Dynamic Energy Management Strategy Of PHEV Based On The Recognition Of Driving Cycle And Driving Style

Unlike traditional fuel-powered vehicles,the plug-in hybrid electric vehicle(PHEV)can use both an engine and an electric motor to drive the vehicle,taking advantage of both pure electric vehicles and conventional petrol-powered vehicles.For the hybrid power system,reasonable power component parameters and energy management strategy will have a very important impact on the comprehensive economy of the vehicle.This paper takes a plug-in hybrid electric vehicle as the research object,combines driving cycle,driving style,parameter optimization and rule-based energy management strategy,and makes the dynamic energy management strategy of PHEV based on the recognition of driving cycle and driving style.The specific research contents are as follows:(1)The research object of this paper is a plug-in hybrid electric vehicle,whose hybrid power system adopts the structure of single row planetary wheel and double motors;According to the relevant theoretical knowledge,this paper has completed the calculation of engine,motor,battery and transmission ratio and other parameters;The forward simulation model of the vehicle was established based on Matlab/Simulink platform,and a rule-based energy management strategy was developed based on the relevant logic threshold value;The simulation results show that both dynamic performance and economic performance meet the requirements of design indicators.(2)Through the analysis of 24 typical driving cycle,four standard driving cycle and a comprehensive driving cycle were constructed through a series of operations including principal component analysis(PCA)and clustering analysis;Based on the research of driving cycle,this paper divides the driving style of drivers into three types: radical type,standard type and calm type;Taking the influence of driving cycle and driving style into consideration,this paper constructs a parameter optimization model of energy management strategy by means of model in the loop,and obtains the optimized parameter database that takes driving cycle and driving style into account.(3)In this paper,genetic algorithm is used to establish parameter optimization model and optimize parameter database by means of model in the loop;In this paper,a driving cycle recognition model is established based on BP neural network,and an energy management strategy based on the recognition of driving cycle is developed,which can call the parameters in the optimized parameter database in real time according to the result of cycle recognition.Its comprehensive economy efficiency is about 3.20% higher than the rule-based energy management strategy.In this paper,a fuzzy controller is used to establish a driving style recognition model.Based on the energy management strategy based on the recognition of driving cycle and the influence of driver factors on fuel economy,a dynamic energy management strategy based on the recognition of driving cycle and driving style for plug-in hybrid electric vehicles is proposed.After simulation verification of a comprehensive driving cycle,compared with the energy management strategy based on the recognition of driving cycle and the rule-based energy management strategy,its comprehensive economy is improved by 1.91% and 5.05% respectively.