Prediction Method of Lithium Battery's State of Charge Based on No Trace of Calman Filter

2014 ◽  
Vol 912-914 ◽  
pp. 1888-1891
Author(s):  
Zhen Ping Cui ◽  
Yong Xin Qin ◽  
Hao Li
Keyword(s):  
Kalman Filter ◽  
Equivalent Circuit ◽  
Lithium Battery ◽  
Unscented Kalman Filter ◽  
Equivalent Circuit Model ◽  
Prediction Method ◽  
Open Circuit ◽  
State Of Charge ◽  
Battery State Of Charge ◽  
Kalman Filter Algorithm

The Thevenin equivalent circuit model is established for single lithium battery,current and voltage data to identify the parameters of the equivalent circuit is obtained by the discharge experiment, and the open circuit voltage and charge state relationship curve was obtained by curve fitting.On this basis, design the extended Kalman filter algorithm and unscented Kalman filter algorithm on the lithium battery state of charge, then use Matlab/Simulik simulation, the results of the state prediction of the two different algorithms are compared. The analysis results show that two kinds of algorithm are effective for single lithium battery state of charge estimation, and no trace of Calman filter algorithm can effectively solve the the problem of accuracy is not high of the extended Calman filter ,which due to the linear approximation.

scholarly journals An Improved Model-Based Self-Adaptive Filter for Online State-of-Charge Estimation of Li-Ion Batteries

2018 ◽  
Vol 8 (11) ◽  
pp. 2084 ◽  
Author(s):  
Chi Zhang ◽  
Fuwu Yan ◽  
Changqing Du ◽  
Giorgio Rizzoni
Keyword(s):  
Kalman Filter ◽  
Equivalent Circuit ◽  
Unscented Kalman Filter ◽  
Equivalent Circuit Model ◽  
Experimental Tests ◽  
State Of Charge ◽  
Hysteresis Phenomenon ◽  
Battery Modeling ◽  
Modified Model ◽  
Soc Estimation

Accurate battery modeling is essential for the state-of-charge (SOC) estimation of electric vehicles, especially when vehicles are operated in dynamic processes. Temperature is a significant factor for battery characteristics, especially for the hysteresis phenomenon. Lack of existing literatures on the consideration of temperature influence in hysteresis voltage can result in errors in SOC estimation. Therefore, this study gives an insight to the equivalent circuit modeling, considering the hysteresis and temperature effects. A modified one-state hysteresis equivalent circuit model was proposed for battery modeling. The characterization of hysteresis voltage versus SOC at various temperatures was acquired by experimental tests to form a static look-up table. In addition, a strong tracking filter (STF) was applied for SOC estimation. Numerical simulations and experimental tests were performed in commercial 18650 type Li(Ni1/3Co1/3Mn1/3)O2 battery. The results were systematically compared with extended Kalman filter (EKF) and unscented Kalman filter (UKF). The results of comparison showed the following: (1) the modified model has more voltage tracking capability than the original model; and (2) the modified model with STF algorithm has better accuracy, robustness against initial SOC error, voltage measurement drift, and convergence behavior than EKF and UKF.

Research on Active Equalization of Lithium Battery via SOC

2014 ◽  
Vol 556-562 ◽  
pp. 2013-2016
Author(s):  
Yun Gan Wang ◽  
Zhong Feng Wang ◽  
J.L. Huang ◽  
Li Gang Li
Keyword(s):  
Kalman Filter ◽  
Equivalent Circuit ◽  
Extended Kalman Filter ◽  
Lithium Battery ◽  
Equivalent Circuit Model ◽  
High Accuracy ◽  
Battery Pack ◽  
Low Loss ◽  
Adaptive Parameters ◽  
Kalman Filter Algorithm

This paper presents an active equalization method for lithium battery via SOC. The high accuracy of SOC is promised by extended Kalman filter algorithm (EKF) based on the adaptive parameters equivalent-circuit model at all SOC region. Then a small size, low loss resonant soft-switching active equalization circuit is presented. That circuit combined with SOC do precisely balance the battery pack during charge and discharge processes, which can effectively improve the battery pack’s using life.

scholarly journals Estimation for Battery State of Charge Based on Temperature Effect and Fractional Extended Kalman Filter

Energies ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 5947
Author(s):  
Chengcheng Chang ◽  
Yanping Zheng ◽  
Yang Yu
Keyword(s):  
Kalman Filter ◽  
Equivalent Circuit ◽  
Extended Kalman Filter ◽  
Open Circuit Voltage ◽  
Equivalent Circuit Model ◽  
Open Circuit ◽  
Circuit Model ◽  
State Of Charge ◽  
First Order ◽  
Battery Capacity

The electric vehicle has become an important development direction of the automobile industry, and the lithium-ion power battery is the main energy source of electric vehicles. The accuracy of state of charge (SOC) estimation directly affects the performance of the vehicle. In this paper, the first order fractional equivalent circuit model of a lithium iron phosphate battery was established. Battery capacity tests with different charging and discharging rates and open circuit voltage tests were carried out under different ambient temperatures. The conversion coefficient of charging and discharging capacity and the simplified open circuit voltage model considering the hysteresis characteristics of the battery were proposed. The parameters of the first order fractional equivalent circuit model were identified by using a particle swarm optimization algorithm with dynamic inertia weight. Finally, the recursive formula of a fractional extended Kalman filter was derived, and the battery SOC was estimated under continuous Dynamic Stress Test (DST) conditions. The results show that the estimation method has high accuracy and strong robustness.

scholarly journals State of charge estimation by using extended Kalman filter based on improved open circuit voltage model

2021 ◽  
Vol 10 (1) ◽  
pp. 1
Author(s):  
Maamar Souaihia ◽  
Bachir Belmadani ◽  
Rachid Taleb ◽  
Kamel Tounsi
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Equivalent Circuit Model ◽  
Open Circuit ◽  
State Of Charge ◽  
Soc Estimation ◽  
Battery Model ◽  
Filter Approach ◽  
State Of Charge Estimation ◽  
Good Agreement

This paper focuses on the state of charge estimation (SOC) for battery Li-ion. By modeling a battery based on the equivalent circuit model, the extended Kalman filter approach can be applied to estimate the battery SOC. An electrical battery model is developed in Matlab, Where the structure of the model is detailed by equations and blocks. The battery model has been validated from the experiment results. The comparison shows a good agreement in predicting the voltage, SOC estimation and the model performs better in SOC estimation.

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