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MODELING CHANGES IN THE STATE-OF-CHARGE OPEN CIRCUIT VOLTAGE CURVE BY USING REGRESSED PARAMETERS IN A REDUCED ORDER PHYSICS BASED MODEL
MODELING CHANGES IN THE STATE-OF-CHARGE OPEN CIRCUIT VOLTAGE CURVE BY USING REGRESSED PARAMETERS IN A REDUCED ORDER PHYSICS BASED MODEL
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机译:在基于降阶物理的模型中,通过使用混合参数对荷电状态下的开路电压曲线进行建模
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摘要
A method for modeling changes in the state of charge vs. open circuit voltage (SOC-OCV) curve for a lithium-ion battery cell as it ages. During battery pack charging, voltage and current data are gathered for a battery cell. A set of state equations are used to determine the stoichiometry and state of charge of the cathode half-cell based on the charging current profile over time. The voltage and current data, along with the stoichiometry and state of charge of the cathode half-cell, are then used to estimate maximum and minimum solid concentration values at the anode, using an error function parameter regression/optimization. With stoichiometric conditions at both the cathode and anode calculated, the cell's capacity and a new SOC-OCV curve can be determined.
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