Remaining Useful Life Prediction of Supercapacitors Based on DMM-EKF

doi:10.3901/JME.2024.14.306

Abstract

Abstract: Supercapacitor is a new type of electrochemical energy storage device, which has the advantages of long cycle life, high power density and wide working temperature. It has been widely used in rail transit, industrial energy saving and power grid frequency modulation. Accurate evaluation of the state of health and remaining useful life of supercapacitors is very important to optimize the energy storage management system and eliminate potential safety hazards. Therefore, a prediction method based on decay mode matching(DMM) and extended Kalman filter(EKF) is proposed to accurately predict the remaining useful life of supercapacitors. Based on the historical decay database, the Hausdorff distance is used to select the historical decay process that best matches the predicted supercapacitor decay mode, that is, the similar decay process. Based on the dual exponential empirical model, the system model and measurement model for capacitance decay are established. Taking the dual exponential fitting results of similar decay process as the initial parameters, the extended Kalman filter algorithm is used to predict the remaining useful life of supercapacitors. The experimental results show that the proposed method has high prediction accuracy and good robustness, and the cell prediction error is less than 1.4% under two different noises and different working conditions.

Key words: supercapacitors, remaining useful life, extended Kalman filter, dual exponential model, decay mode matching

CLC Number:

TG156

LOU Gongmao, LIN Wenwen, WANG Yuzuo. Remaining Useful Life Prediction of Supercapacitors Based on DMM-EKF[J]. Journal of Mechanical Engineering, 2024, 60(14): 306-316.

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