Research On Energy Management System Of New Energy Electric Vehicles

With the emergence of China’s energy crisis and the increasingly urgent requirements of "emission peak" and "carbon neutrality",the new energy electric vehicle must have a good development prospect in the trend of future vehicles.New energy electric vehicles often use lithium batteries with high energy density as energy source,but lithium batteries also have problems such as power density and low cycle life,which have limited the performance of electric vehicle.The emerging energy storage element supercapacitor is often used to assist the main energy source due to its high power density and high allowable charging and discharging power.Therefore,the hybrid energy storage system composed of lithium battery supercapacitor can be used in pure electric vehicles to achieve the goal of comprehensive energy and power demand of vehicle power system.The main research contents of this paper are as follows:Firstly,common model structures are difficult to meet the requirements of parameter identification.This paper based on the working principle of lithium battery and the advantages of common models,a second-order fractional lithium battery model of Thevenin equivalent circuit was established.Then,based on this model,the model parameters and fractional orders were identified by using adaptive genetic algorithm.The simulation results show that the maximum terminal voltage error under the model is reduced to less than 1%,which shows that this method can improve the parameter quality of lithium battery and lay a foundation for the research of lithium battery state estimation.Secondly,in order to further improve the applicability of the Kalman filter algorithm on the fractional-order lithium battery model and the accuracy of the state of charge estimation,This paper proposes to combine the multi innovation identification theory with the extended Kalman filter algorithm and apply it to the state of charge estimation of lithium battery,and design a FOMIEKF algorithm with stronger tracking ability.Finally,the simulation experiment proves the accuracy of the algorithm,and the average error of FOMIEKF algorithm is 0.79%and the maximum error is less than 2%.Finally,in view of the situation that a large amount of transient power exists in some power demand signals of pure electric vehicles equipped with hybrid energy storage system,the wavelet transform method is proposed to extract the high-frequency transient component from the power demand signal,so that the supercapacitor can bear transient power that lithium batteries cannot bear.According to the constraints on energy management for SOC of lithium battery and supercapacitor,fuzzy control strategy is used to improve the power demand after wavelet transform.The simulation test compares wavelet fuzzy strategy and pure fuzzy strategy under UDDS and HWFET working conditions,and verifies that wavelet fuzzy strategy has more advantages in lithium battery protection.The power release of lithium battery is significantly reduced,which also achieves the purpose of improving energy efficiency.The standard deviation of charge and discharge current is reduced during the working process.After the working cycle,the SOC of lithium battery is improved by about 1%.