Optimizing Control and Stability of a Light Commercial Vehicle Based on MOPSO
To address the issue of large roll angle rates in the steady-state circular testing of a light commercial vehicle,its suspension system is optimized and improved.The multi-body dynamics model of the vehicle is established using ADAMS/car.The accuracy of the suspension simulation model is verified by the anti-phase parallel wheel travel test for the front suspension and theoretical calculations for the rear suspension.Through simulation analysis of the vehicle's steady-state circular test and on-center steering test,it is concluded that the roll angle rate is higher than desired.To achieve the automated process of stability optimization analysis,a co-simulation method based on modeFRONTIER is proposed.Taking the suspension design parameters as optimization variables,and targeting the roll angle rate and yaw rate time delay as the optimization objectives,a hybrid agent model was fitted using the Latin hypercube experiment design method.This model was combined with the multi-objective particle swarm optimization algorithm(MOPSO)to carry out the multi-objective optimization of the suspension system,and the optimization scheme of the suspension system is obtained.The optimization results show that,while maintaining ride comfort,the roll angle rate is reduced by 13.93%and the yaw rate time delay is reduced by 2.75%,resulting in improved vehicle control and stability.
controlling and stabilityagent modeljoint simulationmulti-objective particle swarm optimization algorithmADAMS/car
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