The Research on SOC Estimation of Lithium Battery Based on GWO-PF

2020 ◽  
Author(s):  
Tian Dongdong ◽  
Li Liwei ◽  
Yang Yuxin ◽  
Wang Kia
Keyword(s):  
Lithium Battery ◽  
Soc Estimation

Online State of Charge Estimation for Battery of Electric Vehicle Using Sigma-Points Kalman Filters

2013 ◽  
Vol 427-429 ◽  
pp. 824-829
Author(s):  
Li Cun Fang ◽  
Gang Xu ◽  
Tian Li Li ◽  
Ke Min Zhu
Keyword(s):  
Electric Vehicle ◽  
Kalman Filters ◽  
Hybrid Electric Vehicle ◽  
Lithium Battery ◽  
Cell Model ◽  
Operating Conditions ◽  
State Of Charge ◽  
Battery Cell ◽  
Soc Estimation ◽  
Simulation And Experiment

An accurate state-of-charge (SOC) estimation of the hybrid electric vehicle (HEV) and electric vehicle (EV) battery pack is a difficult task to be performed online in a vehicle because of the noisy and low accurate measurements and the wide operating conditions in which the vehicle battery can operate. A Sigma-points Kalman Filters (SPKF) algorithm based on an improved Lithium battery cell model to estimate the SOC of a Lithium battery cell is proposed in this paper. The simulation and experiment results show the effectiveness and ease of implementation of the proposed technique.

Modified Strong Tracking Filter for the SOC Estimation of Lithium Battery in Electric Vehicle

2012 ◽  
Vol 236-237 ◽  
pp. 1362-1367
Author(s):  
Ze Cheng ◽  
Yu Hui Zhang ◽  
Yan Li Liu
Keyword(s):  
Electric Vehicle ◽  
Lithium Battery ◽  
State Of Charge ◽  
Estimation Accuracy ◽  
Original Algorithm ◽  
Soc Estimation ◽  
Tracking Ability ◽  
Strong Tracking Filter ◽  
Vehicle Management ◽  
Tracking Filter

In electric vehicle management system, the key technology is to estimate the SOC (state of charge) of battery in dynamic process. This paper builds the state space equation of lithium battery based on improved Randle’s model, realizes the tracking estimation of SOC using modified STF(strong tracking filter) algorithm. The simulation result proves that compared with the original algorithm, modified algorithm can greatly improve the system’s tracking ability as well as the estimation accuracy of SOC.

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