Study On Electric Vehicle Dynamic Parameters Matching And Simulation

The traditional fuel vehicle is an important symbol of modern industrialcivilization, but it also brings the human society with petroleum energy shortages,global warming, air pollution, noise pollution and a series of negative effects, theseproblems have gradually affected the survival and development of mankind. The pureelectric vehicles as a new kind of energy vehicle with zero emissions are widelyconsidered to be one of the effective methods to solve the above problems.The development of pure electric cars attracts more and more attention. Parametermatching of power system is one of the main contents of pure electric vehicle researchand development, which includes the selection of battery, the selection of motor, thedetermination of transmission ratio and spatial arrangement. Precise parameter matchinghas a great influence on the automobile’s power performance, it also has a significanteffect on the endurance mileage.In this paper, the pure electric vehicle is the research object, Simulation anddynamic parameters matching are carried on. The main research work includes:First of all, the forces on the pure electric vehicles are analyzed according to thetraditional vehicle dynamics research method, a dynamic model of the pure electricvehicle is set up.Secondly, the pure electric vehicle kinetics parameters are initially designed andmatched.Thirdly, as a platform of the simulation software ADVISOR, the simulation modelsof all parts which make up the power system of pure electric vehicles (including motor,battery, the main reducer, differential, wheels and so on) are established, the wholeperformance of vehicle is simulated dynamically, such as dynamic performance andendurance mileage. By analyzing the results of ADVISOR simulation, the effects ofdifferent components of the power system parameters on the performance of pureelectric vehicles are studied.Finally, the power system parameters are optimized according to ant colony geneticalgorithm. And the design schemes before and after optimization are compared by using ADVISOR, the results show that the optimization effect is obvious, the application ofant colony genetic algorithm to the parameters matching of power system is feasible.