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Energies 2017, 10(9), 1284; doi:10.3390/en10091284

Online Lithium-Ion Battery Internal Resistance Measurement Application in State-of-Charge Estimation Using the Extended Kalman Filter

Department of Physics, Donghua University, Shanghai 201620, China
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Received: 2 August 2017 / Revised: 23 August 2017 / Accepted: 24 August 2017 / Published: 29 August 2017
(This article belongs to the Collection Electric and Hybrid Vehicles Collection)
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Abstract

The lithium-ion battery is a viable power source for hybrid electric vehicles (HEVs) and, more recently, electric vehicles (EVs). Its performance, especially in terms of state of charge (SOC), plays a significant role in the energy management of these vehicles. The extended Kalman filter (EKF) is widely used to estimate online SOC as an efficient estimation algorithm. However, conventional EKF algorithms cannot accurately estimate the difference between individual batteries, which should not be ignored. However, the internal resistance of a battery can represent this difference. Therefore, this work proposes using an EKF with internal resistance measurement based on the conventional algorithm. Lithium-ion battery real-time resistances can help the Kalman filter overcome defects from simplistic battery models. In addition, experimental results show that it is useful to introduce online internal resistance to the estimation of SOC. View Full-Text
Keywords: online internal resistance; state-of-charge; extended Kalman filter; lithium-ion battery online internal resistance; state-of-charge; extended Kalman filter; lithium-ion battery
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Wang, D.; Bao, Y.; Shi, J. Online Lithium-Ion Battery Internal Resistance Measurement Application in State-of-Charge Estimation Using the Extended Kalman Filter. Energies 2017, 10, 1284.

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