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基于卡尔曼滤波算法的锂离子电池荷电状态估算
资料介绍
提出并建立了一种锂离子电池二阶电路等效动态模型,在对模型的适应性验证的基础上,设计了一种卡尔曼滤波算法来估算锂离子电池荷电状态。仿真和实验结果表明,卡尔曼滤波算法能有效减少测量噪声以及同一生产工艺下电池的参数不稳定性所带来的影响,并显示了很高的精确度,其中快速估算的精确度为96.1%,缓慢估算的精确度为99.0%。
An easy electric model of the cell(2nd order equivalent circuit model) is identified and verified, and a Kalman fil ter methed is applied to estimate SoC. The simulation and test results on two different cells of the same manufacture and typology show that the algorithm is able to reject the effect of measurement noise and parametric uncertainties with high accuracy. The pre cision of the fast estimation is 96.1%, and the slow estimation is 99.0%.
部分文件列表
文件名 | 大小 |
基于卡尔曼滤波算法的锂离子电池荷电状态估算.pdf | 196K |
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