文章基本信息

标题：Application of Genetic Algorithm on Parameter Optimization of Three Vehicle Crash Scenarios
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作者：Bernard B. Munyazikwiye ; Hamid R. Karimi ; Kjell G. Robbersmyr 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2017
卷号：50
期号：1
页码：3697-3701
DOI：10.1016/j.ifacol.2017.08.564
语种：English
出版社：Elsevier
摘要：AbstractThis paper focuses on the development of mathematical models for vehicle frontal crashes. The models under consideration are threefold: a vehicle into barrier, vehicle-occupant and vehicle to vehicle frontal crashes. The first model is represented as a simple spring-mass-damper and the second case consists of a double-spring-mass-damper system, whereby the front mass and the rear mass represent the vehicle chassis and the occupant, respectively. The third model consists of a collision of two vehicles represented by two masses moving in opposite directions. The springs and dampers in the models are nonlinear piecewise functions of displacements and velocities respectively. More specifically, a genetic algorithm (GA) approach is proposed for estimating the parameters of vehicles front structure and restraint system for vehicle-occupant model. Finally, using the existing test-data, it is shown that the obtained models can accurately reproduce the real crash test data.
关键词：KeywordsModelingvehicle-occupantfrontal crashparameters estimationgenetic algorithm