Research On Estimation Of Battery Health Based On Improved Kalman Filter

As lead-acid batteries(VRLA)continue to be used in industrial applications,the performance of lead-acid batteries must be monitored in real-time to ensure safe and reliable operation as a back-up power source in order to ensure good cell performance and to extend battery life.At present,the domestic and foreign estimates for the performance of the battery mostly reflected the remaining power in the battery(State Of,Charge,SOC),but compared with SOC,the battery health(State Of Health,SOH)research is lagging behind,estimation methods are not mature,the health of the battery(SOH)and battery voltage,current,resistance,temperature,and other electrical parameters are different,it can not be obtained by direct measurement of equipment or instruments,but these electrical parameters with the battery health(SOH)changes.Therefore,accurate on-line estimation of the state of battery health has become a hot topic in current research.In order to solve the above problems,this paper studies the status of battery health and bases on the domestic and foreign.The internal resistance is selected as the main research object of battery health,at the same time the main factors affecting the internal resistance of the experiment showed that the accurate estimation of resistance is the premise of accuracy of residual capacity estimation.The Thevenin is selected as the equivalent circuit model of the battery,and the subsequent algorithm is studied.Then through the research on battery health estimation method,according to the problem of unscented Kalman filter algorithm(UKF),through the optimization of the noise interference and observation interference in the algorithm,a new method based on double adaptive unscented Kalman filter Algorithm,the Thevenin battery equivalent model,on-line estimation of battery residual capacity and internal resistance,thus estimating the battery health,simulation results show that this algorithm has better accuracy on the estimation of battery health online.Finally,under the Windows environment using VC ++ language,through the control of the MFC class library under to build a software test platform,to achieve the UPS backup power of the individual battery health in real-time monitoring.Comparing the simulation and real-time monitoring data of single battery health,and analyzing the results,further verified the accuracy of this algorithm,the proposed algorithm can be applied to the on-line monitoring of individual battery health(SOH)in the industrial control.