基于DUFK的动力电池内阻与SoC估算

DUFK-based Power Battery Internal Resistance and SoC Estimation

对电池荷电状态(SoC)与健康状态(SoH)做出合理准确的估计关系到电动汽车能量分配与安全运行。文章以18650型锂离子动力电池为研究对象,依据电池Randle等效电路模型的状态空间方程,提出采用双无迹卡尔曼滤波算法(Dual Unscented Kalman filter,DUFK)联合在线估算电池SoC与欧姆内阻。通过电池的HPPC实验数据验证表明,双无迹卡尔曼滤波算法能够准确地跟踪电池在整个实验过程中SoC和欧姆内阻的变化,SoC的估算误差在2%以内;欧姆内阻的估算结果与真实值具有良好的一致性,从而可为电池SoH的判断提供参考依据。最后验证了算法对SoC初始值误差的鲁棒性。

The reasonable and accurate estimation of the battery state of charge（ SoC） and state of healthy（ SoH） is crucial for the energy distribution and safety in electric vehicles. The 18650 type lithium-ion power battery is chose as the study object in this paper,based on the Randle equivalent and its state-space equations,the dual unscented Kalman filter algorithm is proposed to realize the dual estimation of the battery SoC and ohmic resistance. And the method is investigated with the HPPC experiment. The result shows that the method is able to track the battery SoC and ohmic resistor accurately,the SoC estimation error is within 2%,the estimated ohmic resistance matches the real value well,which provide reference to the judgment of the battery SoH. The robustness of the method for the SoC initial value error is validated at last.