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Dynamic Parameter Identification of Mathematical Model of Lithium-Ion Battery Based on Least Square Method

机译:基于最小二乘法的锂离子电池数学模型动态参数辨识

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Battery as energy storage equipment plays an important role in social life and industrial production. Lithium-ion batteries have already been widely used in different power demand occasions because of excellent performance. The battery management system (BMS) is the critical part of lithium-ion battery applications. Accurately estimating battery status is the core function of BMS, which relies on the battery model and parameters of model identification. In order to obtain the dynamical parameters precisely online, this paper modifies Shepherd mathematical battery model and decouples connectivity of model parameters to facilitate iterative calculation. Then use least squares method to track the state change of lithium-ion battery in real time through dynamic parameters estimation. The validity is demonstrated by simulation and experiment.
机译:电池作为储能设备在社会生活和工业生产中起着重要作用。锂离子电池由于其出色的性能已被广泛用于不同的电力需求场合。电池管理系统(BMS)是锂离子电池应用的关键部分。准确估计电池状态是BMS的核心功能,它依赖于电池模型和模型识别参数。为了精确地在线获得动力学参数,本文修改了Shepherd数学电池模型,并解耦了模型参数的连通性,以利于迭代计算。然后采用最小二乘法通过动态参数估计实时跟踪锂离子电池的状态变化。仿真和实验证明了该方法的有效性。

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