ANN approach to SOC estimation of Lithium-Ion Battery

被引:0
|
作者
Imane, Chaoufi [1 ,2 ]
Fatiha, Zaghrat [1 ,2 ]
Asma, Benehmine [1 ]
Othmane, Abdelkhalek [1 ]
Brahim, Gasbaoui [1 ]
机构
[1] TAHRI Mohamed Univ, Elect Engn Dept, Bechar, Algeria
[2] TAHRI Mohamed Univ, Fac Technol, Smart Grids & Renewable Energies Lab SGRE, Bechar, Algeria
来源
PRZEGLAD ELEKTROTECHNICZNY | 2024年 / 100卷 / 08期
关键词
Electric Vehicle; State of Charge; Open Circuit Voltage; ANN; MODELS;
D O I
10.15199/48.2024.08.41
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
State-of-charge, or SOC, is an electric vehicle's battery pack's analogue of a gasoline gauge. It becomes crucial to ascertain the status of charge in all battery applications, including electric cars (EVs). This paper's goal is to use an artificial neural network (ANN) to estimate the state of charge (SOC) of a high capacity lithium-ion battery (LIB). This is necessary since SOC cannot be measured directly; instead, it must be calculated using measurable battery metrics like temperature, voltage, and current. It is possible to obtain an accurate predictive model that can predict the SOC in the near future. The simulated data set and the ANN model agreed, indicating the model's strong performance.
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页码:198 / 200
页数:3
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