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Model identification and parameter estimation for LiFePO4 batteries

机译:LiFePO4电池的模型识别和参数估计

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摘要

We propose a method for dynamic model identification and parameter estimation of LiFePO4 cells based on current pulse measurements and electrochemical impedance spectroscopy (EIS). Modelling efforts were focused on diffusion as the predominant dynamic process relevant to battery management systems. An equivalent circuit model approach was adopted with parameters dependant on temperature and state of charge (SOC). The model was parameterised at 50°C, 20°C, 0°C and -30°C and between 10% and 100% SOC. Initial parameter estimations for the model identification procedure were informed by EIS. The model was validated (at constant SOC), for the entire temperature range and at C-rates between C/2 and 9C, by voltage simulation based on a dynamic drive cycle profile. Maximal residuals did not exceed 68 mV or 2% of the nominal cell voltage (Vnom) and root-mean-squared deviations remained within 28 mV or 0.8% of Vnom at all temperatures and C-rates.
机译:我们提出了一种基于电流脉冲测量和电化学阻抗谱(EIS)的LiFePO 4 电池动态模型识别和参数估计的方法。建模工作的重点是扩散,这是与电池管理系统相关的主要动态过程。采用等效电路模型方法,其参数取决于温度和电荷状态(SOC)。在50°C,20°C,0°C和-30°C以及10%至100%SOC之间对模型进行参数设置。 EIS通知了模型识别过程的初始参数估计。通过基于动态驱动循环曲线的电压仿真,在整个温度范围内以及C / 2和9C之间的C速率下,对模型进行了验证(恒定SOC)。最大残留量不超过68 mV或标称电池电压(Vnom)的2%,并且在所有温度和C速率下,均方根偏差均保持在28 mV或Vnom的0.8%之内。

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