State of Charge Estimation for Electric Vehicle Battery Based on Amended Ah Metrology
- 10.2991/ceie-16.2017.60How to use a DOI?
- Electric Vehicle; Lithium-ion Battery; SOC; Ah Metrology
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.
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
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 - 10.2991/ceie-16.2017.60 ID - Zhao2016/10 ER -