A new state of charge estimation for lithium-ion battery based on sliding-mode observer and battery status

2016 ◽  
Author(s):  
Xiaohui Gong ◽  
Zhiwu Huang ◽  
Liran Li ◽  
Honghai Lu ◽  
Sanfeng Liu ◽  
...  
Keyword(s):  
Lithium Ion Battery ◽  
Sliding Mode ◽  
Lithium Ion ◽  
Sliding Mode Observer ◽  
State Of Charge ◽  
State Of Charge Estimation

scholarly journals Estimating the State of Charge of Lithium-ion Battery based on Sliding Mode Observer

2016 ◽  
Vol 49 (11) ◽  
pp. 54-61 ◽  
Author(s):  
Yan Ma ◽  
Bingsi Li ◽  
Yongqiang Xie ◽  
Hong Chen
Keyword(s):  
Lithium Ion Battery ◽  
Sliding Mode ◽  
Lithium Ion ◽  
The State ◽  
Sliding Mode Observer ◽  
State Of Charge

State of Charge Estimation of Power Lithium-Ion Battery Based on Sliding Mode Observer

2013 ◽  
Vol 805-806 ◽  
pp. 1692-1699 ◽  
Author(s):  
Tie Zhou Wu ◽  
Ming Yue Wang ◽  
Qin Xiao
Keyword(s):  
Sliding Mode ◽  
Estimation Error ◽  
Lithium Ion ◽  
Value Theory ◽  
The State ◽  
Sliding Mode Observer ◽  
State Of Charge ◽  
Estimation Accuracy ◽  
Design Parameters ◽  
State Of Charge Estimation

The study of the application of the sliding mode observer method that estimates the state of charge. Based on the state space model of battery established on the model of improved EMF equivalent circuit, a sliding mode state observer is designed to help improve the jitter problem. Considering the nonlinear terms in the model for the analysis of the stability of the observer and the characteristics of the industry under its derivative, and using Lagrange mean value theory to guarantee the convergence conditions of the observer, the design parameters of the observer can thus be determined .Then, this thesis compares the simulation of this method under Matlab environment with the extended Kalman filter method. The results show that the method has higher estimation accuracy in the case of the same battery modeling errors. Therefore, the SOC estimation of the sliding mode observer can effectively reduce the state of charge estimation error introduced by the model error.

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