1673-159X

CN 51-1686/N

基于EKF-UKF模型的锂电池电源参数更新和估计

Update and Estimation Method of Power Parameters of Lithium Battery Based on EKF-UKF Model

  • 摘要: 由于对锂电池的电量参数直接建模存在困难,不便于实现对电源参数的估计,本文提出基于EKF-UKF模型算法直接对锂电池的状态参数进行建模。应用EKF算法获取的电池模型参数、UKF算法观测锂电池的荷电状态,在实现对锂电池进行电量估计的同时,完成对电池模型参数的实时更新,有效地减少漂移电流对估算精度的影响。工况测试表明:这种复合算法复杂度低,能快速实现对锂电池的参数估计,且具有较高的估计精度和鲁棒性。

     

    Abstract: It is difficult to model the electric quantity parameters of lithium battery directly and it is not convenient to estimate the power supply parameters.This paper proposes a solution to model the state parameters of lithium battery based on EKF-UKF model algorithm directly. The battery model parameters obtained by EKF algorithm and UKF algorithm are applied to observe the charge state of lithium battery. In this way, the battery model parameters can be updated in real time while the battery quantity estimation is carried out, and the influence of drifting current on the estimation accuracy can be effectively reduced. The experimental results show that this compounding algorithm is low complexity, high accuracy and robustness, and can quickly estimate the parameters of lithium battery.

     

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