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首页> 外文期刊>Journal of power electronics >Adaptive State-of-Charge Estimation Method for an Aeronautical Lithium-ion Battery Pack Based on a Reduced Particle-unscented Kalman Filter
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Adaptive State-of-Charge Estimation Method for an Aeronautical Lithium-ion Battery Pack Based on a Reduced Particle-unscented Kalman Filter

机译：基于减少粒子无味卡尔曼滤波器的航空锂离子电池组自适应荷电状态估计方法

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摘要

A reduced particle-unscented Kalman filter estimation method, along with a splice-equivalent circuit model, is proposed for the state-of-charge estimation of an aeronautical lithium-ion battery pack. The linearization treatment is not required in this method and only a few sigma data points are used, which reduce the computational requirement of state-of-charge estimation. This method also improves the estimation covariance properties by introducing the equilibrium parameter state of balance for the aeronautical lithium-ion battery pack. In addition, the estimation performance is validated by the experimental results. The proposed state-of-charge estimation method exhibits a root-mean-square error value of 1.42% and a mean error value of 4.96%. This method is insensitive to the parameter variation of the splice-equivalent circuit model, and thus, it plays an important role in the popularization and application of the aeronautical lithium-ion battery pack.
机译：针对航空锂离子电池组的荷电状态估计，提出了一种简化的无味卡尔曼滤波器估计方法以及等效拼接电路模型。该方法不需要线性化处理，仅使用了几个sigma数据点，从而减少了荷电状态估计的计算需求。该方法还通过为航空锂离子电池组引入平衡的平衡参数状态来改善估计协方差特性。另外，通过实验结果验证了估计性能。提出的荷电状态估计方法具有1.42％的均方根误差值和4.96％的平均误差值。该方法对剪接等效电路模型的参数变化不敏感，因此在航空锂离子电池组的推广和应用中起着重要的作用。

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