2022
DOI: 10.1149/1945-7111/acadaa
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The State of Charge Estimation of Lithium-Ion Battery Based on Battery Capacity

Abstract: In order to improve the estimation level of lithium batteries and promote the accurate control of the battery management system, accurate state of charge (SOC) estimation is very important. The CNN algorithm and the two-dimensional CNN (2DCNN) algorithm have been studied in the SOC estimation, but it is a technical difficulty to apply the three-dimensional CNN (3DCNN) algorithm to the SOC estimation. This paper firstly designs two-dimensional and three-dimensional datasets to describe the aging degree and SOC.… Show more

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Cited by 8 publications
(8 citation statements)
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“…To validate the performance of our proposed model, we compared its results with those of other battery SOC estimation studies [36,37] that used data from Battery #5 in the NASA dataset. Zhang et al [36] proposed an SOH-SOC simultaneous estimation model based on the GWO-BP neural network.…”
Section: Experiments and Resultsmentioning
confidence: 99%
“…To validate the performance of our proposed model, we compared its results with those of other battery SOC estimation studies [36,37] that used data from Battery #5 in the NASA dataset. Zhang et al [36] proposed an SOH-SOC simultaneous estimation model based on the GWO-BP neural network.…”
Section: Experiments and Resultsmentioning
confidence: 99%
“…On the other hand, compared with the traditional unidirectional LSTM, the Bi-LSTM neural network [6]…”
Section: Bi-lstm Neural Networkmentioning
confidence: 99%
“…For example, references [18,19] adopted a GRU for SOC estimation, Ref. [20] used an LSTM network and [21,22] derived a method based on CNNs. In addition to using single neural networks for SOC estimation, some studies have proposed combining different neural network models.…”
Section: Introductionmentioning
confidence: 99%