Optimization Of Rule-based Energy Management Strategy For Electric Vehicle Hybrid Energy Storage System

Electric vehicles(EVs)are favored by people because of the advantages of energy saving and environmental protection.One of the key technologies of EVs is the research of energy storage systems.Traditional EVs mostly use single power batteries as energy storage components,while power batteries have the disadvantages of low power density and short cycle life.It is difficult to meet the energy and power requirements for frequent start-up,acceleration and braking in urban road conditions.Ultracapacitor(UC)has the advantages of high power density,high charge/discharge speed,long cycle life and a wide operating temperature range,it can be combined with lithium-ion battery to form a hybrid energy storage system(HESS)as an EV vehicle power source.Firstly,outlined the research background of this article,analyzed the current development status of EVs and power batteries at home and abroad,and the main research methods of HESS energy management strategies.Focusing on the shortcomings in traditional HESS energy management strategies,the main research contents of this paper are proposed.Detailedly analysised the working principle and characteristics of each energy storage unit,established the equivalent model of lithium-ion battery and super capacitor,choosed the right topology and analyzed the working principle and function of bidirectional DC/DC converter in HESS.Secondly,according to the equivalent model of lithium-ion battery and ultracapacitor,EKF(extended Kalman filter method)is used to estimate the state of charge(SOC)of the lithium-ion battery and the integral compensation method is used to calculate the SOC of the ultracapacitor,then a weighted method was studied for calculating the overall SOC of the HESS.According to HESS modelling and SOC estimation,a rule-based HESS energy management strategy was designed.The dynamic programming(DP)optimization scheme was proposed in the control strategy,which could not adapt to the dynamic changes of operating conditions.The DP algorithm is used to solve the objective function of the EV demand power,three control rules were extracted from the results,according to the threshold parameters of speed and demand power,an optimized energy management control strategy was developed.Finally,the original control strategy and optimization control strategy were selected on the ADVISOR simulation platform to select the same cycle condition UDDS to simulate the EV vehicle under different conditions.The analysis data shows that the optimized control strategy can better exert the performance advantages of the “peak cut and valley fill” of the super capacitor,reduced the charge and discharge spikes of lithium-ion batteries,avoid lithium ion batteries of frequent charging and discharging,improve battery life;it also recovers the energy generated by EV braking through ultracapacitor,then reduced vehicle energy loss..