Khan, Ferdous Irtiaz, Hossain, Md. Moinul, Lu, Gang, Wang, Lijuan (2026) Health monitoring of lithium-ion battery through magnetic field sensing. In: IEEE I2MTC – International Instrumentation and Measurement Technology Conference, May 25-28, 2026, Nancy, France. (In press) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:113429)
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Abstract
Lithium-ion batteries require reliable non-invasive monitoring techniques to ensure safety, longevity, and optimal performance. While conventional battery management systems rely on voltage, current, and temperature measurements, these parameters provide limited insight into internal mechanical and electrochemical changes associated with ageing and degradation. Although magnetic field (MF) based approaches have been explored conceptually, their experimental validation for lithium-ion batteries remains limited. This paper presents a non-invasive MF sensing framework based on a dual-coil inductive system that monitors changes in the voltage of a secondary coil induced by the battery’s state-dependent magnetic interactions. A systematic experimental methodology is developed and validated across lithium-ion cells of different capacities, discharge rates, and health conditions. Results show that the proposed MF sensing approach provides a smooth, robust, and voltage-normalized response that scales with battery size and degradation state, exhibiting significantly higher effective sensitivity over narrow operating windows compared to mechanical strain sensing. These findings demonstrate that MF sensing can capture bulk internal state changes associated with both state-of-charge and state-of-health, offering a low-cost, compact, and non-invasive alternative for advanced battery monitoring applications.
| Item Type: | Conference proceeding |
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| Uncontrolled keywords: | magnetic field sensing; lithium-ion battery; state of charge; state of health |
| Subjects: |
Q Science Q Science > Q Science (General) |
| Institutional Unit: | Schools > School of Engineering, Mathematics and Physics > Engineering |
| Former Institutional Unit: |
There are no former institutional units.
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| Depositing User: | Moinul Hossain |
| Date Deposited: | 16 Mar 2026 10:26 UTC |
| Last Modified: | 17 Mar 2026 15:57 UTC |
| Resource URI: | https://kar.kent.ac.uk/id/eprint/113429 (The current URI for this page, for reference purposes) |
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https://orcid.org/0000-0003-4184-2397
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