Performance Evaluation And State Estimation Of Vanadium Redox Flow Battery System

The volatility,intermittency and dispersion of renewable new energy power such as solar energy and wind energy seriously restrict their wide application.The renewable energy power generation system can be transformed into sustainable and stable high-quality energy by equipping it with an appropriate capacity of energy storage system.Compared with other energy storage methods,Vanadium Redox Battery(VRB)is an important development direction of new energy generation and energy storage system in the future because of its advantages of low cost,simple structure,high safety and long cycle life.Battery Management System(BMS)is the guarantee of safe and reliable operation of batteries.The core of BMS is to accurately estimate the state of charge(SOC)of batteries.In this paper,based on a research project,Temasek Polytecnic,the SOC estimation method of a kilowatt-class VRB with 20 single batteries in series is studied.The main work and achievements of this paper are as follows:Design and construction of battery charging and discharging experimental system platform.The experimental data acquisition system based on LabVIEW and DSPIC30F6012 A microcontroller is designed.The acquisition voltage,current and temperature data are processed by the MCU and transmitted to the computer for storage for analysis and display.The user interface can display the change in physical quantity and the abnormal state of the stack.Charge and discharge characteristic of VRB.The effects of temperature,vanadium ion concentration and current density on the efficiency and capacity of the battery are studied and analyzed according to the test data.Secondly,the temperature distribution during the operation of the battery is analyzed.Data analysis shows that the efficiency and capacity of the test battery are in normal state,and the performance is stable.Modeling and parameter identification of VRB.The advantages and disadvantages of four equivalent circuit models of VRB are analyzed and compared.The Thevenin equivalent circuit model of the second-order RC with clear physical meaning is selected as the equivalent circuit model of VRB.The dynamic parameters of the battery are obtained by HPPC experiment on the test platform.Based on the parameters,the simulation circuit model of MATLAB/Simulink is established,which verifies the accuracy of the parameters and the model,and lays the foundation for parameters estimation in the following chapters.Research and analysis of estimation algorithm for SOC.Using the dynamic parameters and the equivalent circuit model,the Extended Kalman Filter Algorithm and Strong Tracking Extended Kalman Filter Algorithm are used to predict the state of VRB.The results show that both algorithms can track accurately;Compared with the Extended Kalman Filter,the strong tracking Kalman filter can also converge quickly if the initial value is not accurate.The realtime estimation of the SOC during the operation of the battery is carried out through the experimental platform.The results show that the test platform has good accuracy for data acquisition,intuitive and convenient use,efficiency and capacity of the test battery are in good condition,the model and parameter identification results are reliable and accurate,and the strong tracking Extended Kalman Filter Algorithm can converge quickly and has high accuracy.