Fractional‐order modeling and SOC estimation of lithium‐ion battery considering capacity loss
Summary For state‐of‐charge (SOC) estimation, the resistance deterioration and continuous capacity loss can lead to erroneous estimation results. In this paper, an SOC estimator of lithium‐ion battery based on the fractional‐order model and adaptive dual Kalman filtering algorithm is proposed first....
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Published in | International journal of energy research Vol. 43; no. 1; pp. 417 - 429 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Bognor Regis
Hindawi Limited
01.01.2019
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Subjects | |
Online Access | Get full text |
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Summary: | Summary
For state‐of‐charge (SOC) estimation, the resistance deterioration and continuous capacity loss can lead to erroneous estimation results. In this paper, an SOC estimator of lithium‐ion battery based on the fractional‐order model and adaptive dual Kalman filtering algorithm is proposed first. Then, to improve the accuracy of SOC estimation considering capacity loss, the particle filter algorithm is applied to update capacity online in real time. Then, an SOC estimation method is proposed considering battery capacity loss. The simulation results show that the accuracy of battery capacity prediction based on particle filter is high under the condition of capacity loss. |
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ISSN: | 0363-907X 1099-114X |
DOI: | 10.1002/er.4275 |