Study of SOC Estimation by the Ampere-Hour Integral Method with Capacity Correction Based on LSTM
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 co...
Main Authors: | , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-10-01
|
Series: | Batteries |
Subjects: | |
Online Access: | https://www.mdpi.com/2313-0105/8/10/170 |
_version_ | 1797475263929384960 |
---|---|
author | Xin Zhang Jiawei Hou Zekun Wang Yueqiu Jiang |
author_facet | Xin Zhang Jiawei Hou Zekun Wang Yueqiu Jiang |
author_sort | Xin Zhang |
collection | DOAJ |
description | 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. |
first_indexed | 2024-03-09T20:41:41Z |
format | Article |
id | doaj.art-3c3973e69c1949658f655c53b8aaed0c |
institution | Directory Open Access Journal |
issn | 2313-0105 |
language | English |
last_indexed | 2024-03-09T20:41:41Z |
publishDate | 2022-10-01 |
publisher | MDPI AG |
record_format | Article |
series | Batteries |
spelling | doaj.art-3c3973e69c1949658f655c53b8aaed0c2023-11-23T22:55:16ZengMDPI AGBatteries2313-01052022-10-0181017010.3390/batteries8100170Study of SOC Estimation by the Ampere-Hour Integral Method with Capacity Correction Based on LSTMXin Zhang0Jiawei Hou1Zekun Wang2Yueqiu Jiang3School of Automobile and Traffic, Shenyang Ligong University, Shenyang 110159, ChinaSchool of Automobile and Traffic, Shenyang Ligong University, Shenyang 110159, ChinaSchool of Automobile and Traffic, Shenyang Ligong University, Shenyang 110159, ChinaSchool of Information Science and Engineering, Shenyang Ligong University, Shenyang 110159, ChinaThe 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.https://www.mdpi.com/2313-0105/8/10/170SOC estimationLSTMampere-hour integral method |
spellingShingle | Xin Zhang Jiawei Hou Zekun Wang Yueqiu Jiang Study of SOC Estimation by the Ampere-Hour Integral Method with Capacity Correction Based on LSTM Batteries SOC estimation LSTM ampere-hour integral method |
title | Study of SOC Estimation by the Ampere-Hour Integral Method with Capacity Correction Based on LSTM |
title_full | Study of SOC Estimation by the Ampere-Hour Integral Method with Capacity Correction Based on LSTM |
title_fullStr | Study of SOC Estimation by the Ampere-Hour Integral Method with Capacity Correction Based on LSTM |
title_full_unstemmed | Study of SOC Estimation by the Ampere-Hour Integral Method with Capacity Correction Based on LSTM |
title_short | Study of SOC Estimation by the Ampere-Hour Integral Method with Capacity Correction Based on LSTM |
title_sort | study of soc estimation by the ampere hour integral method with capacity correction based on lstm |
topic | SOC estimation LSTM ampere-hour integral method |
url | https://www.mdpi.com/2313-0105/8/10/170 |
work_keys_str_mv | AT xinzhang studyofsocestimationbytheamperehourintegralmethodwithcapacitycorrectionbasedonlstm AT jiaweihou studyofsocestimationbytheamperehourintegralmethodwithcapacitycorrectionbasedonlstm AT zekunwang studyofsocestimationbytheamperehourintegralmethodwithcapacitycorrectionbasedonlstm AT yueqiujiang studyofsocestimationbytheamperehourintegralmethodwithcapacitycorrectionbasedonlstm |