Yuheng Yin, Lin Wang^*

Energy Engineering, Vol.122, No.7, pp. 2845-2864, 2025, DOI:10.32604/ee.2025.065889 - 27 June 2025

Abstract The accurate estimation of lithium battery state of health (SOH) plays an important role in the health management of battery systems. In order to improve the prediction accuracy of SOH, this paper proposes a stochastic configuration network based on a multi-converged black-winged kite search algorithm, called SBKA-CLSCN. Firstly, the indirect health index (HI) of the battery is extracted by combining it with Person correlation coefficients in the battery charging and discharging cycle point data. Secondly, to address the problem that the black-winged kite optimization algorithm (BKA) falls into the local optimum problem and improve the… More >

Haoran Li^1,2, Yayou Xu³, Zihan Zhang^1,2, Feng Han^1,2, Ye-Tang Pan^2,*, Rongjie Yang²

Journal of Polymer Materials, Vol.42, No.1, pp. 33-55, 2025, DOI:10.32604/jpm.2025.062352 - 27 March 2025

Abstract The thermal stability of lithium-ion battery separators is a critical determinant of battery safety and performance, especially in the context of rapidly expanding applications in electric vehicles and energy storage systems. While traditional polyolefin separators (PP/PE) dominate the market due to their cost-effectiveness and mechanical robustness, their inherent poor thermal stability poses significant safety risks under high-temperature conditions. This review provides a comprehensive analysis of recent advancements in enhancing separator thermal stability through coating materials (metal, ceramic, inorganic) and novel high-temperature-resistant polymers (e.g., PVDF copolymers, PI, PAN). Notably, we critically evaluate the trade-offs between thermal… More >

Yuheng Yin, Jiahao Song^*, Minghui Yang

Energy Engineering, Vol.122, No.2, pp. 709-731, 2025, DOI:10.32604/ee.2024.059021 - 31 January 2025

Abstract The lithium battery is an essential component of electric cars; prompt and accurate problem detection is vital in guaranteeing electric cars’ safe and dependable functioning and addressing the limitations of Back Propagation (BP) neural networks in terms of vanishing gradients and inability to effectively capture dependencies in time series, and the limitations of Long-Short Term Memory (LSTM) neural network models in terms of risk of overfitting. A method based on LSTM-BP is put forward for power battery fault diagnosis to improve the accuracy of lithium battery fault diagnosis. First, a lithium battery model is constructed… More > Graphic Abstract

Min Deng¹, Quan Min¹, Ge Yang¹, Man Yu^2,3,*

Energy Engineering, Vol.119, No.2, pp. 739-754, 2022, DOI:10.32604/ee.2022.018025 - 24 January 2022

Abstract High-precision estimation of lithium battery SOC can effectively optimize vehicle energy management, improve lithium battery safety protection, extend lithium battery cycle life, and reduce new energy vehicle costs. Based on the forgetting factor recursive least square method (FFRLS), Thevenin equivalent circuit model and Singular Value Decomposition-Unscented Kalman Filter (SVD-UKF), the SVD-UKF combined lithium battery SOC estimation algorithm with model capacity update is proposed, aiming at further improving the SOC estimation accuracy of lithium battery. The parameter identification of Thevenin model is studied by using the forgetting factor recursive least square method. To overcoming the shortcomings… More >