基于抗差UKF的动力锂电池SOC估计算法研究

Estimation of state of charge for Li-ion battery based on robust UKF

从锂离子电池模型的研究与优化入手,以自主设计的电池SOC仿真系统模型和硬件实验平台为基础,分析锂离子电池SOC预估算法中的粗差影响因素,建立一种新型基于抗差无迹Kalman滤波(UKF)的锂离子电池SOC预估方法。该方法将开路-AH法与抗差UKF估计理论相结合,克服传统估算方法无法消除累积误差的缺点。对照实验结果表明,新算法能够提高动力储能锂离子电池的SOC量测过程中的预估精度,对于促进动力储能锂离子电池的推广,提高动力储能锂离子电池组的能量储存能力、利用率和循环寿命有着重要的科学意义。

A new state of Charge （SOC） estimation method of battery based on the robust-UKF was proposed to improve the energy management performance of the lithium-ion battery. Our main efforts are： firstly, the model of the lithium-ion battery was studied in detail to optimize the parameters; secondly, the simulation model of the battery SOC estimation system was established and the hardware experimental platform was designed; thirdly, the gross error of the measurement vector in other estimation method was focused. The characteristic of our new algorithm was that the traditional method OCV-Ah and the roubust-UKF estimation theory were combined and the main problem called the accumulated error could be solved effectively. The experimental results indicate that the new algorithm can improve the accuracy of the SOC estimation results for lithium-ion battery. Besides, the method is very important for the capacity improvement of lithium-ion battery pack, the efficiency improvement of the energy system and the product promotion.