Research On Energy Control Strategy Of Pure Electric Vehicle Hybrid Power System

Promoting and encouraging the innovative development of the new energy automobile industry is one of the important manifestations of our country's advocacy of green life.However,limited by the current level of battery technology development,on-board batteries still have problems such as high cost and insufficient life,which cannot meet the needs of consumers in terms of driving range and economic costs.In order to alleviate such problems,composite power sources have begun to receive attention and have gradually become the research focus of various universities and enterprises.The composite power supply is equipped with two energy storage components,which make up for shortcomings by coordinating the output relationship of the two power supplies and improves the overall performance of the energy system.This article uses a super capacitor-lithium iron phosphate battery combination of composite power supply,through the use of super capacitors to improve the service life and energy efficiency of lithium batteries,and further improve the endurance of the vehicle.The main contents of the paper are as follows:(1)Analyze the connection mode of the composite power system,select the semi-active configuration with the ultracapacitor as the main control unit,and formulate the corresponding working mode;analyze the characteristics of the main components in the system,and complete each according to the power index of the electric vehicle The parameters of the parts match.(2)Formulate the energy management control strategy of the compound power supply based on fuzzy logic control.On this basis,in order to improve the control accuracy of the controller and realize more effective and reasonable energy distribution,Genetic algorithm is introduced to optimize the membership function parameters of fuzzy control in order to obtain global optimal control,aiming at the minimum energy consumption(ECR)of 100 km and the highest braking energy recovery efficiency.(3)In order to further improve the control effect of vehicle energy distribution in practical applications,operating condition recognition control is introduced.By constructing typical operating conditions and BP neural network,the characteristics of real-time vehicle driving data are extracted and identified,and corresponding parameters(The optimal control parameters under typical working conditions)are called according to the identification results.An adaptive energy control strategy based on condition recognition is implemented.Build energy control strategy model and vehicle simulation model in Matlab and AvlCruise respectively,and verify the built control strategy through joint simulation.The results show that:(1)Under NEDC and UDDS conditions,the parameter matching of the composite power system can meet the set performance requirements,and the built fuzzy controller can reasonably allocate energy,increase the service life of the power battery,and extend the driving range of electric vehicles.(2)The controller optimized by the genetic algorithm has a significantly better control effect than before the optimization.The total energy consumption of the system under different working conditions is significantly reduced,and the efficiency of the power battery is significantly improved.(3)After introducing the working condition recognition control,the established control strategy can effectively identify the working condition information,and can switch the corresponding working mode based on this,which has better energy-saving effect.