Online state of charge estimation of supercapacitor considering uncertain bias compensation

The state of charge(SOC) estimation accuracy of the methods based on equivalent circuit model will decrease due to the existence of uncertain bias such as model error, voltage and current measurement errors. In this paper, a SOC estimation method that considering uncertain bias compensation is proposed to improve the SOC estimation accuracy of supercapacitor(SC) under uncertain bias. The factors that cause estimation error and the impact of bias on estimation result are analyzed. A one-dimensional bias term is added as one of the states to the state space equation of SC for observation. Then, a bias-free Kalman filter(KF) and an uncertain bias estimator are built based on KF algorithm after the decomposition of the expanded estimation algorithm, the estimation results of the two estimators are added together to get the optimal estimation result. Thirdly, the sources of bias are analyzed, and the effectiveness of the proposed method is validated under various operating conditions.