Lithium-Ion Battery Capacity Estimation Based on Incremental Capacity Analysis and Deep Convolutional Neural Network

Accurate estimation of Li-ion battery capacity is critical for a battery management system (BMS). This paper proposes an innovative method which combines a convolutional neural network and incremental capacity analysis (ICA). In the present approach, the voltage and temperature, which significantly...

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Main Authors: Sibo Zeng, Sheng Chen, Babakalli Alkali
Format: Article
Language:English
Published: MDPI AG 2024-03-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/17/6/1272
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author Sibo Zeng
Sheng Chen
Babakalli Alkali
author_facet Sibo Zeng
Sheng Chen
Babakalli Alkali
author_sort Sibo Zeng
collection DOAJ
description Accurate estimation of Li-ion battery capacity is critical for a battery management system (BMS). This paper proposes an innovative method which combines a convolutional neural network and incremental capacity analysis (ICA). In the present approach, the voltage and temperature, which significantly affect the ICA curve during the discharging process, are adopted as the inputs for CNN. Rather than extracting feature parameters of an IC curve, as is carried out in the available research, the present method uses the whole ICA curve as the input to avoid complicated feature extraction and correlation analysis. The results show that the maximum error of capacity estimation is less than 4.7%, the rectified mean squared error is less than 1.3% for each battery, and the overall RMSE is below 1.12%.
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spelling doaj.art-aea2d610a16947eabb4be1d96ac4a07c2024-03-27T13:35:18ZengMDPI AGEnergies1996-10732024-03-01176127210.3390/en17061272Lithium-Ion Battery Capacity Estimation Based on Incremental Capacity Analysis and Deep Convolutional Neural NetworkSibo Zeng0Sheng Chen1Babakalli Alkali2Zhuzhou CRRC Times Electric Co., Ltd., Zhuzhou 412001, ChinaSchool of Computing, Engineering and Built Environment, Glasgow Caledonian University, Glasgow G4 0BA, UKSchool of Computing, Engineering and Built Environment, Glasgow Caledonian University, Glasgow G4 0BA, UKAccurate estimation of Li-ion battery capacity is critical for a battery management system (BMS). This paper proposes an innovative method which combines a convolutional neural network and incremental capacity analysis (ICA). In the present approach, the voltage and temperature, which significantly affect the ICA curve during the discharging process, are adopted as the inputs for CNN. Rather than extracting feature parameters of an IC curve, as is carried out in the available research, the present method uses the whole ICA curve as the input to avoid complicated feature extraction and correlation analysis. The results show that the maximum error of capacity estimation is less than 4.7%, the rectified mean squared error is less than 1.3% for each battery, and the overall RMSE is below 1.12%.https://www.mdpi.com/1996-1073/17/6/1272lithium-ion batterycapacity estimationincremental capacity analysisgaussian regressionconvolutional neural network
spellingShingle Sibo Zeng
Sheng Chen
Babakalli Alkali
Lithium-Ion Battery Capacity Estimation Based on Incremental Capacity Analysis and Deep Convolutional Neural Network
Energies
lithium-ion battery
capacity estimation
incremental capacity analysis
gaussian regression
convolutional neural network
title Lithium-Ion Battery Capacity Estimation Based on Incremental Capacity Analysis and Deep Convolutional Neural Network
title_full Lithium-Ion Battery Capacity Estimation Based on Incremental Capacity Analysis and Deep Convolutional Neural Network
title_fullStr Lithium-Ion Battery Capacity Estimation Based on Incremental Capacity Analysis and Deep Convolutional Neural Network
title_full_unstemmed Lithium-Ion Battery Capacity Estimation Based on Incremental Capacity Analysis and Deep Convolutional Neural Network
title_short Lithium-Ion Battery Capacity Estimation Based on Incremental Capacity Analysis and Deep Convolutional Neural Network
title_sort lithium ion battery capacity estimation based on incremental capacity analysis and deep convolutional neural network
topic lithium-ion battery
capacity estimation
incremental capacity analysis
gaussian regression
convolutional neural network
url https://www.mdpi.com/1996-1073/17/6/1272
work_keys_str_mv AT sibozeng lithiumionbatterycapacityestimationbasedonincrementalcapacityanalysisanddeepconvolutionalneuralnetwork
AT shengchen lithiumionbatterycapacityestimationbasedonincrementalcapacityanalysisanddeepconvolutionalneuralnetwork
AT babakallialkali lithiumionbatterycapacityestimationbasedonincrementalcapacityanalysisanddeepconvolutionalneuralnetwork