6533b86ffe1ef96bd12ce6e5

RESEARCH PRODUCT

A Mathematical Model for Vehicle-Occupant Frontal Crash Using Genetic Algorithm

Kjell G. RobbersmyrHamid Reza KarimiBernard B. Munyazikwiye

subject

0209 industrial biotechnologyChassisbusiness.industryComputer scienceCrash02 engineering and technologyStructural engineeringCrash testDisplacement (vector)DamperShock absorber020303 mechanical engineering & transports020901 industrial engineering & automation0203 mechanical engineeringGenetic algorithmPiecewisebusinessSimulation

description

In this paper, a mathematical model for vehicle-occupant frontal crash is developed. The developed model is represented as a double-spring-mass-damper system, whereby the front mass and the rear mass represent the vehicle chassis and the occupant, respectively. The springs and dampers in the model are nonlinear piecewise functions of displacements and velocities respectively. More specifically, a genetic algorithm (GA) approach is proposed for estimating the parameters of vehicle front structure and restraint system. Finally, it is shown that the obtained model can accurately reproduce the real crash test data taken from the National Highway Traffic Safety Administration (NHTSA). The maximum dynamic crash of the vehicle model is 0.05% less than that in the real crash test. The displacement of the occupant is 0.09% larger than that from the crash test. Improvement of the model accuracy is also observed from the time at maximum displacement and the rebound velocities for both the vehicle and occupant.

yearjournalcountryeditionlanguage
2016-04-012016 UKSim-AMSS 18th International Conference on Computer Modelling and Simulation (UKSim)
https://doi.org/10.1109/uksim.2016.12