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Accurate Lithium-ion battery parameter estimation with continuous-time system identification methods

机译:连续时间系统识别方法准确估算锂离子电池参数

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The modeling of Lithium-ion batteries usually utilizes discrete-time system identification methods to estimate parameters of discrete models. This paper adopts direct continuous-time system identification methods to estimate the parameters of equivalent circuit models for Lithium-ion batteries. Compared with discrete-time system identification methods, the continuous-time system identification methods provide more accurate estimates to both fast and slow dynamics in battery systems and are less sensitive to perturbations. A case of a 2nd-order equivalent circuit model is studied which shows that the continuous-time estimates are more robust to high sampling rates, measurement noises and rounding errors. Simulation and experiment results validate the analysis and demonstrate the superiority of the continuous-time system identification methods in battery applications.
机译:锂离子电池的建模通常利用离散时间系统识别方法来估计离散模型的参数。本文采用直接连续时间系统辨识方法来估计锂离子电池等效电路模型的参数。与离散时间系统识别方法相比,连续时间系统识别方法可对电池系统的快速和慢速动力学提供更准确的估计,并且对扰动不太敏感。以一个二阶等效电路模型为例,该模型表明连续时间估计对于高采样率,测量噪声和舍入误差更为稳健。仿真和实验结果验证了该分析结果,并证明了连续时间系统识别方法在电池应用中的优越性。

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