ELIV 2023

doi:10.51202/9783181024232

ELIV 2023

Electric / Electronics for Commercial Vehicles 2023

Reihe: VDI-Berichte

Band 2423 Erschienen 2023

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doi.org/10.51202/9783181024232
ISBN print: 978-3-18-092423-6
ISBN online: 978-3-18-102423-2
VDI Verlag, Düsseldorf VDI Verlag, Düsseldorf

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Zusammenfassung

Content Automated Driving – Systems Criticality driven data acquisition in autonomous driving – A basis for completeness and safety argumentation 1 Vehicle-to-vehicle (V2V) communication as enabler for improved automated driving functions 17 Electronics Technology Estimation of Gender and Age of Vehicle Occupants Using Deep Learning 27 QuietComfort Road Noise Control – Helping Carmakers Design Better Cars 39 New Opportunities with Software Defined Lighting – Appearance drives Emotionalization 61 E Vehicle Mobility – System A Holistic Approach for Designing a Battery Electric Vehicle Thermal Management System 77 Safe and efficient regenerative braking strategies for BEV heavy vehicle combinations 91 A Cloud-based Self-Learning Digital Twin Solution for Increasingly Accurate Range Prediction in Battery Electric Vehicles 103 Automated Driving – Sensors Using Radar and Vision Fusion for Improved Low-light Pedestrian Detection 113 Automotive Radar Technology Innovations power next-gen ADAS and Autonomous Driving 133 Combining ADAS and SD Maps for Augmented Reality Guidance 135 Dev...

Schlagworte

Autonomes Fahren Straßenlärmkontrolle effizientes regeneratives Bremsen Sicherheits Optimierung Kommunikations Schnittstelle DNN-basierte Objekt Erkennung künstliche Intellingenz KI hybrides Fahrzeug autonomous driving road noise control efficient regenerative breaking safety improvement communication interface DNN-based object detection artificial intellingence AI hybrid vehicle

Kapitel Ausklappen | EinklappenAutorenSeiten
I–XVI Titelei/Inhaltsverzeichnis I–XVI
1–26 Automated Driving – Systems 1–26
- 1–16 Criticality driven data acquisition in autonomous driving – A basis for completeness and safety argumentation M. Nestoriuc, H. Walia M. Nestoriuc, H. Walia 1–16
- 17–26 Vehicle-to-vehicle (V2V) communication as enabler for improved automated driving functions M. Kremer M. Kremer 17–26
27–76 Electronics Technology 27–76
- 27–38 Estimation of Gender and Age of Vehicle Occupants Using Deep Learning P. Laufer P. Laufer 27–38
- 39–60 QuietComfort Road Noise Control – Helping Carmakers Design Better Cars A. Beyfuß, M. Wirtz, T. Hein, J. Feng, P. Crowther, O. Forrest A. Beyfuß, M. Wirtz, T. Hein, J. Feng, P. Crowther, O. Forrest 39–60
- 61–76 New Opportunities with Software Defined Lighting – Appearance drives Emotionalization C. Wilks, J. Roslak C. Wilks, J. Roslak 61–76
77–112 E Vehicle Mobility – System 77–112
- 77–90 A Holistic Approach for Designing a Battery Electric Vehicle Thermal Management System S. Miller, L. Nicoletti S. Miller, L. Nicoletti 77–90
- 91–102 Safe and efficient regenerative braking strategies for BEV heavy vehicle combinations J. Hansson, L. Henderson, M. Sadeghi Kati, D. Möller, S. Ray, S. Schoutissen J. Hansson, L. Henderson, M. Sadeghi Kati, D. Möller, S. Ray, S. Schoutissen 91–102
- 103–112 A Cloud-based Self-Learning Digital Twin Solution for Increasingly Accurate Range Prediction in Battery Electric Vehicles M. Wegener, R. Savelsberg, A. Alberti, G. Cechini, L. Schäfers, K. Badalian, S. Pischinger M. Wegener, R. Savelsberg, A. Alberti, G. Cechini, L. Schäfers, K. Badalian, S. Pischinger 103–112
113–158 Automated Driving – Sensors 113–158
- 113–132 Using Radar and Vision Fusion for Improved Low-light Pedestrian Detection Z. Bassi, P. Gulden Z. Bassi, P. Gulden 113–132
- 133–134 Automotive Radar Technology Innovations power next-gen ADAS and Autonomous Driving M. Feulner M. Feulner 133–134
- 135–148 Combining ADAS and SD Maps for Augmented Reality Guidance M. Pfeifle, N. Zeller, A. vom Felde M. Pfeifle, N. Zeller, A. vom Felde 135–148
- 149–158 Development and Testing Autonomous Vehicles (AV) at Scale F. Kraemer F. Kraemer 149–158
159–210 Vehicle Architecture – Strategy 159–210
- 159–168 Plug & Play High-Performance Computer (HPC) and Fluid Cooling Solution A. Heise A. Heise 159–168
- 169–184 Strategically Migrating, Mapping and Scaling Software to new SoC, domain and zone architectures and HPC O. Schmidt, K. Albers, P. Rehkop, R. Münzenberger O. Schmidt, K. Albers, P. Rehkop, R. Münzenberger 169–184
- 185–198 Towards the next step in vehicle E/E architectures T. Huck, A. Achtzehn T. Huck, A. Achtzehn 185–198
- 199–210 Mastering the software update complexity of modern vehicles O. Meyer, B. Böhlen O. Meyer, B. Böhlen 199–210
211–252 E Vehicle Mobility – Components 211–252
- 211–222 How to Improve EV Battery Cell Quality – Making Test a Competitive Advantage D. Cotterle, M. Hofmann D. Cotterle, M. Hofmann 211–222
- 223–234 Analysis of WBG based hybrid semiconductors approach for bidirectional PFC in On-board charger applications D. Nardo, G. Aiello, F. Gennaro D. Nardo, G. Aiello, F. Gennaro 223–234
- 235–246 Power electronic system technology for future high-power charging systems on highways or large inner-city electric charging stations with several MVA system size A. Hensel, D. Derix, J. Bornwasser A. Hensel, D. Derix, J. Bornwasser 235–246
- 247–252 Multi-level GaN inverter for highest HV EV performance and efficiency – comparison of 2-level and 3-level inverter topology T. Hackl, L. Roslaniec T. Hackl, L. Roslaniec 247–252
253–280 Software 253–280
- 253–266 Snapdragon Ride Flex SoC: The central compute solution that’s bringing the SDV vision to reality G. Shirasat, T. Dannemann G. Shirasat, T. Dannemann 253–266
- 267–280 Maintaining Open-Source based Software J. Schlosser, J. Petersohn J. Schlosser, J. Petersohn 267–280
281–306 Automotive AI – Innovations 281–306
- 281–292 How to Become a Leader by Development of AI – ChatGPT Research Papers Analysed U. Bodenhausen U. Bodenhausen 281–292
- 293–306 Seeing with Sound: AI-Based Detection of Participants in Automotive Environment from Passive Audio J. Sieracki, R. Yang, A. Vamos, M. Caggiano J. Sieracki, R. Yang, A. Vamos, M. Caggiano 293–306
307–330 Vehicle Architecture – Aspects 307–330
- 307–320 Continuous System Architecture Development for Automated Driving Features A. Malvankar, S. Riediger, V. Kumar Konenki, F. Probst, M. Marx, A. Jasoliya, J. Philipp Hake A. Malvankar, S. Riediger, V. Kumar Konenki, F. Probst, M. Marx, A. Jasoliya, J. Philipp Hake 307–320
- 321–330 New EE Architecture – MB.OS 1.0, the digitalization of the E/E architecture of Mercedes-Benz Y. Duhr Y. Duhr 321–330
331–378 Connectivity 331–378
- 331–346 Achieving Ubiquitous Connectivity for Future Vehicles T. Hinzmann T. Hinzmann 331–346
- 347–364 Cooperative Perception Services to Improve the Safety of Road Users K. Eliasch, Dr. P. Friedel, D. Li, D. Shan K. Eliasch, Dr. P. Friedel, D. Li, D. Shan 347–364
- 365–378 A Holistic Approach for a Universal Vehicle-to-Robot (V2R) Communication Interface L. Heinrich, M. Springer, D. Schütz, J. Pannek L. Heinrich, M. Springer, D. Schütz, J. Pannek 365–378
379–390 Software 379–390
- 379–384 A unified middleware for SoC-agnostic application development S. Duda, Laurent Emmerich S. Duda, Laurent Emmerich 379–384
- 385–390 Automotive OS reloaded – Refocus and Reality Check C. Horn C. Horn 385–390
391–436 Automotive AI – Applications 391–436
- 391–404 AI-Based Energy Management of Next Generation Architectures L. Li, M. Schlecker, T. Zipper L. Li, M. Schlecker, T. Zipper 391–404
- 405–418 Generative Artificial Intelligence – How AI Models Change the Way We Develop Automotive Products P. Dreiseitel, D. Yesilbas P. Dreiseitel, D. Yesilbas 405–418
- 419–436 Validation and Interpretation of Neural Networks: DNN-Based Object Detection as an Example X. Wang, A. Hübner, K. Weishaupt, K. Chung X. Wang, A. Hübner, K. Weishaupt, K. Chung 419–436
437–462 System Engineering and Processes 437–462
- 437–442 Virtual Homologation – new opportunities for the automotive industry to enable more efficient development processes and improving safety and quality of vehicles for high scaling software updates A. Kraus, R. Lokner A. Kraus, R. Lokner 437–442
- 443–446 An Approach to Digital Lifecycle Management as a Service H. Bastian H. Bastian 443–446
- 447–462 Master Algorithm for Event-based Co-Simulation with FMI 3.0 for Timing Accurate Software-in-the-Loop O. Kotte, L. Beermann, D. Ziegenbein, S. Ravi, M. Vinnakota O. Kotte, L. Beermann, D. Ziegenbein, S. Ravi, M. Vinnakota 447–462
463–502 Security – Vulnerabilities 463–502
- 463–478 Automotive Software Vulnerabilities: Strategies for Early Detection, Mitigation, and Prevention in the Software-Development-Lifecycle A. Weichslgartner A. Weichslgartner 463–478
- 479–496 Supply chain security risks of software driven products T. Löhr, B. Bauer T. Löhr, B. Bauer 479–496
- 497–502 Tales from a Penetration Testing Team I. Lidovski, A. Geynis I. Lidovski, A. Geynis 497–502
503–518 Panel Discussion 503–518
- A leap in innovation – What European OEMs can learn from Chinese OEMs in terms of User Experience A. Matarage A. Matarage
519–558 Software – Cloud & Data 519–558
- 519–532 Sustainable Software Development for Cloud-Native Vehicles M. Bornemann, F. Baumann M. Bornemann, F. Baumann 519–532
- 533–542 Rust for Automotive – A Modern, Memory-Safe and Secure Programming Language M. Cupelli M. Cupelli 533–542
- 543–558 Software-Defined Vehicle: Combining Real-Time Safety Critical Functions with Cloud Connectivity S. K S, Tata Elxsi, N. Velinov S. K S, Tata Elxsi, N. Velinov 543–558
559–598 System Engineering and Processes 559–598
- 559–572 Challenges in the Synchronous Development of Software, Hardware and Mechanics for Drive Systems P. Fietkau, L. Diebolder P. Fietkau, L. Diebolder 559–572
- 573–588 A Review of using Artificial Intelligence in Large Projects for Requirements Classification H. Ghezali, L. Trautmann, S. Witke, S. Herbold H. Ghezali, L. Trautmann, S. Witke, S. Herbold 573–588
- 589–598 Addressing the challenge of “integrating everything” C. Hübscher, R. Geppert C. Hübscher, R. Geppert 589–598
599–634 Security – Challenges 599–634
- 599–612 Why Trusted Execution Environments are Critical for Automotive Security A. Till, R. Hayton A. Till, R. Hayton 599–612
- 613–622 Distributed development along the automotive supply chain: 8 insightful recommendations for OEMs and suppliers to jointly implement cybersecurity M. Sandler M. Sandler 613–622
- 623–634 Where is Everybody? – Looking for Remote Attacks on Cars in the Wild N. Ilg, D. Sisejkovic, P. Duplys N. Ilg, D. Sisejkovic, P. Duplys 623–634
635–XVIII Electric / Electronics for Commercial Vehicles 2023 635–XVIII
- 635–644 SAE J1939 in AUTOSAR – CAN FD and CAN XL – Achieve Higher Data Rates for J1939 Communication in AUTOSAR T. Schwendner, M. Schlodder T. Schwendner, M. Schlodder 635–644
- 645–662 Event-Chain-Focused Development of System Architectures Makes Complex Systems Manageable F. Mayer, J. Apelt, R. Münzenberger, F. Kraft, C. Winkler F. Mayer, J. Apelt, R. Münzenberger, F. Kraft, C. Winkler 645–662
- 663–672 How Data-driven Approaches Enhance Agile and Quality-assured Software Development for AD K. Fuchs, G. Hasenbichler K. Fuchs, G. Hasenbichler 663–672
- 673–676 An evolutionary approach to commercializing autonomous vehicles S. Choi S. Choi 673–676
- 677–688 Key Factors of a robust and safe Automated Driving Function – Transferable Insights of City-Bus Platooning in Munich N. Kechler, E. Sax, N. Venkatesh N. Kechler, E. Sax, N. Venkatesh 677–688
- 689–702 Hydrogen – A Game Changer in the Automotive Industry ... and Beyond S. Spitzer, S. Wahl S. Spitzer, S. Wahl 689–702
- 703–710 Electrified commercial vehicle trailers – how to turn a conventional trailer into a hybrid vehicle N. Pfullmann N. Pfullmann 703–710
- 711–XVIII Modular High Power DC/DC Platform for FC-Applications B. Budaker B. Budaker 711–XVIII

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