Method for estimating remaining capacity of battery based on threshold extension Kalman algorithm

A method for estimating the remaining capacity of a battery based on a threshold extension Kalman algorithm includes the following steps: 1) using an EKF algorithm to obtain estimated values of respective state variables at a current time, the state variables including remaining battery capacity, first RC link terminal voltage, and second RC link terminal voltage; 2) setting the thresholds of state variables in a state equation in combination with short-term historical current data, and determining whether the estimated values of the state variables exceed respective threshold ranges, and if so, restricting the corresponding state variable to the threshold range. Based on the EKF algorithm, the method add thresholds to state variables in the model by using historical data, restricts the range of state changes, and prevents an decrease in the accuracy of SOC estimation caused by the divergence of state variables, and has better robustness than the existing model-based SOC estimation method. 基于阈值扩展卡尔曼算法的蓄电池剩余电量