State of Charge Estimation for Lithium Battery in Shipboard DC Power Grid Based on Differential Evolutionary Algorithm
More and more attention has been paid to ships with a DC power grid. State-of-charge (SOC) estimation is a pivotal and challenging assignment for lithium-ion batteries in such ships. However, the precision of SOC estimation is strongly connected with the system parameters. To better identify these p...
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MDPI AG
2025-01-01
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| Series: | Journal of Marine Science and Engineering |
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| Online Access: | https://www.mdpi.com/2077-1312/13/1/126 |
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| author | Yanbiao Li Jundong Zhang Zunlei Duan Chuan Wang |
| author_facet | Yanbiao Li Jundong Zhang Zunlei Duan Chuan Wang |
| author_sort | Yanbiao Li |
| collection | DOAJ |
| description | More and more attention has been paid to ships with a DC power grid. State-of-charge (SOC) estimation is a pivotal and challenging assignment for lithium-ion batteries in such ships. However, the precision of SOC estimation is strongly connected with the system parameters. To better identify these parameters in lithium-ion batteries, a differential evolution (DE) algorithm was introduced into this paper as the optimizer. Initially, a first-order RC equivalent circuit model (ECM) was created to characterize the battery’s dynamic behavior. Following this, to estimate open-circuit voltage (OCV) throughout the entire dynamic process, a math model of optimization was established to minimize inaccuracies between the real and estimated terminal voltages. Moreover, estimated SOC values were obtained through OCV-SOC mappings and were contrasted against the true SOC values. The findings manifested the efficacy of the presented structure and technique in comparison with various frequently-cited DE variants. |
| format | Article |
| id | doaj-art-68223a9ef9724a2093e81a194c7b3a09 |
| institution | Kabale University |
| issn | 2077-1312 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
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| series | Journal of Marine Science and Engineering |
| spelling | doaj-art-68223a9ef9724a2093e81a194c7b3a092025-01-24T13:36:56ZengMDPI AGJournal of Marine Science and Engineering2077-13122025-01-0113112610.3390/jmse13010126State of Charge Estimation for Lithium Battery in Shipboard DC Power Grid Based on Differential Evolutionary AlgorithmYanbiao Li0Jundong Zhang1Zunlei Duan2Chuan Wang3College of Marine Engineering, Dalian Maritime University, Dalian 116026, ChinaCollege of Marine Engineering, Dalian Maritime University, Dalian 116026, ChinaAcademic Journal Center, Dalian Maritime University, Dalian 116026, ChinaCollege of Marine Engineering, Dalian Maritime University, Dalian 116026, ChinaMore and more attention has been paid to ships with a DC power grid. State-of-charge (SOC) estimation is a pivotal and challenging assignment for lithium-ion batteries in such ships. However, the precision of SOC estimation is strongly connected with the system parameters. To better identify these parameters in lithium-ion batteries, a differential evolution (DE) algorithm was introduced into this paper as the optimizer. Initially, a first-order RC equivalent circuit model (ECM) was created to characterize the battery’s dynamic behavior. Following this, to estimate open-circuit voltage (OCV) throughout the entire dynamic process, a math model of optimization was established to minimize inaccuracies between the real and estimated terminal voltages. Moreover, estimated SOC values were obtained through OCV-SOC mappings and were contrasted against the true SOC values. The findings manifested the efficacy of the presented structure and technique in comparison with various frequently-cited DE variants.https://www.mdpi.com/2077-1312/13/1/126SOC estimationshipboard DC griddifferential evolutionoptimization problemlithium-ion battery |
| spellingShingle | Yanbiao Li Jundong Zhang Zunlei Duan Chuan Wang State of Charge Estimation for Lithium Battery in Shipboard DC Power Grid Based on Differential Evolutionary Algorithm Journal of Marine Science and Engineering SOC estimation shipboard DC grid differential evolution optimization problem lithium-ion battery |
| title | State of Charge Estimation for Lithium Battery in Shipboard DC Power Grid Based on Differential Evolutionary Algorithm |
| title_full | State of Charge Estimation for Lithium Battery in Shipboard DC Power Grid Based on Differential Evolutionary Algorithm |
| title_fullStr | State of Charge Estimation for Lithium Battery in Shipboard DC Power Grid Based on Differential Evolutionary Algorithm |
| title_full_unstemmed | State of Charge Estimation for Lithium Battery in Shipboard DC Power Grid Based on Differential Evolutionary Algorithm |
| title_short | State of Charge Estimation for Lithium Battery in Shipboard DC Power Grid Based on Differential Evolutionary Algorithm |
| title_sort | state of charge estimation for lithium battery in shipboard dc power grid based on differential evolutionary algorithm |
| topic | SOC estimation shipboard DC grid differential evolution optimization problem lithium-ion battery |
| url | https://www.mdpi.com/2077-1312/13/1/126 |
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