An Improved Gated Recurrent Unit Neural Network for State-of-Charge Estimation of Lithium-Ion Battery
Open accessAbstract
State-of-charge (SOC) estimation of lithium-ion battery is a key parameter of the battery management system (BMS). However, SOC cannot be obtained directly. In order to predict SOC accurately, we proposed a recurrent neural network called gated recurrent unit network that is based on genetic algorithm (GA-GRU) in this paper. GA was introduced to optimize the key parameters of the model, which can improve the performance of the proposed network. Furthermore, batteries were tested under four dynamic driving conditions at five temperatures to establish training and testing datasets. Finally, the proposed method was validated on dynamic driving conditions and compared with other deep learning methods. The results show that the proposed method can achieve high accuracy and robustness.
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Chen et al. applied genetic algorithms to optimize GRU hyperparameters, achieving an RMSE of 0.07%.
“Chen et al. applied genetic algorithms to optimize GRU hyperparameters, achieving an impressive RMSE of 0.07%[81].”
From Advancements in the estimation of the state of charge of lithium-ion battery: a comprehensive review of traditional and deep learning approaches (2025) · cites this paper as [81]
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- Authors
- Chen, J., Lu, C., Chen, C., Cheng, H., & Xuan, D.
- Affiliations
- Wenzhou University (CN)
- Corresponding author
- Xuan, Dongji
- Venue
- Applied Sciences
- Publisher
- MDPI AG
- Published
- 2022-02-22
- Volume
- 12
- Issue
- 5
- Pages
- 2305
- ISSN
- 2076-3417 (ISSN-L)
- OpenAlex
- W4213385733
- Cited by
- 42
- References
- 28
- Citations by year
- 2026: 7 · 2025: 13 · 2024: 7 · 2023: 12 · 2022: 3
- FWCI
- 2.39
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Applied Sciences (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Dongji Xuan (2018ZG007)
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Advanced Battery Technologies Research
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advancements in Battery Materials
- Physical Sciences › Engineering › Control and Systems Engineering › Control Systems and Identification
- Keywords
- state of charge estimation, lithium-ion batteries, gated recurrent unit, genetic algorithm parameter optimization, battery management systems, temperature effects, deep learning
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