Research On Balance Control Strategy Based On Lithium Battery SOC Estimation

Due to the increasing impact of fossil energy on the environment,electric vehicles have become the future development direction of the automobile industry because of their relatively low noise and pollution.At present,the power source of pure electric vehicles mainly relies on lithium batteries,and it is necessary to connect multiple lithium batteries in series to form a battery pack to meet the power demand of electric vehicles.The inconsistency between the single cells of the battery pack will aggravate the inconsistency between the batteries when the car is driving in complex working conditions,which has a great impact on the performance of the battery pack.In order to weaken the influence of inconsistency,accurate estimation of battery SOC(State Of Charge.SOC)and an effective balancing strategy are critical to the lithium battery management system(Battery Management System.BMS).The main contents of this article are as follows:1)Introduce the characteristics of several common mathematical models that simulate the internal chemical characteristics of batteries,build the Thevenin secondorder RC equivalent circuit model as a model for battery SOC estimation,use pulse experimental data to identify model parameters,and establish corresponding mathematical equations The internal charge and discharge process of the battery.2)The common algorithms for estimating SOC are described,and the state space equation is established according to the principle of AEKF algorithm.From the analysis of multiple charge and discharge experiments,it can be seen that the battery SOC has different charge and discharge capacities at different temperatures,so it will cause battery SOC estimation errors.Observing the output state equation,polarization voltage will also affect the observation,resulting in errors in the SOC estimation.Therefore,this paper introduces the temperature correction coefficient η＿T to improve the AEKF algorithm,and conducts simulation verification in Matlab/Simulink.The result proves the improved algorithm The estimation error fluctuation range is reduced,and the estimation accuracy of the power battery SOC is further improved.3)Analyze the current main research balance methods and balance topology structures,and compare the advantages and disadvantages of commonly used balance methods and balance topology structures.Based on the principle of flyback converter circuit and inductive balance circuit,this paper proposes neuron algorithm and The PID algorithm is combined to optimize the duty cycle signal of the switching pole in the circuit,so that the equalization circuit can shorten the equalization time.In Matlab/Simulink,the algorithm and balance topology are fused and verified,and the algorithm can improve the balance efficiency of the circuit topology,which has certain guiding significance for further improving the lithium battery energy management system.