Research On The Optimization And Control Strategy Of Hybrid Electric Vehicle Power System Based On Factor Analysis

With the continuous rise of the national economy,people's quality of life is also improved.As the main way of travel,vehicles are almost necessary for every family.Although vehicles bring great convenience to people's travel,they cause a series of problems,such as oil depletion and environmental pollution,which has aroused great attention of the state.The response policies have been issued,but the effect is not very optimistic.Nowadays,there are more and more scholars studying new energy vehicles,not many of them can consider from the perspective of consumers' vital interests.In order to find out the root causes that affect consumers' purchase of hybrid vehicles,firstly,some consumers were investigated by questionnaire,the collected data were processed professionally,and factor analysis was carried out by SPSS software to find out the root causes that lead to the supply of hybrid vehicles is greater than the demand.Secondly,optimized the higher factors that affect consumers' purchase of hybrid vehicles.In order to verify the optimization results conveniently,the whole vehicle model and its sub model of hybrid electric vehicle were built by using Matlab/Simulink software.At the same time,in order to simulate the driving condition of the vehicle more accurately,the reference model of vehicle moving steering was designed.As the power source of hybrid vehicles is not single,according to the SOC(stage of charge)of battery,the control system of hybrid electric vehicle was optimized by using logic gate control strategy.Then,the decision variables were determined according to the objective to be optimized,the double objective optimization function was established,and the corresponding constraints were made.This paper compares several commonly used algorithms of solving double objective optimization function,and selects NSGA-? to solve the objective function.Finally,the solution set satisfying the objective to be optimized is obtained,a group of solutions were randomly selected and substituted into the established vehicle model for simulation,which was compared with the results before optimization to verify the feasibility and practicability of the algorithm.Make the performance of hybrid vehicle more close to the actual needs of consumers,which can enhance consumers' purchase intention for hybrid vehicles,contribute to the popularization and development of new energy vehicles,and also contribute to the improvement of energy situation and environment.