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首页> 外文会议>IEEE Transportation Electrification Conference and Expo >Lightweight Parameter Estimation for the Third-Order Lithium-Ion Battery Model Based on Non-iterative Algorithm
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Lightweight Parameter Estimation for the Third-Order Lithium-Ion Battery Model Based on Non-iterative Algorithm

机译：基于非迭代算法的三阶锂离子电池模型轻量化参数估计

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摘要

Equivalent circuit battery models can cooperate with electric vehicle models well at a system level, and can reduce largely complexity compared with electrochemical models. The equivalent circuit with more RC branches has a higher accuracy but also higher complexity. Traditional parameter estimation tools rely heavily on hardware and software. This research aims to come up with a lightweight parameter estimation algorithm however to guarantee the accuracy of the third-order equivalent circuit. It proves that the algorithm has a reliable result for the energy storage system simulation and SOC estimation. The mean residual error achieves to 0.06% or 1.98 mV, which can meet basically the engineering requirements.
机译：等效电路电池模型可以在系统级别上与电动汽车模型很好地协作，并且与电化学模型相比可以大大降低复杂性。具有更多RC支路的等效电路具有较高的精度，但也具有较高的复杂度。传统的参数估计工具严重依赖于硬件和软件。本研究旨在提出一种轻量级的参数估计算法，但要保证三阶等效电路的准确性。证明了该算法在储能系统仿真和SOC估计中具有可靠的结果。平均残留误差达到0.06％或1.98 mV，基本可以满足工程要求。

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