicknesses of the liner of less than 0.8 mm can be achieved through form-fit connections. Another special feature is the elimination of demoulding bevels through a patented tool concept, which enables a constant air gap. In the experimental investigations, the suitability of the moulded liner for use in an electric machine is demonstrated. This includes the required mould technology and the special features of process control when dealing with cross-linking plastics.

Passenger car drivetrain technology is transforming into electric drivetrains. Simultaneously, vehicles are transforming into highly complex overall systems with interacting subsystems. Both transformations lead to a rethinking in the organization and the way to develop. Drivetrain development must handle both transformations and design a more effectively and efficiently testing of future drivetrain for more connected vehicles. The methodology for separation into components, distributed development in departments and sub-sequent integration into the overall system is becoming more difficult. To meet all these challenges, new test bench types, an adapted testing methodology and new forms of cooperation are necessary.The article shapes the terms generic testing methodology and specific full system. It focuses on the questions of how, where and with which methods will future drive systems be integrated into the vehicle. It includes an over-view of test fields for drive system integration and an insight into the test field in the Electric Software Hub at the Mercedes-Benz AG. The methodology contains the areas of application, benchmarking, validation, energy analysis and E/E validation and software validation. Newly developed specific full system test benches for specific development contents with representative full system change the development process. These enable an early integration and reduce the development effort in the vehicle.

Due to the lower energy density of the batteries compared to conventional fuels, electric powertrains require a larger installation space in the vehicle for the same driving range requirement. Due to the limited space available in motorbikes, the overall package is a major challenge in powertrain electrification. Motorbikes are divided into different legally defined vehicle classes [1]. The respective motorbike classes have different requirements and usage criteria.In this project, the various vehicle classes are analyzed in detail as a basis for drawing up catalogs of requirements. Based on this, a powertrain architecture concept is designed for each vehicle class and the associated requirements, taking into account the installation space and usage behavior.Based on these concepts, a design for an all-electric light motorbike is presented. This is followed by a comparison with conventional light motorbikes in terms of installation space, driving range and weight, as well as the effects on driving characteristics and usage options.

In the development of future passenger cars, the statutory regulations on decarbonization of the exhaust emissions must be reconciled with customer requirements. Therefore, it is necessary to con-sider the complex interactions within powertrain systems at the earliest possible stage of development, to exploit their full potential. Thus, this paper presents a holistic methodology for optimizing the operation of all powertrain components exemplified by a hybrid powertrain. The methodology enables the full potential of all powertrain components to be exploited. For this purpose, a requirements catalog focused on the powertrain was derived using a top-down systems engineering approach. This requirements catalog is necessary for the identification of all limiting factors of the powertrain system. The development and application of the methodology and the system optimization were carried out via extensive simulation studies. Thereby, an optimal design of the hybrid powertrain was derived for a defined target application. Based on this, the system limitations were identified in Real-World Driving Scenarios, considering all relevant requirements. These limitations were significantly minimized and optimized by predictive control strategies, sophisticated hardware adaptations and innovative technologies. Finally, the scalability and transferability of this holistic approach is demonstrated by developing and optimizing a P2-Hybrid powertrain for the same requirements.

The latest legislative regulations and technology concepts for Zero-Impact Tailpipe Emissions (ZITE) aim to further significantly improve air quality. Various technologies that reduce pollutant emissions from road transport below current legal levels have been intensively investigated. To realize their full potential, a comprehensive system design is required that takes into account all boundary constraints. To this end, this paper presents two ZITE vehicle concepts, namely a small gasoline passenger car and a light commercial vehicle (LCV) with a diesel engine. A 2030 pollutant emissions regulation scenario and a ZITE compliance test matrix are considered for the conception of the vehicles. Achieving ZITE with the gasoline car requires stoichiometric operation over the entire operating range if a three-way-catalyst is used, a larger relative catalyst size compared to designs commonly used today, and an electric heater disc combined with engine power limitation or preheating with a fuel burner. Similarly, achieving ZITE with a diesel LCV requires a larger sized exhaust aftertreatment system compared to state-of-the-art twin-SCR designs. For extremely low-load scenarios, preheating by an electric heater disc or a fuel burner is required. For high-load scenarios, a limitation of the vehicle speed or an increase of the total SCR deNOx capacity is required.

This work summarizes the main outcomes of the FVV project “Water Injection in Spark-Ignition Engines II” (project nr. 1367) on the topic of innovative water injection strategies for application on a turbocharged spark-ignition engine. The focus lies on the investigations of water-in-fuel emulsions direct injection and of the applicability of water injection strategies in combination with the adoption of a synthetic renewable fuel. The study includes both experimental and numerical approaches. In particular, in the experimental campaign different fuels, water and water-in-fuel emulsions sprays are analyzed by means of optical measurements, different water injection strategies have been implemented on a single-cylinder test engine and the selected best ones were also tested in the derived 3-cylinder engine. Furthermore, detailed chemistry calculations and 3D-CFD engine simulations provided a deep understanding of the behavior of water injection and emulsions injection strategies and their effects on engine performance, efficiency and emissions.

With the current and expected CO2-emissions for passenger vehicles, a strong integration of hybridized powertrains will be necessary to reach these targets alongside other alternative propulsion systems, e.g. battery electric and fuel cell electric vehicles. The increasing diversity and complexity within a single fleet shows the challenges with current modular powertrain architectures, which are mostly derived from a manufacturing perspective and are not manufacturer independent. The answer to this problem can be observed today in different fields of application, e.g. the computer world with all its peripheral devices. The paradigm of functional design needs to be introduced in the development of the powertrain systems by utilizing object-oriented design methods. The goal of this project is to derive a modular powertrain architecture with an object-oriented layout. Dedicated use cases support the development of the interface design and the communication structure. The feasibility of this approach is shown with the simulation of driving scenarios in a virtual environment. The modularity is further demonstrated by introducing a novel object (electric heated catalyst) with the extension of the interaction between the objects and the resulting boundary conditions brought by the catalyst.

In the use of “green” hydrogen, fuel cell technology plays a key role in the realisation of carbon-free energy management and mobility. For regional involved parties such as component manufacturers, easy access to knowledge and test facilities is an important building block for market entry. Numerous regional companies can contribute their specific expertise from the traditional precision mechanics and automotive industry. These include ancillary components in the air (cathode) and hydrogen (anode) path such as the air compressor, the H2 recycling pump, the humidifier, the cooling system, the power electronics, valves and many more sensors and control devices. The periphery of the media pathways also plays an important role in terms of durability and reliability, as well as cost and weight of the overall system. Ultimately, all of this has a major impact on overall efficiency. Based on the requirements for the components “humidifier” and “circulation pump”, this paper presents the concept and design of modular test rigs for product evaluation. Furthermore, an outlook on future development and test possibilities is given.

Hydrogen has a great potential as future fuel, and it is widely discussed for appli-cation for passenger cars as well as commercial vehicles. It can be used as an en-ergy carrier to achieve local carbon dioxide neutrality. The hydrogen quality and the exact recording of the hydrogen mass flow play a significant role to ensure the required lifetime of such applications. However, during the production, transport, storage, and compression or refueling contaminants might remain (e.g. from production processes like the todays dominating steam reforming process) or introduced during the later process. They can be highly critical for the relevant functionality. Even the presence of nitrogen (e.g. from flushing processes at hydrogen filling stations) leads to a reduction in performance. Furthermore, sulfur compounds are very critical for the membrane of the cell. In principle, Raman spectroscopy could be the suitable analysis technology: It has the advantage to measure hydrogen and nitrogen. Today, however, Raman detectors for gases are laboratory setups. We have now developed a highly sensitive Raman sensor as compact measurement device for gas detection in industrial applications. It features a simple calibration process and is easy to use. A gas matrix is recognized at a glance and, depending on the area of application, in a few seconds. Even more, mass flow monitoring is possible.

Direct injection H $$_2$$ 2 engine represents a potential solution towards decarbonisation, combining high power output with efficiency. However, mixing process is worth of thorough investigation, since, even in overall lean mixtures, locally rich zones result in high heat release rates and temperatures, leading to abnormal combustion and high NOx production. Within this scope, an H $$_2$$ 2 outward-opening injector, manufactured by BorgWarner, providing mass flow rates close to 6 g/s when operating at 36 bar of injection pressure, is studied. An experimental campaign has been carried out, injecting H $$_2$$ 2 into a N $$_2$$ 2 -filled vessel, the presented results being at ambient temperature and pressures of 3, 5 and 10 bar. H $$_2$$ 2 initially enters this domain as a hollow-cone jet and its development differs for each condition. Predictive modelling of the injection event is of interest to further investigate the spray development, besides its integration within engine cylinder simulations. To this end, a validation regarding the 3D-CFD implementation of the referred injector and real test vessel in the software CONVERGE is presented, against the experimental results. This methodology includes preliminary 2D and 3D-simplified simulation cases, to initially define the numerical setup in a time effective manner. Furthermore, the accuracy of modelling the injection via 2D simulations is discussed, as well as the robustness of the applied strategy.

Current and future engine emission regulations and the imminent need to decarbonize energy systems drive the development of future engine applications, capable of running on renewable fuels with efficient combustion mechanisms. In order to accomplish an optimized performance of future engines, predictive three-dimensional CFD simulations of the phenomena inside the combustion chamber provide a powerful and efficient tool to gain detailed insight into the characteristics of spray formation, mixture and ignition/combustion processes. The presented work demonstrates the application of a developed model implemented into a commercial CFD code to model ignition and combustion for pilot ignited dual fuel engine applications. Validation with experimental data from an optically accessible test rig allows the comparison of the simulation for mixture formation, ignition and combustion behaviour at engine relevant conditions. Excellent agreement between simulation and experiment was found for the application of pilot ignition of natural gas by micro n-dodecane sprays. Furthermore, the demonstration of the simulation of pilot ignition of ammonia is presented to showcase the flexibility of the developed numerical approach wrt. Fuel types, injection and engine parameters for the application in internal combustion engines.

High-tech vehicles of the future need more and increasingly complex software. Testing these numerous software functions is always associated with high-cost factors such as time, effort and money. In order to minimize these factors, it is necessary to automate tests right at the beginning of the development process in MiL and SiL environments. Moving these tests to the cloud offers advantages in terms of scalability, flexibility and short-term availability of computing power without the need for additional hardware. In order to gain more testing experience in cloud environments and to advance the tool development towards Linux, a prototype for scalable cloud testing was created. It utilizes a Kubernetes cluster, which manages multiple pods with suitable software tools for test planning, test execution and report handling. The integration of this prototype into a cloud infrastructure offers various new opportunities, but also reveals critical obstacles, like security aspects and the need for well-functioning backup strategies. In addition to the presentation of the prototype itself, different aspects are discussed: how fully automated software testing can be realized in the cloud, how the necessary resources are handled and if software testing in the cloud can reduce time and costs.

The software industry has shown that DevOps approaches offer many advantages: faster value chain, shorter time-to-market, and fast and frequent updates. The current vehicle architecture is powertrain-centric, and the software is distributed via bus systems. With digitization, a redesign is taking place. The vehicle is becoming an intelligent and digital ecosystem – “a smartphone on wheels!” But unlike a smartphone, a vehicle is a safety-critical environment. Therefore, a robust validation, verification, and optimization process is required. The automotive industry has a very well-established development process. This change makes the new architecture software-oriented, with a central vehicle operating system and a hierarchical structure of ECUs. And with that, the DevOps approach is gaining dominance. The key is to integrate the DevOps process with the V-model for the validation and verification of software. Both approaches will work together to ensure speed, a faster value chain, and risk mitigation on critical aspects such as safety, durability, etc. Continuous release and deployment of software functions require intensive functional testing of the software, as well as cybersecurity testing. Our vision allows executing and reporting tests automatically while adding test intelligence and adaptive tests that reduce testing effort and increase the robustness of results.

Driven by progressive networking in the automotive industry, such as cloud connectivity, interaction between microcontroller- and microprocessor-based systems, or automated driving, vehicle system software is spreading continuously into new areas that were previously outside the automotive domain. Conversely, vehicle data is also becoming increasingly interesting for operators of non-automotive systems. Hence, the integration of these systems is also accompanied by an adaptation of existing software architectures and their already established standards and technologies. AUTOSAR as a major standard in the automotive domain has proven over the past 20 years that complex software systems can be developed at the same time in a cost-effective manner by applying the technical framework to day-to-day business. This pool of experience clears the way for mastering the more complex software infrastructures of the future.Bosch, as a founding partner of AUTOSAR, contributes to the standard particularly by long time experience in software and tool development as well as profound system integration know-how. We are convinced that the AUTOSAR standard enables a variety of collaboration models with vehicle manufacturers and other suppliers. Bosch proves this claim by having successfully brought many high-volume AUTOSAR-based products to the streets.This paper illustrates on the example Basic Software (BSW) how a support of a variety of vehicle platforms from various manufacturers can be managed. The individual needs regarding the integration of AUTOSAR functionality create new challenges which are handled by innovation in SW-development and collaboration. Particularly a high degree of modularity in SW-architecture and tool-landscape enables modern SW solutions and efficient project execution.

Software-based functionalities will become increasingly important in the vehicle of the future and will also have a decisive influence on buyer behavior. The vehicle is evolving into an integral part of the digital life of customers – with corresponding requirements for usability, the reloading of apps and the temporary activation and deactivation of functionalities such as driver assistance functions. Technically and organizationally, this increase in the importance of software in the vehicle represents both a challenge and an opportunity. On the software and E/E side, architectures must be carefully selected and implemented. Virtualization and containerization become standard techniques to ensure maximum encapsulation, independence and security. From an organizational point of view, software development must be accelerated and become more agile – DevOps will become an integral part of automotive development and will help to improve the development speed and quality of the software. In this paper the authors will provide an overview of how FEV.io assesses the challenges of the Software Defined Vehicle and which possible solutions FEV.io has identified in order to solve the technical and organizational challenges successfully.

In urban environments, vehicles share the road space with other road user types, like vulnerable road users (VRU), i.e., pedestrians and bicyclists. Nowadays, preventing accidents with VRUs requires inferring a variety of information about a VRU from the perspective of the vehicle. This prevention is challenging for at least two reasons: First, pedestrians have higher degrees of freedom of movement and can spontaneously alter their movement dynamics compared to vehicles. Second, in the urban environment, “non-line-of-sight” (NLOS) situations are common. In NLOS situations VRUs are not within the field of view of the driver and car-based sensor systems. Consequently, the VRU may not be identified in time, thus leading to a collision.The avoidability of collisions between VRUs and vehicles in urban NLOS scenarios highly depends on the behavior of both the VRU and the vehicles, respectively. Thus, as part of the research project KoSi (funded by the BMDV), we integrate human behavior models in the 3D simulation environment $${\text {Tronis}}^\circledR $$ Tronis ® . Considering individual human behaviors in this virtual prototyping and validation environment allows to asses the performance of collision avoidance systems more realistically in contrast to generalized human behavior models. The significance of considering different human behaviors is highlighted by results of simulations for the Euro NCAP NLOS scenario with different behavior models for the driver and a pedestrian, respectively.

In today’s vehicle development, software is developed and should be tested independent from vehicle and even before a real prototype or hardware components are available. The various digital hard- and software components are developed and integrated as X-Domain software-in-the-loop systems. The full virtualization of vehicles saves enormous resources, but also raises one essential question: How can we evaluate the quality and suitability of the virtual environment without real vehicle reference data for comparison? New approaches are needed for assessing the credibility of virtual systems according to the prevailing boundary conditions and included components. Knowledge about a model’s credibility level enables simulation-based decisions from virtual calibration, design decisions up to virtualized releases. It also forms the communication basis for collaboration across organizational boundaries. Across multiple Bosch domains, we develop and apply processes, methods and tools to achieve credibility of simulation models by generalized steps including verification, validation and uncertainty quantification of X-Domain simulation environments. In this paper we will present our approach at Bosch Engineering, how future collaboration in the development of X-domain features can look like by showing a simulation environment for Advanced Driver Assistance System including virtualized radar software, electronic stability control and electronic power steering system.

The trend towards e-mobility means that at least one inverter is part of the drive system in every vehicle. Software is a crucial component for the function of the inverter in vehicles and significantly determines the vehicle behavior. To shorten development times, an efficient software release process is essential. Since in-vehicle tests are very time-consuming and cost-intensive as well as poorly reproducible, a large part of the tests is already performed on an inverter test system where the characteristics of the electric motor are emulated. Due to limited test capacities, there is a need to distribute tests worldwide and to perform some of them unmanned. Inverter test systems offer good conditions for worldwide testing, since the characteristics of the electric motor can be mapped in software and parameters and thus distributed as data around the world. In order to implement safe unmanned operation, door monitoring, additional smoke and temperature sensors, and a thermal imaging camera were added to the test benches. These components were incorporated into the test stand automation and security system. With this setup, a 30 % increase in available test capacity is planned.

Testing is the most important activity in quality assurance for software. However, years of experience in assessing test processes in the automotive industry have shown that it seems to be very hard to establish test processes that are both effective and conforming to standards like Automotive SPICE (ASPICE) on a sufficient process capability level. Proper training for test personnel like test managers and testers is needed for all decisions on the test process. They need to be trained on ASPICE requirements to understand the fundamental framework of the automotive test process. They also need to be trained on testing terms, test process steps and test methods to be able to understand both the terms used in ASPICE and to decide upon how to implement ASPICE in their development and testing teams. Lastly, they also need experience and training on the job to plan, supervise and perform their daily testing tasks. We propose to use specific modules from the ISTQB® Certified Tester Scheme to qualify test managers and testers to come up with proper test processes up to capability level 3 (CL3). Additionally, we propose a sustainable approach for continuous stabilization and improvement of these test processes to permanently keep CL3 in the face of change.

The complexity of vehicle E/E-architectures grows with increasing vehicle functions and driver assistance systems. I. e., environment recognition systems rely on lidar, radar, and camera sensors, which each are subject to multiple complex failure modes. Faults within a component may propagate into further systems, due to functions. On top, the number of system variants, both in soft- and hardware, increases. Subsequently, challenges arise for the development of complete and accurate diagnostic concepts starting with the identification of faults and their effect on a system as a whole (FMEA scope).This paper presents a methodology to automate the Failure Modes and Effects Analysis process using a graph representation of a mechatronic system. The representation, a causal-structural dependency graph, is automatically generated by exploiting existing standardized data sources (such as SysML and ODX) and its analysis is capable to identify potential failure modes and their associated effects. The graph model allows for an efficient analysis of complex vehicle systems, and provides a clear and intuitive representation of the system’s structure and behavior.The proposed method is validated using a case study of an environment-recognition system. Results demonstrate its effectiveness in identifying potential failure modes and their effects. It has the potential to significantly reduce time and effort required for FMEA, and improve accuracy and completeness of a diagnostic concept.

Although a promising solution for zero emission long haul transport, a fuel cell system poses a significant challenge when it comes to the thermal management of the system and its integration into a vehicle. This paper discusses the challenges of fuel cell cooling, including low coolant temperature, high losses and large radiators, as well as the challenges of battery thermal management. These difficulties are illustrated using the example of the SeLv project, whose aim is to develop and integrate a fuel cell powertrain for retrofitting of conventional 40t heavy-duty diesel trucks. Firstly, an oversized system and the resulting problems of integrating the components into the vehicle are discussed. To address these challenges, a 1D full vehicle model is developed in Amesim. This simulation model includes the longitudinal dynamics of the vehicle and the characteristics of the powertrain components that define the thermal management requirements. A real, measured driving cycle is used as input data. The radiators and the ambient air flow are modelled in detail, taking into account both the air flow due to vehicle speed and the forced air flow due to the fans. Two different packaging concepts, with the FC cooling system located either behind the cab or in the engine compartment, are evaluated for suitability using the simulation model developed. Furthermore, an attempt is made to identify an optimal thermal system topology through the use of simulation.

The courier express parcel service industry (CEP industry) has experienced significant changes in recent years due to increasing parcel volume. Similar to the parcel volume, the number of vehicles is growing. Therefore, the fleets of CEP service providers are particularly in the focus of the public and should contribute to the reduction of emissions. Moreover, there is an increasing interest in regulating the use of internal combustion engine vehicles by imposing stricter exhaust emission standards and transit restrictions in metropolitan areas. Nevertheless, the electrification progress in the CEP industry is slow because of the low electric range, the limited vehicle availability and high acquisition costs. An opportunity to increase the electric range is the optimization of the thermal management strategy by predictive data of the future driving task. This paper investigates the CEP usage behavior with a focus on thermal management and identifies exploitable potentials of predictive strategies. For this purpose, the metropolitan CEP usage behavior is discussed and the influence on the thermal management system is investigated. The evaluation shows that thermal management energy consumption accounts for a significant share of the total consumption, up to 50% at an ambient temperature of 0 °C. Predictive thermal management strategies are evaluated by a potential analysis for their practicability in battery electric CEP vehicles. The results show that predictive battery conditioning for maximum regenerative braking and predictive thermal energy storage have high potential for increasing electric range and thermal comfort in battery electric CEP vehicles.

Electromobility is on a growth path in Europe. This is supported by the European Commission’s “green deal” and the funding projects it contains. However, it is not enough to promote battery-electric vehicles only politically. It is also necessary to increase customer acceptance of this technology. In extreme weather conditions air conditioning can have an unfavorable impact on the driving range. An intelligent thermal strategy can help to reduce energy consumption and maintain comfort in the cabin.With this in mind, this paper presents a predictive control strategy for air conditioning of battery electric vehicles that optimizes the use of the energy sources available in the vehicle. For this purpose, maximum utilization of the air recirculation rate is desirable. In this context, however, it must be prevented that the air quality suffers from an excessive increase of the CO2 concentration in the cabin. This criterion is also taken into account by the control algorithm. Another feature of the developed approach is the possible use of heating radiating surfaces to increase comfort and reduce energy consumption. The functionalities described were implemented in a Model Predictive Control (MPC) approach and tested in simulation.The modeling and the functional architecture of the MPC cabin air conditioning system will be explained in this paper. Using selected scenarios, it will be shown that the novel strategy can significantly save energy while ensuring the occupant comfort.

Currently the development of suspension layouts in cars relies heavily on multibody simulation models. Those simulations test the suspension during maneuvers and can last from minutes to hours. Optimization algorithms need thousands of simulations, this combination makes that approach extremely computational expensive. This publication describes a proposed workflow, by using a high-fidelity multibody simulation model as basis, the output of which is used for training a neural network. An ISO maneuver is programmed, and the roll angle of the vehicle is chosen to be the main output. The large number of input parameters leads to an extra sensitivity analysis step. The following design of experiments produces the training data for a neural network. To select the hyperparameters, an automated machine learning technique is employed. A particle swarm optimizer is used in the end to find an optimum design with respect to the L2-norm of the roll angle.

The automotive industry has started using Artificial Intelligence (AI) for autonomous vehicles, innovative user interfaces and predictive maintenance. AI can optimize huge numbers of parameters based on training data that would not be feasible without AI. Furthermore, there is and will in future be even more innovation in AI. For automotive SW development that means significant transformation effort to keep up. There are three key elements: 1.) Training: The performance of AI-based system depends heavily on training data. There are various sources of uncertainty that have a root cause in missing or unbalanced evidence of uncertain situations in the training data. But AI has advanced and there are solutions for this that must be adapted to automotive. For example, in natural language processing systems (e.g. ChatGPT), similar gaps in the training data are overcome by using task-agnostic unsupervised training on very huge data sets. 2.) Testing: With AI-based systems, there is a need to test with test data that is independent of the training data. Still the challenge of incomplete evidence due to missing data exists. 3.) AI Diligence: It is good practice to assess the development capability of automotive projects to ensure delivery in time, quality and budget. With AI, assessment models need to be adapted, focusing on the capability to apply new AI methods. In this paper we will explain key methods for AI training, testing and diligence and their practical application.