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World Electric Vehicle Journal is published by MDPI from Volume 9 issue 1 (2018). Articles in this Issue were published by The World Electric Vehicle Association (WEVA) and its member the European Association for e-Mobility (AVERE), the Electric Drive Transportation Association (EDTA), and the Electric Vehicle Association of Asia Pacific (EVAAP). They are hosted by MDPI on mdpi.com as a courtesy and upon agreement with AVERE.
Open AccessArticle

Proposal and Validation of a SOC Estimation Algorithm of LiFePO4 Battery Packs for Traction Applications

IK4-Ikerlan, Po. J. Ma Arizmendiarrieta 2, 20500 Arrasate-Mondragón, Gipuzkoa, Spain
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World Electr. Veh. J. 2013, 6(3), 771-781; https://doi.org/10.3390/wevj6030771
Published: 27 September 2013
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Abstract

An accurate onboard State-of-Charge (SOC) estimation is one of the key functions a Battery Management System (BMS) has to perform in order to provide the optimal performance management of the battery system under control. In this framework, this paper presents a proposal of an Enhanced Coulomb Counting (CC) State-of-Charge estimation algorithm based on Constant Voltage Charge Detection (CVCD) and Open Circuit Voltage (OCV) model for LiFePO4 batteries. Designed for onboard BMS implementation, it is characterized by its simplicity and operability in wide operating conditions (under diverse load profiles, temperatures, SOC ranges, etc.). The description of the algorithm at both, cell and battery-module level is detailed in the paper. Furthermore, its on-line experimental validation and scope determination is tested under three different traction applications and cell specimens in an own-developed real time validation platform: 2.5 Ah cells (Type A) in a residential elevator application, 8 Ah cells (Type B) in a pure electric on-road vehicle application and 100 Ah cells (Type C) in an electric railway vehicle application. According to the achieved results, the accuracy and versatility of the algorithm for different operating scenarios is certainly proven. In the worst case scenario the algorithm is capable of keeping the SOC estimation of the system under test stabilized around 5% of error.
Keywords: lithium battery; BMS (Battery Management System); diagnosis; state of charge; battery model lithium battery; BMS (Battery Management System); diagnosis; state of charge; battery model
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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Garmendia, M.; Gandiaga, I.; Perez, G.; Viscarret, U.; Etxeberria-Otadui, I. Proposal and Validation of a SOC Estimation Algorithm of LiFePO4 Battery Packs for Traction Applications. World Electr. Veh. J. 2013, 6, 771-781.

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