Proceedings of the International Conference on Communication and Electronic Information Engineering (CEIE 2016)

State of Charge Estimation for Electric Vehicle Battery Based on Amended Ah Metrology

Authors
Qiang Zhao, Chengjun Shao, Yinghua Ha
Corresponding Author
Qiang Zhao
Available Online October 2016.
DOI
https://doi.org/10.2991/ceie-16.2017.60How to use a DOI?
Keywords
Electric Vehicle; Lithium-ion Battery; SOC; Ah Metrology
Abstract
The battery is the power source of electric vehicles and its performance has a direct influence on the power performance and the trip range. The state of charge (SOC) of the battery is one of the most important parameters in the use process of a battery. At the same time, the estimation accuracy of SOC can prevent battery over charging or over discharging, extending the service life of the battery effectively, and forecasting the remainder range accurately while traveling. The estimation of SOC is a very complicated work, due to the high nonlinear of the process of estimating. Moreover, SOC is affected by many factors, such as temperature, charge and discharge efficiency and aging factors and so on. In this paper, the parameters which affect the estimation accuracy of SOC are analyzed. To improve the estimation accuracy of SOC, an amended model is proposed, which combines Ah Metrology and open-circuit voltage with the correction on charge and discharge efficiency, aging factors, the initial SOC and capacity of battery. Simulation results show that an amended model of Ah Metrology can improve the estimation accuracy of SOC and reduce the error, which validates the feasibility and reliability of the proposed method.
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This is an open access article distributed under the CC BY-NC license.

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Volume Title
Proceedings of the International Conference on Communication and Electronic Information Engineering (CEIE 2016)
Series
Advances in Engineering Research
Publication Date
October 2016
ISBN
978-94-6252-312-8
ISSN
2352-5401
DOI
https://doi.org/10.2991/ceie-16.2017.60How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Qiang Zhao
AU  - Chengjun Shao
AU  - Yinghua Ha
PY  - 2016/10
DA  - 2016/10
TI  - State of Charge Estimation for Electric Vehicle Battery Based on Amended Ah Metrology
BT  - Proceedings of the International Conference on Communication and Electronic Information Engineering (CEIE 2016)
PB  - Atlantis Press
SP  - 475
EP  - 484
SN  - 2352-5401
UR  - https://doi.org/10.2991/ceie-16.2017.60
DO  - https://doi.org/10.2991/ceie-16.2017.60
ID  - Zhao2016/10
ER  -