A Review on Battery Model-Based and Data-Driven Methods for Battery Management Systems
Battery state estimation is fundamental to battery management systems (BMSs). An accurate model is needed to describe the dynamic behavior of the battery to evaluate the fundamental quantities, such as the state of charge (SOC) or the state of health (SOH). This paper presents an overview of the mos...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-11-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/16/23/7807 |
| _version_ | 1827592297114501120 |
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| author | Valentina Lucaferri Michele Quercio Antonino Laudani Francesco Riganti Fulginei |
| author_facet | Valentina Lucaferri Michele Quercio Antonino Laudani Francesco Riganti Fulginei |
| author_sort | Valentina Lucaferri |
| collection | DOAJ |
| description | Battery state estimation is fundamental to battery management systems (BMSs). An accurate model is needed to describe the dynamic behavior of the battery to evaluate the fundamental quantities, such as the state of charge (SOC) or the state of health (SOH). This paper presents an overview of the most commonly used battery models, the equivalent electrical circuits, and data-driven ones, discussing the importance of battery modeling and the various approaches used to model lithium batteries. In particular, it provides a detailed analysis of the electrical circuit models commonly used for lithium batteries, including equivalent circuit and thermal models. Furthermore, a comprehensive overview of data-driven approaches is presented. The advantages and limitations of each type of model are discussed. Finally, the paper concludes with a discussion of current research trends and future directions in the field of battery modeling. |
| first_indexed | 2024-03-09T01:51:36Z |
| format | Article |
| id | doaj.art-30aa25bb81b648eab55d7d15e0ebad54 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-09T01:51:36Z |
| publishDate | 2023-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-30aa25bb81b648eab55d7d15e0ebad542023-12-08T15:14:53ZengMDPI AGEnergies1996-10732023-11-011623780710.3390/en16237807A Review on Battery Model-Based and Data-Driven Methods for Battery Management SystemsValentina Lucaferri0Michele Quercio1Antonino Laudani2Francesco Riganti Fulginei3Department of Industrial Engineering, Electronics and Mechanics, Roma Tre University, Via Vito Volterra 62, 00146 Rome, ItalyDepartment of Industrial Engineering, Electronics and Mechanics, Roma Tre University, Via Vito Volterra 62, 00146 Rome, ItalyDepartment of Electrical, Electronic and Computer Engineering (DIEEI), University of Catania, Viale Andrea Doria 6, 95125 Catania, ItalyDepartment of Industrial Engineering, Electronics and Mechanics, Roma Tre University, Via Vito Volterra 62, 00146 Rome, ItalyBattery state estimation is fundamental to battery management systems (BMSs). An accurate model is needed to describe the dynamic behavior of the battery to evaluate the fundamental quantities, such as the state of charge (SOC) or the state of health (SOH). This paper presents an overview of the most commonly used battery models, the equivalent electrical circuits, and data-driven ones, discussing the importance of battery modeling and the various approaches used to model lithium batteries. In particular, it provides a detailed analysis of the electrical circuit models commonly used for lithium batteries, including equivalent circuit and thermal models. Furthermore, a comprehensive overview of data-driven approaches is presented. The advantages and limitations of each type of model are discussed. Finally, the paper concludes with a discussion of current research trends and future directions in the field of battery modeling.https://www.mdpi.com/1996-1073/16/23/7807equivalent circuit battery modelsbattery management systemsLi-ion battery |
| spellingShingle | Valentina Lucaferri Michele Quercio Antonino Laudani Francesco Riganti Fulginei A Review on Battery Model-Based and Data-Driven Methods for Battery Management Systems Energies equivalent circuit battery models battery management systems Li-ion battery |
| title | A Review on Battery Model-Based and Data-Driven Methods for Battery Management Systems |
| title_full | A Review on Battery Model-Based and Data-Driven Methods for Battery Management Systems |
| title_fullStr | A Review on Battery Model-Based and Data-Driven Methods for Battery Management Systems |
| title_full_unstemmed | A Review on Battery Model-Based and Data-Driven Methods for Battery Management Systems |
| title_short | A Review on Battery Model-Based and Data-Driven Methods for Battery Management Systems |
| title_sort | review on battery model based and data driven methods for battery management systems |
| topic | equivalent circuit battery models battery management systems Li-ion battery |
| url | https://www.mdpi.com/1996-1073/16/23/7807 |
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