Parameter Matching Design Of Powertrain For Battery Electric Vehicle Based On Genetic Algorithm

Battery Electric Vehicle(EV),refers to the vehicle which takes batteries as the power,makes use of motor to drive vehicles,conforms to the requirements of road traffic and safety regulations.The motor is substituted for engine to achieve zero emissions.In aspects,such as dynamic property,economy,safety and reliability,EV performs better or close to the traditional engine vehicles.As for the driving range,it can meet the general driving requirements.Furthermore,EV has advantages of low noise,easy maintenance,high energy efficiency and recoverability.It is the ideal energy vehicles in the future.In this paper,a compact passenger vehicle is set as the research object,explores the core content of the electric vehicle powertrain parameter matching method,shift law,speed ratio optimization and matching,and build a vehicle combined simulation test platform,in order to verify the correctness and rationality of component selection and optimization design,the main contents are as follows:First of all,aiming at the target vehicle,a new parameter matching method is adopted.By dividing the power requirements into three levels(that is,the limit condition requirements,the acceleration ability requirements and the efficiency optimization requirements),from low level to high level,match and design the key components in turn.Among them,in terms of efficiency optimization matching,this paper selects the condition analysis method based on energy probability density,focuses on the efficiency point of energy conversion and divides a more scientific target section.Finally,the vehicle can meet the power requirements as well as make full use of the motor's high efficient area,and achieve good economy performance.Then,this study takes Matlab/Simulink as the main control part,combined with the advanced modeling software AMEsim to build the vehicle simulation platform,using bench test to calibrate and verify the results,as well as paving the way for further research.Based on the genetic algorithm,this paper optimizes the ratio of electric vehicle transmission system.Use the vehicle energy consumption as optimized objective function and regard the dynamic demand as the constraint condition.With the help of the genetic algorithm toolbox,obtain the global optimal result and be verified by the simulation experiment.Analyze the power requirement and economic performance before and after the optimization in fixed speed ratio vehicle,two gearbox as well as the difference between two optimized objects.The results show that the optimization effect is obvious,the energy consumption is reduced,the driving range is increased and the vehicle performance is improved.At last,according to the design requirements,select the transmission speed scheme and draw the shift curve.Through the analysis and comparison by simulation test,make sure of the impact on dynamic property,economy and comprehensive shift law.Finally,choose the comprehensive shift law to ensure that the power and economic performance of vehicle can be as excellent as possible.This study has a certain refered value for the design of electric vehicle powertrain parameter matching,the selection of shift law and the optimization of transmission ratio based on genetic algorithm,which has played a positive significance for the common use of electric vehicle.