Jixie chuandong (Feb 2019)
Parameter Matching and Optimization of Electric Vehicle Powertrain
Abstract
Taking a pure electric vehicle as the research object， the optimization of power system parameters is analyzed. Based on the energy transfer of the whole vehicle， a preliminary parameter matching method is developed to meet the performance design target. By establishing the simulation model in Cruise and the vehicle control strategy in MATLAB， the Cruise-MATLAB/Simulink co-simulation is realized， and the rationality of the model is verified. Nonlinear weighted particle swarm optimization （NWPSO） is used to decouple the parameters and realize the global optimization with the vehicle economy as the optimization objective and the coupling relationship among the parameters as the constraints. The results before and after optimization are compared and analyzed by simulation. The results show that the power performance of the whole vehicle is basically unchanged， but the economic performance is improved significantly. The correctness and feasibility of the matching optimization method are verified， which makes the matching of vehicle power system parameters more reasonable.
