基于改进PNGV模型的动力锂电池SOC精确估计

作为动力锂电池的核心参数,锂电池的荷电状态(SOC)的精度估算决定了储能系统控制的精度和管理的可靠性,目前业内对于SOC估计算法的研究不够深入,导致精度低,计算量大,并且依赖于初始值精度,工程应用难度大,以至于动力锂电池管理系统的精确控制和管理难以实现。对电池等效电路PNGV模型进行改进,提高了模型精度,并结合拓展卡尔曼滤波算法(EKF)实现了高精度的SOC估计,通过电池实测和仿真验证,该算法提高了SOC估算精度,解决了SOC估计依赖初值精度问题,具有较高的工程应用价值。

Accurate SOC estimation of power Li-ion battery based on improved PNGV model

Accurate SOC estimation was difficult to traditional algorithm,so that the battery management system (BMS) couldn't work as better as we want.To solve this problem,the PNGV model was improved and its parameters were identified.The SOC estimation was estimated using extended Kalman filter (EKF) with the improved PNGV.After the experiments and simulations,it's clear that the method meets the requirements.