Research On SOC Estimation Of VRLA Battery Based On Fuzzy Dual Kalman Filter Algorithm

The large-scale development of clean and renewable energy,led by solar and wind energy,can effectively solve the environmental problems caused by fossil energy.However,their inherent uncertainty and intermittency restrict their wide application,and the use of energy storage systems can make up for this deficiency.For storage batteries,state of charge(SOC)is one of its core parameters.Accurate estimation of SOC has direct influence on the performance of batteries,and it mainly depends on estimation algorithms.In this paper,a valve-regulated lead-acid(VRLA)battery is selected as the research object to study SOC estimation,on the purpose of improving SOC estimation accuracy.Basic structures,working principles,main technical parameters,and performance characteristics of VRLA battery are analyzed,and SOC estimation methods are studied in depth.After extended Kalman filter(EKF)algorithm is selected as the main subject,a SOC estimation method based on fuzzy dual Kalman filter(FDKF)algorithm is proposed.On the one hand,in order to reflect the dynamic changes of the model parameters,an online parameter identification method based on KF(Kalman Filter,KF)algorithm was introduced: the first-order RC equivalent circuit was converted into an autoregressive exogenous(ARX)model by using mathematical methods,and then the parameters of the model were identified by using KF algorithm.The simulation results show that: online parameter identification method based on KF algorithm can reflect the dynamic change of model parameters.and provides a more accurate model for the battery SOC estimation under complex working conditions.On the other hand,in order to improve the accuracy of SOC estimation further,on the basis of the high-precision model obtained by online parameter identification method based on KF algorithm,EKF algorithm was used to estimate battery SOC,fuzzy algorithm was introduced,and the observation noise covariance of EKF was updated by the fuzzy controller to compensate the impact from model error under complex working conditions.The simulation results show that: SOC estimation method based on FDKF algorithm improves the accuracy of SOC estimation obviously.Finally,a SOC estimation experimental platform was built for the battery SOC estimation function,related hardware and software were designed,and the designed platform was tested.The test results show that the SOC estimation method based on FDKF algorithm improves the accuracy of SOC estimation and has a high application value.