Application of Kalman Filter in SOC Estimation of Power Lithium-Ion Battery

2012 ◽  
Vol 605-607 ◽  
pp. 1939-1943
Author(s):  
Chen Zhao ◽  
Xi Kun Chen
Keyword(s):  
Kalman Filter ◽  
Lithium Ion Battery ◽  
Lithium Ion ◽  
Estimation Algorithm ◽  
State Of Charge ◽  
Voltage Response ◽  
Integrated Method ◽  
Soc Estimation ◽  
Terminal Voltage ◽  
State Of Charge Estimation

This paper analyses the application of Kalman Filter (KF) in Power Lithium-ion Battery SOC (State of Charge) estimation algorithm. After the analysis of two popular SOC estimate algorithm based on KF, an improved KF-SOC algorithm is proposed. The main advance of this improved algorithm is the introduction of parameter-rectification. The parameter-rectification which based on analysis of battery electrochemical principle and battery terminal voltage response curve is also achieved by KF. The main algorithm of improved KF-SOC is generated by the combination of KF and Ampere-hour integrated method. Later the simulations proved the new algorithm with high accuracy.

scholarly journals State-of-Charge Estimation of Lithium-Ion Battery Based on Extended Kalman Filter Algorithm

2020 ◽  
pp. 420-437
Author(s):  
Wu Xiaogang ◽  
Xuefeng Li ◽  
Nikolay I. Shurov ◽  
Alexander A. Shtang ◽  
Michael V. Yaroslavtsev ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Lithium Ion Battery ◽  
Electric Vehicle ◽  
Extended Kalman Filter ◽  
Lithium Ion ◽  
Operating Conditions ◽  
State Of Charge ◽  
Battery Management ◽  
Soc Estimation ◽  
Ternary Polymer

As the core component of electric vehicle, lithium-ion battery needs to adopt effective battery management method to prolong battery life and improve the reliability and safety. The accurate estimation of the battery SOC can be used to prevent the battery over charge and over discharge, reduce damage to the battery and improve battery performance, which plays a vital role in the battery management system. The study of battery SOC estimation mainly focused on the battery model construction and SOC estimation algorithm. Aiming at the problem that the state of charge (SOC) of electric vehicle is difficult to be accurately estimated under complex operating conditions, based on the parameter identification of the equivalent circuit of a ternary polymer lithium-ion battery, an Extended Kalman Filter (EKF) algorithm was used to estimate the SOC of the ternary polymer lithium-ion battery. Simulation and experimental results show that the estimation of SOC can be carried out by using the EKF algorithm under the conditions of China Passenger Car Condition (Chinacar) and new European driving cycle (NEDC) Compared with the coulomb counting method, the average error of SOC estimation can be realized is 1.042% and 1.138% respectively, the maximum error within 4%. Application of this algorithm to achieve SOC estimation has good robustness and convergence

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