A Novel Method for Estimating State-of-Charge in Power Batteries for Electric Vehicles

  • Nan Zhang
  • Yunshan Zhou
  • Qiang Tian
  • Xiaoying Liao
  • Feitie ZhangEmail author
Regular Paper


Estimation of the state-of- charge (SOC) of power batteries has always been the focus of electric vehicle users’ criticism. Accurate SOC is beneficial for extending the mileage of electric vehicles and the life of the battery pack. The key to improving SOC accuracy is to establish its accurate model and combine it with an appropriate estimation algorithm. Based on characterization experiments related to SOC, this paper describes a second-order charge–discharge resistor–capacitor model that can accurately simulate external characteristics of the battery and identify them online. An improved adaptive unscented Kalman filter algorithm based on Sage–Husa is introduced to estimate SOC. The reliability of the algorithm is verified by building a MATLAB/Simulink simulation model. The results show that the improved algorithm displays increased robustness and can quickly converge to the true value; the steady-state error is also within a small range.


Adaptive unscented Kalman filter Equivalent circuit model Power battery State-of-charge 

List of Symbols






Internal ohmic resistance


The battery capacity








Forgetting factor


The process noise of the system


The observation noise of the system


The covariance of the process noise


The covariance of the observed noise


The mean of wk


The mean of vk



First of all, I would like to thank my supervisor, Professor Zhou Yunshan, for his great support and encouragement during my study and work. The topic selection, research, and writing of the paper were all completed under the strict requirements and patient guidance of Prof. Zhou. Prof. Zhou has been committed to the research and development of key technologies for automotive power transmission and electronic control for many years; his rich experience in engineering projects, selfless research spirit, and strategic vision of cutting-edge technology have had a profound impact on me. Secondly, thanks to Tian Qiang, Xiong Huanjian, Li Hangyang and other brothers for pointing me in the right direction when I encountered difficulties in my studies. Thanks to all the members of the lab; the laboratory’s good learning atmosphere and research environment which have enabled me to complete this paper successfully. Thanks to my girlfriend Liao Xiaoying for her concern and care in my life. Finally, I would like to express my heartfelt thanks to the experts and teachers who reviewed this paper despite their busy schedule. This work was supported by the National Natural Science Foundation of China (Grant No. 51475151).

Supplementary material

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Copyright information

© Korean Society for Precision Engineering 2019

Authors and Affiliations

  • Nan Zhang
    • 1
  • Yunshan Zhou
    • 1
  • Qiang Tian
    • 1
  • Xiaoying Liao
    • 1
  • Feitie Zhang
    • 1
    Email author
  1. 1.College of Mechanical and Vehicle EngineeringHunan UniversityChangshaChina

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