High Precision State of Health Estimation of Lithium-ion Batteries Based on PSO-LSSVM AdaBoost Model

• Published in: 2024 IEEE 25th China Conference on System Simulation Technology and its Application (CCSSTA) pp. 570 - 574
• Main Authors: Feng, Renjun, Wang, Shunli, Yu, Chunmei, Cui, Yixiu, Zhou, Yifei
• Format: Conference Proceeding
• Language: English
• Published: IEEE 21.07.2024
• Subjects: Adaboost algorithm; Battery management systems; Estimation; Feature extraction; health features; Kernel; least squares support vector machine; Lithium-ion batteries; NASA; Particle swarm optimization; Prediction algorithms; Predictive models; state of health; Support vector machines

The accurate estimation of the state of health (SOH) of lithium-ion batteries is paramount for the maintenance and longevity of battery management systems (BMS). To enhance the precision and robustness of SOH prediction models for lithium-ion batteries, this article introduces a novel approach that...