Title: Cycle life estimation method for parallel lithium battery pack based on double Kalman filtering algorithm

Authors: Qiuting Wang; Wei Qi

Addresses: Department of Electric and Information Engineering, Zhejiang University City College, 51 Huzhou Road, Hangzhou 310015, China ' Department of Electric and Information Engineering, Zhejiang University City College, 51 Huzhou Road, Hangzhou 310015, China

Abstract: The lithium-iron phosphate battery cell and parallel battery pack are studied in this paper. The characteristics of three parameters defined as Ohmic resistance, open circuit voltage (OCV) and state of charge (SOC) are analysed based on the equivalent circuit model. The double Kalman filtering (D-KF) algorithm is presented to estimate the cycle life of lithium battery pack, which is defined as state of health (SOH). The efforts of our study are: first, the equivalent model of battery pack is established and the model parameters are estimated based on robust unscented Kalman filtering algorithm (R-UKF). Second, the SOH estimation model is proposed and validated. Third, the SOH value of battery pack is calculated using extended Kalman filter (EKF) as the auxiliary filter, according to the real-time value of model parameters. The experimental results indicate that the proposed parameters and SOH estimation method has better accuracy, robustness and convergence behaviour.

Keywords: lithium-iron phosphate; SOH; state of health; double Kalman filter; cycle life; parallel battery pack; robust unscented Kalman filter.

DOI: 10.1504/IJEHV.2017.085341

International Journal of Electric and Hybrid Vehicles, 2017 Vol.9 No.2, pp.103 - 120

Received: 21 Dec 2016
Accepted: 23 Jan 2017
Published online: 23 Jul 2017 *

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