Study On Energy Management Strategy Of Extended-range Electric Vehicle

Extended-range electric vehicles have the characteristics of low cost and high ranges.Energy management strategy is the core control strategy of extended-range electric vehicles.Its control effect largely determines the fuel economy and range of the vehicle.In-depth research and improvement of the strategy can not only improve the fuel economy of the vehicle,but also maintain the battery state of charge(SOC)to achieve long battery life.This paper summarizes the current research status of energy management strategies at home and abroad,by studying the structure and working principle of the target vehicle,a full-range electric vehicle model is established,combines with the working mode of the target vehicle,an energy management strategy based on accurate rules is established and the model is verified.Establish an energy management strategy based on fuzzy control and use a particle optimization algorithm to optimize the membership function,combine multiple working cycle characters and use neural network algorithms to establish a neural network-based energy management strategy,compare and analyze the equivalent fuel economy from different energy management strategies.The main research contents of the paper are as follows:First of all,the background and significance of this topic were introduced,determined the range-extended electric vehicle as the research object.The research status of energy management strategy at home and abroad was summarized,and the deficiencies in the research were discovered,and the research content and technical route of this topic were determined.Secondly,combined with the specific structure,parameters and working principle of an extended-range electric vehicle,analyzed the theoretical structure and test bench results of key components such as range extender,motor,battery and transmission system,the wholevehicle model of the extended-range electric vehicle was established in Matlab/Simulink using a combination of experiment and theoretical modeling.Then,according to the specific working mode of the actual vehicle,the design rules for the energy management strategy of the extended-range electric vehicle were proposed,and the engine multi-operating point energy management strategy was established in Stateflow in combination with the optimal operating point of the engine,which was embedded in the Simulink vehicle model Simulation.On this basis,the fuzzy control algorithm which used by tradition hybrid vehicle was combined to establish the fuzzy control energy management strategy,and the simulation analysis and comparison were carried out to verify the control effect.Next,aimed at the shortcoming that fuzzy control rule making had subjectivity,combined the particle swarm algorithm to optimize the membership function in the fuzzy controller.Through simulation analysis and comparison of different working conditions,the control effect of the optimized energy management strategy was verified.Finally,in order to improve the optimization effect of energy management strategy on fuel economy under random working conditions,combined with the radial basis function neural network,an energy management strategy based on working condition identification was established,which realized working condition recognition and could produce good optimization effect on fuel economy under different working conditions.At last,the research results and content of the whole paper were summarized,and looked forward to the next stage of research.