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Electromotive force characterization of secondary battery cells using estimated electrolyte molality

机译:使用估计的电解质摩尔浓度表征二次电池的电动势

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摘要

Existing methods for electromotive force (EMF) characterization that make use of readily available data, such as terminal voltage and applied current, require a significant time commitment and a constant temperature environment. Both linear interpolation and extrapolation rely on state-of-charge (SOC) calculation by Coulomb-counting which only serves to reduce the accuracy of the resulting EMF-SOC curve(s). A battery management system requires accurate EMF-SOC data for periodic recalibration otherwise it cannot apply proper charge control. This paper presents an alternative concentration-based method for EMF characterization and the key lies in the fact that molality is not influenced by temperature. A modified version of the Nernst equation and temperature-compensated open-circuit voltage measurements are used to estimate the molality when the cell is at rest. During operation, the energy into or out of the cell is mapped to changes in the estimated molality to calculate the EMF as the cell charges or discharges. The concentration-based method is verified using experimental data from valve-regulated lead-acid cells and its EMF curves are compared to those of linear interpolation and extrapolation. The proposed method has less stringent practical requirements and validation results indicate a significant improvement in accuracy and applicability over the existing methods.
机译:现有的电动势(EMF)表征方法利用易于获得的数据(例如端子电压和施加的电流)需要大量的时间投入和恒温环境。线性内插法和外插法都依赖于通过库仑计数进行的荷电状态(SOC)计算,这仅用于降低所得EMF-SOC曲线的精度。电池管理系统需要准确的EMF-SOC数据以进行定期重新校准,否则无法应用适当的充电控制。本文提出了另一种基于浓度的EMF表征方法,关键在于摩尔浓度不受温度的影响。 Nernst方程的修改版本和温度补偿的开路电压测量值用于估算电池静止时的摩尔浓度。在操作过程中,进入或流出电池的能量被映射为估计摩尔浓度的变化,以计算电池充电或放电时的EMF。使用阀调节的铅酸电池的实验数据验证了基于浓度的方法,并将其EMF曲线与线性内插法和外推法进行了比较。所提出的方法具有不太严格的实际要求,并且验证结果表明,与现有方法相比,准确性和适用性有了显着提高。

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