6533b82cfe1ef96bd128eac3
RESEARCH PRODUCT
Application of Genetic Algorithm on Parameter Optimization of Three Vehicle Crash Scenarios
Kjell G. RobbersmyrHamid Reza KarimiBernard B. Munyazikwiyesubject
ChassisComputer scienceModeling010103 numerical & computational mathematics02 engineering and technologyCollision01 natural sciencesCrash testfrontal crashvehicle-occupantDamperNonlinear system020303 mechanical engineering & transports0203 mechanical engineeringControl theoryControl and Systems EngineeringGenetic algorithmparameters estimationgenetic algorithm0101 mathematicsSimulationfrontal crash; genetic algorithm; Modeling; parameters estimation; vehicle-occupant; Control and Systems EngineeringMotor vehicle crashdescription
Abstract This 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.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2017-07-01 |