A novel estimation of state of charge for the lithium-ion battery in electric vehicle without open circuit voltage experiment

Energy ◽  
2022 ◽  
pp. 123072
Author(s):  
Renxin Xiao ◽  
Yanwen Hu ◽  
Xianguang Jia ◽  
Guisheng Chen
Energies ◽  
2019 ◽  
Vol 12 (17) ◽  
pp. 3383 ◽  
Author(s):  
Woo-Yong Kim ◽  
Pyeong-Yeon Lee ◽  
Jonghoon Kim ◽  
Kyung-Soo Kim

This paper presents a nonlinear-model-based observer for the state of charge estimation of a lithium-ion battery cell that always exhibits a nonlinear relationship between the state of charge and the open-circuit voltage. The proposed nonlinear model for the battery cell and its observer can estimate the state of charge without the linearization technique commonly adopted by previous studies. The proposed method has the following advantages: (1) The observability condition of the proposed nonlinear-model-based observer is derived regardless of the shape of the open circuit voltage curve, and (2) because the terminal voltage is contained in the state vector, the proposed model and its observer are insensitive to sensor noise. A series of experiments using an INR 18650 25R battery cell are performed, and it is shown that the proposed method produces convincing results for the state of charge estimation compared to conventional SOC estimation methods.


Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2408 ◽  
Author(s):  
Ruifeng Zhang ◽  
Bizhong Xia ◽  
Baohua Li ◽  
Libo Cao ◽  
Yongzhi Lai ◽  
...  

Open circuit voltage (OCV) is an important characteristic parameter of lithium-ion batteries, which is used to analyze the changes of electronic energy in electrode materials, and to estimate battery state of charge (SOC) and manage the battery pack. Therefore, accurate OCV modeling is a great significance for lithium-ion battery management. In this paper, the characteristics of high-capacity lithium-ion batteries at different temperatures were considered, and the OCV-SOC characteristic curves at different temperatures were studied by modeling, exponential, polynomial, sum of sin functions, and Gaussian model fitting method with pulse test data. The parameters of fitting OCV-SOC curves by exponential model (n = 2), polynomial model (n = 3~7), sum of sin functions model (n = 3), and Gaussian model (n = 4) at temperatures of 45 °C, 25 °C, 0 °C, and −20°C are obtained, and the errors are analyzed. The experimental results show that the operating temperature of the battery influences the OCV-SOC characteristic significantly. Therefore, these factors need to be considered in order to increase the accuracy of the model and improve the accuracy of battery state estimation.


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