基于PNGV模型储能锂电池参数辨识及SOC估算研究  

Study on Parameter Identification and SOC Estimation Based on PNGV Model for Energy Storage Lithium-ion Battery

作　　者：甘屹[1] 李杨 姚俊[2] 

机构地区：[1]上海理工大学机械工程学院,上海200093 [2]上海电气集团股份有限公司中央研究院,上海200070

出　　处：《能源研究与信息》2017年第4期194-199,共6页Energy Research and Information

摘　　要：锂电池因具有比能量高、循环寿命长、对环境无污染等优点,在储能系统中已逐渐得到应用.准确估算锂电池的荷电状态(SOC)可防止电池过充、过放,保障电池安全、充分地使用.为了精确估算储能锂电池SOC,基于PNGV(partnership for a new generation of vehicles)电池等效模型,利用递推最小二乘法(RLS)对模型参数进行在线辨识和实时修正,增强了系统的适应性.结合安时法、开路电压法和PNGV模型,提出了一种实时在线修正SOC算法.根据实验数据,建立了仿真模型,以验算模型和SOC估算算法的精度.仿真结果表明,PNGV模型能真实地模拟电池特性,且能有效地提高SOC估算精度,适合长时间在线估算储能锂电池的SOC.Lithium-ion batteries have been gradually applied toenergy storage system with the advantages of high energy density , long cycle life , no pollution to environment and so on. Accurate state- of-charge （SOC） estimation of lithium-ion battery can avoid the overcharge or over-discharge , ma8e fu l l use of the battery and guarantee the battery safety.In order to accurately estimate SOC for energy storage lithium-ion battery , recursive least squares method（RLS） was adopted for online identification and real-time modification of the model parameters to enhance the system adaptability according to the equivalent battery model of partnership for a new generation vehicles （P N G V ） . Combined with Ampere-hour method, open circuit voltage method and PNGV model, an online modified SOC algorithm was proposed. The simulation model was established using the experimental data to verify the accuracy of the model and the SOC estimation. The simulation results salgorithm could effectively improve the accuracy of SOC estimation, and was sestimation of SOC for energy storage lithium-ion battery for a long time.

关 键 词：锂电池 PNGV模型 荷电状态 递推最小二乘法 

分 类 号：TM912[电气工程—电力电子与电力传动]