A Comparative Study on Open Circuit Voltage Models for Lithium-ion Batteries

The current research of state of charge (SoC) online estimation of lithium-ion battery (LiB) in electric vehicles (EVs) mainly focuses on adopting or improving of battery models and estimation filters. However, little attention has been paid to the accuracy of various open circuit voltage (OCV) mode...

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Bibliographic Details
Published in:Chinese journal of mechanical engineering 2018-12, Vol.31 (1), p.76-83, Article 65
Main Authors: Yu, Quan-Qing, Xiong, Rui, Wang, Le-Yi, Lin, Cheng
Format: Article
Language:English
Subjects:
Advanced Transportation Equipment
Ambient temperature
Circuits
Comparative studies
Curve fitting
Data points
Electric filters
Electric vehicles
Electrical Machines and Networks
Electronics and Microelectronics
Engineering
Engineering Thermodynamics
Graphite
Heat and Mass Transfer
Instrumentation
Lithium
Lithium-ion batteries
Machines
Manufacturing
Mechanical Engineering
Open circuit voltage
Original Article
Power Electronics
Processes
Rechargeable batteries
Root-mean-square errors
State of charge
Theoretical and Applied Mechanics
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Summary:The current research of state of charge (SoC) online estimation of lithium-ion battery (LiB) in electric vehicles (EVs) mainly focuses on adopting or improving of battery models and estimation filters. However, little attention has been paid to the accuracy of various open circuit voltage (OCV) models for correcting the SoC with aid of the ampere-hour counting method. This paper presents a comprehensive comparison study on eighteen OCV models which cover the majority of models used in literature. The low-current OCV tests are conducted on the typical commercial LiFePO 4 /graphite (LFP) and LiNiMnCoO 2 /graphite (NMC) cells to obtain the experimental OCV-SoC curves at different ambient temperature and aging stages. With selected OCV and SoC points from experimental OCV-SoC curves, the parameters of each OCV model are determined by curve fitting toolbox of MATLAB 2013. Then the fitting OCV-SoC curves based on diversified OCV models are also obtained. The indicator of root-mean-square error (RMSE) between the experimental data and fitted data is selected to evaluate the adaptabilities of these OCV models for their main features, advantages, and limitations. The sensitivities of OCV models to ambient temperatures, aging stages, numbers of data points, and SoC regions are studied for both NMC and LFP cells. Furthermore, the influences of these models on SoC estimation are discussed. Through a comprehensive comparison and analysis on OCV models, some recommendations in selecting OCV models for both NMC and LFP cells are given.
ISSN:1000-9345
2192-8258
DOI:10.1186/s10033-018-0268-8