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10th International Munich Chassis Symposium 2019

chassis.tech plus

  • Peter E. Pfeffer
Conference proceedings

Part of the Proceedings book series (PROCEE)

Table of contents

  1. Front Matter
    Pages I-XXI
  2. KEYNOTE LECTURES I

  3. KEYNOTE LECTURES II

  4. KEYNOTE LECTURES III

  5. INNOVATIVE CHASSIS SOLUTIONS

  6. RISK ANALYSES AND VIRTUAL METHODS

  7. AI IN THE CHASSIS

    1. Front Matter
      Pages 155-156
    2. Yuran Liang, Steffen Müller, Daniel Rolle, Dieter Ganesch, Immanuel Schaffer
      Pages 159-178
    3. Guru Bhargava Khandavalli, Marcus Kalabis, Daniel Wegener, Lutz Eckstein
      Pages 179-199
  8. LIGHTWEIGHT DESIGN AND DRIVEABILITY

    1. Front Matter
      Pages 229-229
    2. Peter Kuhn, Christoph Loy, M. Kuehnel, W. Pinch, C. Ebel
      Pages 249-261
  9. CHARACTERIZATION OF ADAS DRIVING PROPERTIES

    1. Front Matter
      Pages 289-290
    2. Manuel Höfer, Florian Fuhr, Bernhard Schick, Peter E. Pfeffer
      Pages 293-306
    3. A. Affani, P. Zontone, R. Fenici, D. Brisinda, D. Bacchin, L. Gamberini et al.
      Pages 307-321
    4. Guido Tosolin, Jaume Cartró, Vishwas Sharma
      Pages 323-340
  10. DEVELOPMENT METHODS

    1. Front Matter
      Pages 341-341
    2. Matthias Wilmes, Rob Kraaijeveld, Marvin Schrage, Frank Schummers
      Pages 343-353
    3. Sergey Orlov, Matthias Korte, Florian Oszwald, Pascal Vollmer
      Pages 355-368
  11. RIDE COMFORT

  12. DEVELOPMENT METHODOLOGY AND AI

    1. Front Matter
      Pages 445-446
    2. Patrick Krupka, Paul Lukowicz, Christopher Kreis, Bastian Boßdorf-Zimmer
      Pages 449-464
    3. Marcus Irmer, Michael Haßenberg, Hermann Briese, Hermann Henrichfreise
      Pages 465-479
    4. Xabier Carrera Akutain, Kimiaki Ono, Francesco Comolli, Massimiliano Gobbi, Giampiero Mastinu
      Pages 481-502
  13. NEW STEERING TECHNOLOGIES

    1. Front Matter
      Pages 503-503
    2. Dirk Ferge, Takumi Mio, Toyoki Sugiyama, Satou Fumihiko, Satoshi Shinoda
      Pages 505-513
    3. Bertram Moeller, M. Nakielski
      Pages 515-530
    4. Dominik Nees, Jannick Altherr, Marcel Ph. Mayer, Michael Frey, Sebastian Buchwald, Philipp Kautzmann
      Pages 531-547
  14. HUMAN-MACHINE INTERFACE

    1. Front Matter
      Pages 549-549

About these proceedings

Introduction

The increasing automation of driving functions and the electrification of powertrains present new challenges for the chassis with regard to complexity, redundancy, data security,
and installation space. At the same time, the mobility of the future will also require entirely new vehicle concepts, particularly in urban areas. The intelligent chassis must be connected, electrified, and automated in order to be best prepared for this future.

Contents

Innovative chassis solutions.- Risk analyses and virtual methods.- AI in the chassis.- Lightweight design and driveability.- Characterization of ADAS driving properties.- Development methods.- System Requirements and brake feel.- Innovative brake components.- Ride comfort.- Systems for electric/connected vehicles.- Development methodology and AI.- New steering technologies.- Wheel technologies and requirements.- Tire tests and simulations.- Human-machine interface.- Vehicle dynamics and tire development.

Target audiences

Automotive engineers and chassis specialists as well as students looking for state-of-the-art information regarding their field of activity - Lecturers and instructors at universities and universities of applied sciences with the main subject of automotive engineering - Experts, researchers and development engineers of the automotive and the supplying industry

Publisher

ATZ live stands for top quality and a high level of specialist information and is part of Springer Nature, one of the leading publishing groups worldwide for scientific, educational and specialist literature. 

Partner 
TÜV SÜD is an international leading technical service organisation catering to the industry, mobility and certification segment.

Keywords

Chassis for future mobility Challenges and solutions Urban mobility Deep learning approaches Model-based parameter

Editors and affiliations

  • Peter E. Pfeffer
    • 1
  1. 1.Munich University of Applied SciencesMunichGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-658-26435-2
  • Copyright Information Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2020
  • Publisher Name Springer Vieweg, Wiesbaden
  • eBook Packages Engineering
  • Print ISBN 978-3-658-26434-5
  • Online ISBN 978-3-658-26435-2
  • Series Print ISSN 2198-7432
  • Series Online ISSN 2198-7440
  • Buy this book on publisher's site