The Estimation Of State Of Charge And Battery Management System Design For Lithium Battery

With the continuous reduction of traditional fossil energy storage,clean energy represented by solar energy has been used more.Battery energy storage is the most commonly used method in photovoltaic energy storage technology.The state of charge(SOC)estimation of lithium battery is one of the core functions of the battery management system,which is of great significance for extending battery life and improving battery safety.This paper takes lithium battery as the research object,aiming at the problem of large linear error in estimation of SOC by central differential Kalman filter(CDKF),an improved CDKF algorithm is proposed,which can reduce the linear error effectively.In addition,it also conducts related research on the design of the battery management system.The main contents of this paper are as follows:First of all,this paper summarizes the development status of photovoltaic energy storage technology,the research status of SOC estimation and battery equivalent model,and the shortcomings.On the basis of analyzing the working principle and main performance indicators of the battery,the ARBIN battery charging and discharging test platform is used to complete the discharge characteristics,open circuit voltage,constant current condition and dynamic condition experiments,which provides data resources for subsequent model parameter identification and SOC estimation.Secondly,this paper based on the analysis and comparison of multiple equivalent circuit models,and the characteristics of the voltage change at the end of battery discharge,the second-order RC circuit model is selected as the equivalent model.In this paper,the least square method(including the forgetting factor)is used to identify the resistance and capacitance parameters of the model online,and then the HPPC experiment is performed to verify the accuracy of the model.The equivalent model can be used for the comparison and verification of SOC estimation algorithms in the future.Then,the recursive process of the CDKF algorithm is deduced in detail.In the deduction process,the iterative idea is introduced,the measurement information is used to update the state quantity estimation value,and the covariance matrix is continuously modified based on the Levenberg-Marquardt optimization method.On this basis,an improved CDKF algorithm is proposed.Finally,the accuracy and robustness of the CDKF algorithm and the improved algorithm are verified under constant current and dynamic condition.The results show that the improved CDKF algorithm has higher accuracy,SOC estimation accuracy can be improved by 1.16%,the maximum error is less than 1.7%,and has the better robustness.Finally,a simplified battery management system module was designed.Among them,the microprocessor uses the STM32 chip,the information acquisition module uses the BQ76940 chip,the acquisition module and the microprocessor use the Inter-Integrated Circuit bus for communication,and the control module realizes the charge and discharge management of the battery.The system can complete the monitoring of battery SOC,temperature,voltage and current and display it on the host computer in real time.It also has a variety of fault protection functions.It can meet the requirements of lithium battery information status monitoring.