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Energies 2015, 8(5), 4400-4415; doi:10.3390/en8054400

Online Internal Temperature Estimation for Lithium-Ion Batteries Based on Kalman Filter

School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China
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Academic Editor: Izumi Taniguchi
Received: 1 April 2015 / Revised: 5 May 2015 / Accepted: 12 May 2015 / Published: 15 May 2015
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Abstract

The battery internal temperature estimation is important for the thermal safety in applications, because the internal temperature is hard to measure directly. In this work, an online internal temperature estimation method based on a simplified thermal model using a Kalman filter is proposed. As an improvement, the influences of entropy change and overpotential on heat generation are analyzed quantitatively. The model parameters are identified through a current pulse test. The charge/discharge experiments under different current rates are carried out on the same battery to verify the estimation results. The internal and surface temperatures are measured with thermocouples for result validation and model construction. The accuracy of the estimated result is validated with a maximum estimation error of around 1 K. View Full-Text
Keywords: internal temperature estimation; Kalman filter; thermal model; heat generation; entropy change internal temperature estimation; Kalman filter; thermal model; heat generation; entropy change
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Sun, J.; Wei, G.; Pei, L.; Lu, R.; Song, K.; Wu, C.; Zhu, C. Online Internal Temperature Estimation for Lithium-Ion Batteries Based on Kalman Filter. Energies 2015, 8, 4400-4415.

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