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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Goud J.S. | |
| dc.contributor.author | Kalpana R. | |
| dc.contributor.author | Singh B. | |
| dc.date.accessioned | 2021-05-05T10:31:32Z | - |
| dc.date.available | 2021-05-05T10:31:32Z | - |
| dc.date.issued | 2021 | |
| dc.identifier.citation | IEEE Transactions on Energy Conversion , Vol. 36 , 1 , p. 111 - 119 | en_US |
| dc.identifier.uri | https://doi.org/10.1109/TEC.2020.3008937 | |
| dc.identifier.uri | http://idr.nitk.ac.in/jspui/handle/123456789/16745 | - |
| dc.description.abstract | Li-ion batteries are playing a crucial role in the fields of renewable energy systems and electric vehicles. The reliability of these systems depends on a battery management system (BMS) which monitors the state of charge (SoC) and state of health (SoH) effectively. Knowing the SoH of a battery in advance enhances the system reliability. This article proposes an accurate online estimation of SoH of a Li-ion battery integrated in solar photovoltaic system (SPV) applications. The proposed method uses the modified coulomb counting method to estimate the SoH of a battery. The proposed SoH estimation method is simulated in MATLAB/Simulink by considering the aging factors such as temperature, charge/discharge rates and depth of discharge. Moreover, the proposed method is validated using an experimental prototype and the results are found to be satisfactory. © 1986-2012 IEEE. | en_US |
| dc.title | An Online Method of Estimating State of Health of a Li-Ion Battery | en_US |
| dc.type | Article | en_US |
| Appears in Collections: | 1. Journal Articles | |
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