Research on SOC Estimation Method for Lithium-Ion Batteries Based on Neural Network
Abstract
:1. Introduction
2. Study of SOC Estimation Method
2.1. Lithium-Ion Battery Working Principle
2.2. SOC Estimation Based on BP Algorithm
2.2.1. Model Building
2.2.2. Model Simulation
2.3. SOC Estimation Based on PSO-BP Algorithm
2.3.1. Model Building
2.3.2. Model Simulation
2.4. SOC Estimation Based on LSTM Algorithm
2.4.1. Principle of LSTM Algorithm
- (1)
- LSTM forward calculation process
- (2)
- LSTM reverse calculation process
2.4.2. Model Building
2.4.3. Model Simulation
3. Contrast and Analysis
4. SOC Estimation Based on PSO-LSTM Algorithm
4.1. Principle of PSO-LSTM Model
4.2. Model Building
4.3. Model Simulation
4.4. Analysis of the Results of LSTM and PSO-LSTM for DST Condition
4.5. Analysis of the Results of LSTM and PSO-LSTM for US06 Condition
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Type | Nominal Voltage | Nominal Capacity | Upper/Lower Cut-Off Voltage | Nominal Continuous Discharge Current |
---|---|---|---|---|
18650 | 3.7 V | 2200 mAh | 4.20 V/2.75 V | 0.2 C |
Model | RMSE | MAE | ME |
---|---|---|---|
BP | 0.0545 | 0.0386 | 0.0457 |
PSO-BP | 0.0432 | 0.0218 | 0.0265 |
LSTM | 0.0350 | 0.0162 | 0.0184 |
PSO-LSTM | 0.0115 | 0.0112 | 0.0147 |
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Zhang, C.; Xu, X.; Li, Y.; Huang, J.; Li, C.; Sun, W. Research on SOC Estimation Method for Lithium-Ion Batteries Based on Neural Network. World Electr. Veh. J. 2023, 14, 275. https://doi.org/10.3390/wevj14100275
Zhang C, Xu X, Li Y, Huang J, Li C, Sun W. Research on SOC Estimation Method for Lithium-Ion Batteries Based on Neural Network. World Electric Vehicle Journal. 2023; 14(10):275. https://doi.org/10.3390/wevj14100275
Chicago/Turabian StyleZhang, Chuanwei, Xusheng Xu, Yikun Li, Jing Huang, Chenxi Li, and Weixin Sun. 2023. "Research on SOC Estimation Method for Lithium-Ion Batteries Based on Neural Network" World Electric Vehicle Journal 14, no. 10: 275. https://doi.org/10.3390/wevj14100275