Multi-objective optimization of chassis integrated system for electric wheel vehicle

In order to improve the overall performance of the electric wheel vehicle, this paper researches the multi-objective optimization method of the chassis integrated system. The dynamic models of integrated system including differential steering system, differential brake system, and active suspension system are established. In order to verify the validity of the vehicle dynamic model and ensure the correctness of the optimization analysis results, the model validation is implemented. Considering the coupling relationship among subsystems, the performance evaluation indexes of steering road feel, steering sensitivity, and suspension ride comfort are deduced under steering and braking conditions. To alleviate the subjectivity in the selection of objective weighting, the deviation sort polymerization method is used to convert the multi-objective model into a single-objective one based on the linear weighted polymerization. Aiming at the optimization characteristic of chassis integrated system, an adaptive weight particle swarm optimization algorithm is proposed to improve the optimization efficiency and convergence. The optimization results show that the optimized chassis integrated system can obtain favorable steering road feel, better steering sensitivity, and suspension ride comfort.