A Robust and Efficient State-of-Charge Estimation Methodology for Serial-Connected Battery Packs: Most Significant Cell Methodology
Safely and efficiently managing a battery pack consisting of hundreds to thousands of battery cells is a critical but challenging task due to commonly observed uncertainties, e.g. temperature, battery degradation and SOC estimation inaccuracy. This paper proposes a robust and efficient most signific...
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2021-01-01
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| Online Access: | https://ieeexplore.ieee.org/document/9433556/ |
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doaj-59093aa2fdcd4ca5a17eb4e89d4c302b2021-06-02T23:17:50ZengIEEEIEEE Access2169-35362021-01-019743607436910.1109/ACCESS.2021.30816199433556A Robust and Efficient State-of-Charge Estimation Methodology for Serial-Connected Battery Packs: Most Significant Cell MethodologyCong-Sheng Huang0https://orcid.org/0000-0002-1304-5721Zheyuan Cheng1https://orcid.org/0000-0002-6907-4062Mo-Yuen Chow2Department of Electrical and Computer Engineering, Advanced Diagnosis, Automation, and Control Laboratory, North Carolina State University, Raleigh, NC, USADepartment of Electrical and Computer Engineering, Advanced Diagnosis, Automation, and Control Laboratory, North Carolina State University, Raleigh, NC, USADepartment of Electrical and Computer Engineering, Advanced Diagnosis, Automation, and Control Laboratory, North Carolina State University, Raleigh, NC, USASafely and efficiently managing a battery pack consisting of hundreds to thousands of battery cells is a critical but challenging task due to commonly observed uncertainties, e.g. temperature, battery degradation and SOC estimation inaccuracy. This paper proposes a robust and efficient most significant cell methodology that estimates the battery pack SOC depending on the determined most significant cells. The estimation adopting this methodology is robust to variations of temperature, battery degradation and battery cell SOC estimation inaccuracy. A battery pack simulator and a real battery pack designed for electric vehicles were used as prototypes to illustrate the high performance, robustness and effectiveness of the proposed methodology. Moreover, the proposed algorithm requires light computational effort, making it suitable for real-time operation.https://ieeexplore.ieee.org/document/9433556/Efficientelectric vehiclelithium-ion battery packmicrogridrobustnessserial-connection |
| collection |
DOAJ |
| language |
English |
| format |
Article |
| sources |
DOAJ |
| author |
Cong-Sheng Huang Zheyuan Cheng Mo-Yuen Chow |
| spellingShingle |
Cong-Sheng Huang Zheyuan Cheng Mo-Yuen Chow A Robust and Efficient State-of-Charge Estimation Methodology for Serial-Connected Battery Packs: Most Significant Cell Methodology IEEE Access Efficient electric vehicle lithium-ion battery pack microgrid robustness serial-connection |
| author_facet |
Cong-Sheng Huang Zheyuan Cheng Mo-Yuen Chow |
| author_sort |
Cong-Sheng Huang |
| title |
A Robust and Efficient State-of-Charge Estimation Methodology for Serial-Connected Battery Packs: Most Significant Cell Methodology |
| title_short |
A Robust and Efficient State-of-Charge Estimation Methodology for Serial-Connected Battery Packs: Most Significant Cell Methodology |
| title_full |
A Robust and Efficient State-of-Charge Estimation Methodology for Serial-Connected Battery Packs: Most Significant Cell Methodology |
| title_fullStr |
A Robust and Efficient State-of-Charge Estimation Methodology for Serial-Connected Battery Packs: Most Significant Cell Methodology |
| title_full_unstemmed |
A Robust and Efficient State-of-Charge Estimation Methodology for Serial-Connected Battery Packs: Most Significant Cell Methodology |
| title_sort |
robust and efficient state-of-charge estimation methodology for serial-connected battery packs: most significant cell methodology |
| publisher |
IEEE |
| series |
IEEE Access |
| issn |
2169-3536 |
| publishDate |
2021-01-01 |
| description |
Safely and efficiently managing a battery pack consisting of hundreds to thousands of battery cells is a critical but challenging task due to commonly observed uncertainties, e.g. temperature, battery degradation and SOC estimation inaccuracy. This paper proposes a robust and efficient most significant cell methodology that estimates the battery pack SOC depending on the determined most significant cells. The estimation adopting this methodology is robust to variations of temperature, battery degradation and battery cell SOC estimation inaccuracy. A battery pack simulator and a real battery pack designed for electric vehicles were used as prototypes to illustrate the high performance, robustness and effectiveness of the proposed methodology. Moreover, the proposed algorithm requires light computational effort, making it suitable for real-time operation. |
| topic |
Efficient electric vehicle lithium-ion battery pack microgrid robustness serial-connection |
| url |
https://ieeexplore.ieee.org/document/9433556/ |
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