21. Internationales Stuttgarter Symposium

Table of Contents

1. Frontmatter

2. E/E-Architecture

   1. Frontmatter

   2. Mercedes “S-Class” Powernet Architecture

      Michel Weber, Thomas Mundinger, Ferdinand von Kageneck, Marius-Florin Buciuman, Fridolin Häuser

      Abstract

      The brand-new S-Class is the beacon of automotive luxury, which addresses evolving customer expectations and technical opportunities. We enter into a new era in the automotive Powernet domain. Optimization in both power availability and drive hybridization, as well as new features such as partial networking characterize the highly integrated state-of-the-art Mercedes powernet. The new S-Class offers heightened energy efficiency and increased reliability for further automation of driving and vehicle features. The systematically optimized E/E network architecture for the 2020 S-Class maximizes the availability of automotive electronics innovations. Mercedes-Benz further enhances the energy-efficient and cost-effective power supply with the improved 48V system. It prepares for the latest driver assistance and automation systems with a fail-safe 12V power supply. Furthermore, a new vehicle feature experience is defined before and after driving with a “Living” powernet. Since the initial launch in the 222 predecessor, the fully integrated 12V and 48V power network system increases the energy availability for additional comfort and chassis innovations with consumption-reducing EQ hybrid features culminating in the realization of the 223 model.

   3. A Cross-domain System Architecture Model of Dynamically Configurable Autonomous Vehicles

      Tarık Şahin, Christian Raulf, Volkan Kızgın, Tobias Huth, Thomas Vietor

      Abstract

      The development of a dynamically configurable autonomous vehicle is subject to a high degree of complexity. This complexity is further intensified by usually domain-specific thinking and document-based development, leading to difficulties in managing the development processes. Therefore, there is a need for manageable and cross-domain approaches in the development of vehicle systems. For this purpose, Model-based Systems Engineering (MBSE) proposes an approach for modeling systems architectures with the necessary views for the development of vehicles. This contribution presents accordingly a cross-domain system architecture model in the sense of MBSE using the example of a dynamically configurable autonomous vehicle (DCAV) and highlights the resulting advantages for the development process. A DCAV includes an electrically and autonomously driven platform and exchangeable add-on capsules for different use cases. The system architecture model provides here a development environment where requirements on the DCAV, its behavior, and structure as well as their interrelations are described, structured, and unified at several levels for different use cases (e.g. passenger transport). In this way, a comprehensive basis for various development activities (e.g. function-oriented modularisation) is established, which at the same time indicates the great potential of system architecture models for the development of future vehicles.

   4. Analysis and Modeling of Future Electric/Electronic Architectures for Modular Vehicles Concepts

      Marc Schindewolf, Houssem Guissouma, Eric Sax

      Zusammenfassung

      In addition to the megatrends electrification, automation and connectivity, the whole mobility business model is experiencing substantial transformation through increasing car sharing services, less individual traffic and introducing new environmental protection measures. This leads to new modular vehicle concepts. These new modular and reconfigurable vehicle concepts should also consider the new trends such as automated/autonomous driving, connected vehicles and OTA updates. In addition, high security and safety requirements must be fulfilled. All this leads to an increasing complexity of the Electric/Electronic architecture (E/E-A) for modular vehicles. The adaptation of the existing approaches in the E/E-A design to those becomes challenging especially regarding the aspect of distributed and integrated E/E modules in different vehicle parts. We analyzed existing concepts for E/E-A design targeting the mentioned new trends and showed their limits for application in modular vehicle concepts. Based on that, we conducted a gap analysis to cover the needs for the considered aspects and integrated the results in a generic E/E-A model consisting of drive module, additional vehicle parts and cloud/infrastructure module. The resulting architecture is based on modular distributed services leading to a seamless service-oriented architecture which is able to handle the new challenges.

3. Hydrogene + Methane

   1. Frontmatter

   2. Redefining the Requirements for Hardware Development and Simulation for DI-H2 Combustion Engines

      Thomas Ebert, Gidion Maniezki, Roberto-Fabio Nobile

      Abstract

      Climate change is a major challenge not only to Europe but the entire world. To cope with this threat, the European as well as other EU member countries – i.e., Germany – introduced substantial environmental protection regulations. On the EU level, this is called the “Green Deal”, providing an action plan to accelerate the use of renewable resources and hence, “moving to a clean, circular economy, restoring biodiversity and cut pollution”, ultimately reducing net emission to 0 by 2050 [27, 28].

   3. Review of State of the Art and Future Options of Hydrogen Storage Systems for Internal Combustion Engines with Direct Fuel Injection for Use in Heavy Duty Vehicles

      Richard Trott, Ingo Friedrich

      Abstract

      Currently there is an intensive discussion about the use of hydrogen for mobile applications in particular for heavy-duty vehicles. Here, the focus is also on the integration of internal combustion engines into road vehicles and construction machinery. For maximizing engine efficiency and power density direct injection is generally speaking the favorable option for hydrogen combustion engines, although direct hydrogen injection is in a relatively early development stage and it imposes the demand of high supply pressure on the supply system.

      This paper focusses on possible supply system solutions that are suitable for supplying an ICE (internal combustion engine) with high gas pressures suitable for DI (direct injection). Gaseous and liquid hydrogen storage options that are relatively mature today as well as possible future innovative approaches are reviewed and necessary changes for supply of high pressure in all operational scenarios are presented. The additional efforts are evaluated and quantified in terms of package volume, weight, cost and impact of overall drivetrain efficiency.

      The components used in each technical solution will be described regarding their functionality; the options of pressurization techniques mentioned above will be explained and finally an outlook on potentially beneficial combinations of hydrogen storage system for supply of high pressure and highly efficient hydrogen DI ICE is presented.

   4. Significance of Synthetic Methane for Energy Storage and CO2 Reduction in the Mobility SectorDimopoulos

      Florian Kiefer, Karin Schröter, Panayotis Dimopoulos Eggenschwiler, Christian Bach

      Abstract

      The introduction of synthetic fuels is one approach to reducing CO₂ emissions in the transport sector. In this context, synthetic methane is promising due to the high degree of development of the technology and easy substitution in the vehicle fleet. In particular, the existing infrastructure including gas grid, gas storage, and filling stations as well as existing trade mechanisms allow a comparatively fast substitution of fossil natural gas by synthetic methane for light and heavy duty vehicles. This study discusses the direct potential for substitution of parts of the newly registered vehicle fleet with gas vehicles, fueled with synthetic methane, and compares it to the potential of using fuel cell electric vehicles relying on hydrogen. The production path of hydrogen and synthetic methane is analyzed with respect to electricity demand and overall associated CO₂ emissions. The result is an estimate of the well-to-wheel CO₂ emissions of vehicles fueled with hydrogen or synthetic methane.

4. Test II

   1. Frontmatter

   2. Concept for the Automatic Generation of Individual Test Sequences Verified by Artificial Intelligence Algorithms.

      Ralf Lutchen, Andreas Krätschmer, Hans Christian Reuss

      Abstract

      In vehicle development, more and more test sequences (diagnostic scripts) are established for function testing of individual components, systems and cross-functional methods. Due to decentralization and the modular approach, modern development vehicles consist of different numbers of electronic control units (ECU). The high number of ECUs in purpose and number pose a challenge for test creation and updating.

      The ECU software is also developed in cycles within the vehicle cycle. This also results in a very high software variance. This variance leads to the fact that in the vehicle development with global test conditions only one works. The vehicle structure (ECU and their software status) is uncertain, so errors and a longer script runtime must be expected during test execution.

      Due to this initial situation a concept was developed, which excludes the individual vehicle structure (global pattern) and verifies and stores this supported by an Artificial Intelligence (AI) database. This ensures traceability of the vehicle body at all times. In addition, it is possible to create individualized test sequences for each vehicle and to keep them up to date. Furthermore, the AI is able to identify the user and to generate person-specific test sequences. Finally, the AI evaluates the quality of the measured values in order to provide the ECU developer with a tool to detect discrepancies.

   3. Acceleration of ECU-Development by Using Connected Mixed Reality Environments

      Franz Dengler, Bruno Eichler, Abduelkerim Dagli

      Abstract

      The automotive industry is facing a profound transformation: New functions such as autonomous driving lead to a continuous increase in the complexity of vehicles and the dynamics of development.

      One solution to face the according challenges for automotive testing is the use of Connected Mixed Reality (CMR). This involves test environments consisting of real and simulated components. The CMR approach combines the strengths of classic HiL systems with the advantages of virtualization solutions.

      Modern CMR environments are characterized by the following features:

      • Modularization and standardization of all test components (models, ECU setups, environmental simulations)
      • Dynamic configuration of test setups consisting of real ECUs and virtual components
      • Real-time operation from the cloud with real ECUs
      • Common integrated operation of best-in-class solutions
      • Support of interface standards
      • Middleware for coupling best-in-class components

      The combination of CMR environments with Continuous Integration Systems will allow test cycles to be shortened to an unprecedented extent. An automated triggered test during the check-in of a component will be possible. This contribution presents the current status of the CMR approach in MicroNova’s NovaCarts platform. The focus will be on experiences with the introduction of real-time operation in mixed cloud environments.

   4. Automized Testing - Support of the Testcase Generation & Assessment Using Systems Engineering

      Peter Ebner, Michael Maletz Schneider, Richard Schneider, Martin Ringdorfer, Gerald Teuschl

      Abstract

      Within powertrain system development, testing has a major impact on development duration and cost. The introduction of new technologies, strongly driven by electrification, customization and connectivity, leads to increased testing effort.

      The paper will present a method based on systems engineering (introducing a systematic description of the powertrain using SysML and a systematic collection and management of the requirements).

      This enables to introduce automation for testcase generation as well as test automation and the judgement of test results. The whole process of “testing” could be finally automized.

5. Vehicle Attributes II

   1. Frontmatter

   2. A Hybrid Approach using an Adaptive Waypoint Generator for Lane-changing Maneuver on Curved Roads

      Qianwei Yang, Qihang Shi, Mustafa Saraoğlu, Klaus Janschek

      Zusammenfassung

      Unsuitable lane-change maneuvers are one of the most common potential safety risks in traffic. Nevertheless, it is a maneuver that must be executed carefully by both human drivers and self-driving cars. Developing a suitable automated driving algorithm for self-driving cars to address the lane changing problem is not straightforward because the problem can only be stated as a high dimension problem with many variables and parameters. Therefore, safe driving needs to be assured by optimal trajectory generating algorithms as well as high-level behavioral planners, which assess the safety of the intended behavior and discard the infeasible trajectory candidates. In this paper, a hybrid approach to a behavioral planner algorithm with lane changing behavior using the Frenet coordinate system was developed to solve the lane changing maneuver problem on roads that consist of road segments with different curvature values. The controllers that need to generate the actuator commands according to the reference trajectory cannot always precisely follow the trajectories. Hence, the waypoint generation algorithm has to adapt to the controller and vehicle dynamics. The road structures for the driving scenarios were modeled according to the OpenDRIVE format and were implemented in a model-based traffic simulation environment MOBATSim. The proposed approach is evaluated and demonstrated by the simulating driving scenarios in the same environment.

   3. New Approach to Friction Estimation with 4WD Vehicle

      Smiljana Todorovic, Sven Müller, Jochen Kiebler, Jens Neubeck, Andreas Wagner

      Abstract

      This research is a part of publicly funded project – FlexCar, which aims to build an autonomous vehicle. The vehicle offers open source software and construction models and should serve as a platform for rapid development and testing of new technologies. The project strives to bring new solutions for future mobility and overcomes some of existing limitations. The FlexCar platform has symmetrical design - it consists of two drive modules and one energy module between them. Both axles are steered, which allows a small turning radius. Furthermore, each wheel is equipped with one electromotor and can be accelerated separately. This can be used as an advantage for slip based friction estimation. Currently, ADAS functions have restrictions due to bad weather or road condition. With a continuous and driver-independent friction information, it would be possible to improve these functions and make a step towards autonomous driving. This paper shows first results from measurements done on the Handling Roadway test rig. Both, longitudinal and lateral slip are observed during accelerating/braking and steering.

   4. How to Upgrade Vehicles? Release Planning in the Automotive Industry

      Tarık Şahin, Luca Köster, Tobias Huth, Thomas Vietor

      Abstract

      Automotive manufacturers are facing highly dynamic customer demands and shorter life cycles forcing them to continuously upgrade their vehicles by releasing new versions with innovative features. Accordingly, manufacturers have to determine well-conceived release-strategies in order to upgrade existing vehicle models in their portfolio. The influence of accelerated technological progress and the digital transformation of today’s vehicles require novel release strategies in development and use stage of the vehicles. Here, traditional release-strategies of the automotive industry, for instance, by introducing facelifts or special editions, are becoming less effective and very limited compared to other branches such as the software industry. Therefore, this contribution aims to present the current practice of release planning in the automotive industry and the resulting recommendations. For this purpose, a comprehensive study was conducted, analyzing six vehicles from different brands of the upper-range segment in the German automotive industry between the years of 2009–2019 regarding their introduced releases and features as well as their impact on market success. Moreover, interviews were conducted in the automotive industry to gain an overview of the understanding, challenges, needs, and current processes of release planning in practice. Additionally, release strategies and principles from different branches (e.g. smartphone industry) were analyzed and compared. As a result, recommendations for appropriate release planning and strategies to upgrade vehicles were defined for the automotive industry.

6. E-Powertrain

   1. Frontmatter

   2. Data-Enhanced Battery Simulator for Testing Electric Powertrains

      Philipp Gesner, Richard Jakobi, Philipp Klein, Ivo Horstkötter, Bernard Bäker

      Zusammenfassung

      Battery simulations are an essential tool for the efficient development of electric powertrains, which require accurate models and reliable hardware. Surprisingly, today’s massively collected measurements are not yet used for realistic and virtual development environments. Among other reasons, handling the large and heterogeneous datasets of automotive batteries still prevents a consequent application. Hence, a data-enhanced electric model of the battery is presented, which relies on a recurrent neural network to compensate the error of a physically-motivated model. Such a hybrid model introduces the high accuracy of machine learning to simulations. Ultimately, it allows a replacement of real batteries with model-based simulators at test benches. The approach is validated based on a comparison of a real battery with a simulator and its different model variants. It is shown, that the data-driven enhancement of existing simulations increases the accuracy while maintaining the robustness of the original model.

   3. The FKFS High-Performance Electric Powertrain Test Bench

      Alfons Wagner, Andreas Krätschmer, Hans Christian Reuss

      Abstract

      The Research Institute of Automotive Engineering and Vehicle Engines (FKFS) already operates a range of state-of-the-art specialist test benches for engine and powertrain applications. Its portfolio covers both conventional drives as well as hybrid and battery electric vehicles. To meet demands for more testing capacity with test bench runs for electrified vehicle powertrains – and to comply with the significantly increased requirements for power, torque and especially dynamics – FKFS has planned, built and started operating a new high-performance electric powertrain test bench (HEP). The HEP is a single-axis test bench, characterized by a variable machine layout enabling setup of different drive and powertrain configurations. For example, it is possible to run test specimens consisting of a vehicle’s electric machine, gearbox and driveshafts, with a power of up to 1160 kW. A high-performance battery simulator provides up to 1600 A, with a voltage range from 0 to 1000 V. The portfolio includes back-to-back setups as well as testing of purely mechanical axles for electric vehicles. A highly dynamic drive machine permits speeds of up to 20,000 rpm, with a maximum power of up to 700 kW. This makes it possible to comply with new requirements coming from politics and automotive development, so we can continue to provide reliably tested drives in the future too.

   4. AI-Based Diagnostic Tool for Offline Evaluation of Measurement Data on Test Benches

      Andreas Krätschmer, Ralf Lutchen, Hans Christian Reuss

      Abstract

      Test benches are becoming increasingly important in the development of modern vehicles. It does not matter whether the vehicle has a conventional, hybridized or fully electric drive. This trend is further strengthened by shorter development times, cost effectiveness and measures such as Road-to-Rig. In order to generate long running times and thus operate the test bench as effectively as possible, downtimes must be reduced to a minimum. In addition to the interruptions for setup and commissioning work, the downtimes primarily include the time for measuring data analysis in the event of an error. The procedure in the event of an error related shutdown is first of all to isolate the affected components and convert the required measurement data. These are then manually evaluated, categorized and logged by the test bench operator. The approach of the diagnostic tool developed here is the automated pre-evaluation of measurement data in the event of an error, before the test bench operator arrives at the testbench. This offers the possibility of efficient error analysis and support for the test bench operator. Thanks to the AI-based approach, the diagnostic tool learns independently and without intervention from the test bench operator, possible wear-related changes to the components over the course of time.