Study On Energy Management Strategy Of Plug-in Hybrid Electric System Considering Battery Aging

With the energy crisis,air pollution and the staggering growth of mobility demands,new energy vehicles have always been the focus of the development of automobile industry in the world.As an important direction of the development of new energy vehicles,plug-in hybrid electric vehicles have significant advantages in improving fuel economy and reducing pollutant emissions.However,they may be subject to expensive battery replacement caused by battery aging.Therefore,how to prolong battery life should be carefully considered in the design of supervisory energy management strategies.This paper takes a plug-in parallel hybrid electric bus loaded with lithium iron phosphate batteries as the research object,and conducts study on an energy management strategy considering the battery aging.The specific research contents are as follows:(1)The longitudinal dynamic model of the vehicle and the control-oriented mathematical model of each subsystem in the powertrain are established,and the gear shifting strategy considering the energy recovery efficiency of the motor is formulated.The basic theories of Dynamic Programming(DP)and Pontryagain’s Minimum Principle(PMP)are expounded respectively,in addition,the optimization function and constraints are defined according to the research objectives.The optimization performance and solution efficiency of the two strategies are compared and analyzed,the global optimal characteristics of PMP are revealed,and its advantage in computational efficiency is proved.(2)Based on PMP algorithm,the multi-objective optimization problem integrated with battery aging and energy consumption is studied.After analyzing the external factors and root causes that affect battery aging,a semi-empirical capacity attenuation model considering battery cycle aging and calendar aging is established,and a multi-objective optimization framework of PMP is constructed by unifying battery aging,fuel consumption and energy consumption.Furthermore,by making the service life of the battery reach the service life of the bus,the ideal compromise scheme between energy consumption and battery aging is determined,and the important influence of calendar aging on battery service life is revealed.Moreover,the rationality of the ideal compromise scheme and its sensitivity to battery price are analyzed.(3)Based on the stochastic characteristics of traffic conditions,a mathematical modeling method of random driving cycles is proposed.According to the implementation principle of the equivalent fuel consumption minimum strategy,an adaptive energy consumption optimization strategy based on SOC feedback is designed by using PI controller,and the influence mechanism of different adaptive parameters on the control strategy is studied.In order to realize the on-line collaborative optimization of battery aging and energy consumption,based on the fact that both SOC and effective Ahthroughput of the battery are approximately linear with the driving distance,a doublestate adaptive optimization strategy is developed according to the PMP principle.The simulation results verify the feasibility and effectiveness of the strategy.(4)In view of the shortcomings of the dual-state adaptive optimization strategy,based on the kernel density estimation and entropy weight Bayesian theory,the algorithm of condition severity identification is designed,and the adaptive scheme integrating driving cycle severity identification and PI control is developed;By applying chargesustaining control,the problem that SOC termination value deviates from the target value downward is solved,and the simulation analysis of adaptive strategy is carried out by MATLAB.The results show that the improved adaptive strategy has certain improvement in both adaptive performance and optimization performance.