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LiFePO4 battery state of charge estimation based on the improved Thevenin equivalent circuit model and Kalman filtering
Lithium iron phosphate (LiFePO4) batteries are widely used as power batteries for electric vehicle applications. For safety issues, it is important to estimate the State of Charge (SOC) of a battery accurately. The improved Thevenin equivalent circuit model is established according to the characteristics of the LiFePO4 battery, and the model parameters are identified by experimental testing. Furthermore, a novel algorithm of SOC online estimation is proposed, which combines the open-circuit voltage method, ampere-hour integration, and Kalman filtering. The simulations and experimental results show that the improved Thevenin equivalent circuit model can enhance the accuracy of SOC estimation. This proposed algorithm could estimate the SOC precisely even with inaccurate initial values and current measurement errors and distinguish the performances between the batteries. The performance of the proposed SOC estimation method when the voltage sensor is unavailable has been investigated and presented as well. From the characteristics mentioned above, this novel approach is able to guarantee the reliability and safety of the batteries.
LiFePO4 battery state of charge estimation based on the improved Thevenin equivalent circuit model and Kalman filtering
Lithium iron phosphate (LiFePO4) batteries are widely used as power batteries for electric vehicle applications. For safety issues, it is important to estimate the State of Charge (SOC) of a battery accurately. The improved Thevenin equivalent circuit model is established according to the characteristics of the LiFePO4 battery, and the model parameters are identified by experimental testing. Furthermore, a novel algorithm of SOC online estimation is proposed, which combines the open-circuit voltage method, ampere-hour integration, and Kalman filtering. The simulations and experimental results show that the improved Thevenin equivalent circuit model can enhance the accuracy of SOC estimation. This proposed algorithm could estimate the SOC precisely even with inaccurate initial values and current measurement errors and distinguish the performances between the batteries. The performance of the proposed SOC estimation method when the voltage sensor is unavailable has been investigated and presented as well. From the characteristics mentioned above, this novel approach is able to guarantee the reliability and safety of the batteries.
LiFePO4 battery state of charge estimation based on the improved Thevenin equivalent circuit model and Kalman filtering
Xu, Zhu (author) / Gao, Shibin (author) / Yang, Shunfeng (author)
2016-03-01
14 pages
Article (Journal)
Electronic Resource
English
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