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- W4303943885 abstract "The estimation of the state of charge (SOC) of a battery’s power is one of the key technologies in a battery management system (BMS). As a common SOC estimation method, the traditional ampere-hour integral method regards the actual capacity of the battery, which is constantly changed by the usage conditions and environment, as a constant for calculation, which may cause errors in the results of SOC estimation. Considering the above problems, this paper proposes an improved ampere-hour integral method based on the Long Short-Term Memory (LSTM) network model. The LSTM network model is used to obtain the actual battery capacity variation, replacing the fixed value of battery capacity in the traditional ampere-hour integral method and optimizing the traditional ampere-hour integral method to improve the accuracy of the SOC estimation method. The experimental results show that the errors of the results obtained by the improved ampere-hour integral method for the SOC estimation are all less than 10%, which proves that the proposed design method is feasible and effective." @default.
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- W4303943885 date "2022-10-09" @default.
- W4303943885 modified "2023-10-10" @default.
- W4303943885 title "Study of SOC Estimation by the Ampere-Hour Integral Method with Capacity Correction Based on LSTM" @default.
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- W4303943885 doi "https://doi.org/10.3390/batteries8100170" @default.
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