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Energies 2017, 10(8), 1149; https://doi.org/10.3390/en10081149

A Comparative Study of Three Improved Algorithms Based on Particle Filter Algorithms in SOC Estimation of Lithium Ion Batteries

1
Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, China
2
Sunwoda Electronic Co. Ltd., Shenzhen 518108, China
*
Author to whom correspondence should be addressed.
Received: 29 June 2017 / Revised: 26 July 2017 / Accepted: 28 July 2017 / Published: 4 August 2017
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Abstract

The state of charge (SOC) is an important parameter for batteries, especially those for electric vehicles. Since SOC cannot be obtained directly by measurement, SOC estimation methods are required. In this paper, three model-based methods, including the extended particle filter (EPF), cubature particle filter (CPF), and unscented particle filter (UPF), are compared in terms of complexity, accuracy, and robustness. The second-order resistor-capacitor (RC) equivalent circuit model is selected as the circuit model of the lithium-ion battery, and the parameters of the model are obtained by off-line identification. Then, the City test is applied to compare the performance of the methods. The experimental results show that the EPF method exhibits low complexity and fast running speed, but poor accuracy and robustness. Compared with the EPF method, the complexity of the CPF and UPF methods is relatively high, but these models offer improved accuracy and robustness. View Full-Text
Keywords: state of charge; lithium-ion battery; extended particle filter (EPF); cubature particle filter (CPF); unscented particle filter (UPF) state of charge; lithium-ion battery; extended particle filter (EPF); cubature particle filter (CPF); unscented particle filter (UPF)
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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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Xia, B.; Sun, Z.; Zhang, R.; Cui, D.; Lao, Z.; Wang, W.; Sun, W.; Lai, Y.; Wang, M. A Comparative Study of Three Improved Algorithms Based on Particle Filter Algorithms in SOC Estimation of Lithium Ion Batteries. Energies 2017, 10, 1149.

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