Study On Matching And Optimization Of Pure Electric Vehicle Power System Parameters

Vehicle has become an important means of transport in modern society,but it also brings enormous challenges to environment and energy supply of the world with the rapid increasing of vehicle ownership.Because it's powered by rechargeable battery,and driven by motor,pure electric vehicle has significant advantages,such as no emission,low noise and high energy efficiency,so that it has attracted more and more attentions of automotive industry and vehicle researchers.The parameter matching and optimization of the pure electric vehicle power system is crucial for the electric vehicle designing.The main work of parameter matching is to select the types of power system assemblies and match the parameters according to the design performance.Then,to improve the overall performance of the vehicle,algorithm will be used to optimize the parameters of the power system.In this thesis,one pure electric vehicle power system is matched and optimized.The content of this thesis mainly includes:(1)The basic structure of pure electric vehicle is introduced,and the force on a pure electric vehicle is analyzed based on principle of automobile kinematics.The power indexes such as maximum speed,acceleration time and the economic indexes such as specific energy consumption and driving distance are presented.(2)According to the designed performance requirements,the types of drive motor,the battery and the transmission system are selected and their parameters are matched.(3)The vehicle model and assembly models such as motor model,battery model of the pure electric vehicle are built by using ADVISOR.A number of simulations are carried out to analyze the power and economic performance of this pure electric vehicle.Simulation results show that power system parameters matched can satisfy the designed requirement.(4)The basic theories of genetic algorithm are studied.The parameters of the power system of the pure electric vehicle are optimized by using GA.Compared with the previous results,after optimization the driving distance increases by 3.72% and specific energy consumption decreases by 2.71% when it drives in CYC_NEDC cycle.Power performance isalso got certain improvement that the acceleration time from 0~100km/h reduced by 2.15%and the max speed increased by 1.77%.Therefore the genetic algorithm has better effect on optimization of the power system of the pure electric vehicle.