Overview
Vehicle deformation as a possible indicator of crash severity
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Table of contents (15 chapters)
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Front Matter
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State-of-the-Art
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Front Matter
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New Algorithm Concept and Simulation Model
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Front Matter
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Methods and Results
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Front Matter
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Back Matter
Keywords
About this book
State-of-the-art airbag algorithms make a decision to fire restraint systems in a crash by evaluating the deceleration of the entire vehicle during the single events of the accident. In order to meet the ever increasing requirements of consumer test organizations and global legislators, a detailed knowledge of the nature and direction of the crash would be of great benefit. The algorithms used in current vehicles can only do this to a limited extent. André Leschke presents a completely different algorithm concept to solve these problems. In addition to vehicle deceleration, the chronological sequence of an accident and the associated local and temporal destruction of the vehicle are possible indicators for an accident’s severity.
About the Author:
Dr. André Leschke has earned his doctoral degree from Tor-Vergata University of Rome, Italy. Currently, he is working as head of a team of vehicle safety developers in the German automotive industry.
Authors and Affiliations
About the author
Bibliographic Information
Book Title: Algorithm Concept for Crash Detection in Passenger Cars
Authors: André Leschke
DOI: https://doi.org/10.1007/978-3-658-29392-5
Publisher: Springer Vieweg Wiesbaden
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2020
Hardcover ISBN: 978-3-658-29391-8Published: 19 March 2020
Softcover ISBN: 978-3-658-29394-9Published: 20 March 2021
eBook ISBN: 978-3-658-29392-5Published: 18 March 2020
Edition Number: 1
Number of Pages: XXXIV, 271
Number of Illustrations: 101 b/w illustrations, 56 illustrations in colour
Topics: Automotive Engineering, Electrical Engineering, Simulation and Modeling