Abstract
Modeling and state of charge (SOC) estimation of Lithium cells are crucial techniques of the lithium battery management system. The modeling is extremely complicated as the operating status of lithium battery is affected by temperature, current, cycle number, discharge depth and other factors. This paper studies the modeling of lithium iron phosphate battery based on the Thevenin’s equivalent circuit and a method to identify the open circuit voltage, resistance and capacitance in the model is proposed. To improve the accuracy of the lithium battery model, a capacity estimation algorithm considering the capacity loss during the battery’s life cycle. In addition, this paper solves the SOC estimation issue of the lithium battery caused by the uncertain noise using the extended Kalman filtering (EKF) algorithm. A simulation model of actual lithium batteries is designed in Matlab/Simulink and the simulation results verify the accuracy of the model under different operating modes.
Highlights
Wind power generation has been developing rapidly in recent years for being pollution-free and sustainable [1,2,3,4]
4 Results The data is collected from experiments on domestic lithium iron phosphate batteries with a nominal capacity of 40 AH and a nominal voltage of 3.2 V
The state of charge (SOC) is estimated with extended Kalman filtering (EKF) under certain current and voltage for verification
Summary
Wind power generation has been developing rapidly in recent years for being pollution-free and sustainable [1,2,3,4]. Wind power curtailment has become a prominent problem due to the constraints imposed by power dispatch and wind power’s fluctuation and unpredictability. Energy storage is an effective means to solve the wind power curtailment problem as it can dynamically absorbs and releases energy. It realizes the temporal transition of power and energy to effectively eliminate wind power curtailment caused by the system’s poor peak regulation ability. Electrochemical energy storage exemplified by lithium battery has been applied in renewable power generation for its high controllability, modularity, energy density and conversion efficiency [5]. Multiple lithium battery energy storage demonstration projects have been conducted throughout China, including Zhangbei County in Zhangjiakou of Hebei Province (14 MW/63WMh lithium phosphate battery system), Baoqing energy storage station in Shenzhen
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