Affiliation:
1. College of Engineering, Huaqiao University, Quanzhou 362021, China
2. Business School, Huaqiao University, Quanzhou 362021, China
Abstract
Lead–acid batteries are widely used, and their health status estimation is very important. To address the issues of low fitting accuracy and inaccurate prediction of traditional lead–acid battery health estimation, a battery health estimation model is proposed that relies on charging curve analysis using historical degradation data. This model does not require the assistance of battery mechanism models or empirical degradation models, instead, it is combined with improved deep learning algorithms. A long short-term memory (LSTM) regression model was established, and parameter optimization was performed using the bat algorithm (BA). The experimental results show that the proposed model can achieve an accurate capacity estimation of lead–acid batteries.
Funder
Quanzhou Huawei Guowei Electronic Technology Co., Ltd.
Science and Technology Project of Xiamen City
The Young and Middle-aged Teachers Education Scientific Research Project of Fujian Province, China
Foundation of Huaqiao University
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering
Reference19 articles.
1. Yang, N., Feng, J., Sun, Q., Liu, T., and Zhong, D. (2016, January 26–28). Online estimation of state-of-health for lithium ion batteries based on charge curves. Proceedings of the 2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS), Hangzhou, China.
2. Review on state of health estimation methodologies for lithium-ion batteries in the context of circular economy;Basia;CIRP J. Manuf. Sci. Technol.,2021
3. A review on the state of health estimation methods of lead-acid batteries;Jiang;J. Power Sources,2022
4. Zhen, L., Zang, X., Ye, B., Zhang, X., Li, F., Zhou, C., Xu, X., Jiang, B., and Chen, X. (2018, January 6–9). A novel comprehensive evaluation method for state-of-health of lead-acid batteries. Proceedings of the 2018 International Conference on Power System Technology (POWERCON), Guangzhou, China.
5. Equivalent circuit model and parameter identification of VRLA batteries;Zhang;Chin. J. Power Sources,2017