Algorithm Concept for Crash Detection in Passenger Cars
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.

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Algorithm Concept for Crash Detection in Passenger Cars
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.

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Algorithm Concept for Crash Detection in Passenger Cars

Algorithm Concept for Crash Detection in Passenger Cars

by Andrï Leschke
Algorithm Concept for Crash Detection in Passenger Cars

Algorithm Concept for Crash Detection in Passenger Cars

by Andrï Leschke

Hardcover(1st ed. 2020)

$169.99 
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Overview

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.


Product Details

ISBN-13: 9783658293918
Publisher: Springer Fachmedien Wiesbaden
Publication date: 03/19/2020
Edition description: 1st ed. 2020
Pages: 271
Product dimensions: 5.83(w) x 8.27(h) x (d)

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.

Table of Contents

State of the art: Vehicle Structure, Restraint Systems, Electronic Systems and Algorithm for Crash Detection.- Model Proposal for the Description of Threshold-based Algorithms.- Simulation Model for Component-specific Local Loading.- New Algorithm Concept for Crash Detection based on Local Component-specific Loads and for the Classification of Load Cases.
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