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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识别

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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交生活和工业生产中起着重要作用。由于性能优异,锂离子电池已被广泛应用于不同的电源需求。电池管理系统(BMS)是锂离子电池应用的关键部分。准确估算电池状态是BMS的核心功能,依赖于电池模型和模型识别参数。为了精确地在线获得动态参数,本文修改了牧羊人数学电池模型,并分离了模型参数的连接,便于迭代计算。然后使用最小二乘法通过动态参数估计实时地跟踪锂离子电池的状态变化。通过模拟和实验证明了有效性。

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