Research On Algorithm Of SOC Estimation In Lithium-ion Battery And The Simulation Of Hardware-in-the-loop

Since the beginning of the 21 st century,with people’s attention to the environmental protection and the reduction of fossil energy,the use of renewable energy and relatively environmental friendly electric vehicles have developed rapidly.As the most important parameter of the battery management system(BMS),the state of charge(SOC)of the battery plays a key role in ensuring the safety of the battery.How to improve the online estimation accuracy of the SOC has become the most important task of the BMS.In this paper,the SOC estimation of ternary lithium-ion battery is taken as the research object,and the SOC estimation algorithm and its hardware-in-the-loop(HIL)simulation are studied.Firstly,analyze the commonly used battery simulation models,establish a2 RC equivalent circuit model,and calibrate the relationship between the open circuit voltage(OCV)and SOC of the battery.Then,the parameters of the battery model are identified based on the least square method with forgetting factor,and finally the accuracy of the parameterized model is simulated and analyzed in MATLAB.The results show that the established battery model can adapt to a variety of working conditions,the simulation voltage errors are all within 40 m V,and the accuracy meets the requirements.Secondly,it analyzes various commonly used SOC estimation algorithms,and chooses the extended kalman filter algorithm and the unscented kalman filter algorithm to estimate the battery SOC.After analyzing the factors that affect the estimation accuracy,the parameters Q and R are optimized based on genetic algorithm(GA)and particle swarm optimization(PSO),and the results before and after optimization are compared and analyzed.Then the model-in-the-Loop(MIL)simulation experiment of SOC estimation under a variety of cycle conditions shows that the SOC estimation method based on particle swarm optimization parameters has strong robustness.The estimation effect is good,the error is within 3%,and the optimized unscented kalman filter algorithm has higher accuracy in estimating SOC.Finally,the ECU underlying operating system is configured based on the D2P(From Development to Production,D2P)rapid prototyping platform,and the SOC estimation algorithm model built in MATLAB/Simulink is compiled and written into the ECU.Then combined with NI Veri Stand and NI PXI to build a hardware-in-the-loop simulation system to perform HIL simulation of the SOC estimation algorithm.The results show that the SOC estimation accuracy of HIL simulation is slightly lower than that of MIL simulation,but the estimation error is still within 3%,which proves the effectiveness and accuracy of the built SOC estimation algorithm in the hardware-in-the-loop system.