基于云端数据充电初期片段的电池极化参数辨识

打开文本图片集

Identification of battery polarization parameters based on initial charging segment of cloud data

WANG Limei1，CUI Yanwei1，SUN Jingjing1，ZHAO Xiuliang*2，LIU Liang1， PAN Chaofeng

（1.AutomotiveEngineeringResearch Institute，Jiangsu University，Zhenjiangl2ol3，China； 2.SchoolofAutomotiveandTrafcEngineering，Jiangsu University，Zhenjiang2l2ol3，China）

Abstract：A benchmark polarization parameter identification method was proposed based on cloud data toenhance the accuracy and thespeed of online identificationof battery polarization parameters.The characteristics of battery polarization parameters were investigated by conducting charge-discharge pulse experiments.A method analogous wasemployed by utilizing the initialcharging segment from cloud data throughthe Hybrid Pulse Power Characterization （HPPC）teststoobtain the charging polarization parameters. The Variable Forgeting Factor Recursive Least Squares （VFFRLS）algorithm wasapplied with the identified charging polarization parametersas constraints to compute the discharging polarization parameters.The results indicated that thismethodyieldedbattery timeconstantsranging from 34～53s ，and the polarization parameters remained invariant with respect to the current rate under corresponding low current rates in the cloudenvironment.Thecalculated chargingpolarizationresistanceandpolarizationcapacitancealignedwel with laboratory results.The convergence speed of the proposed constrained online identification method was improvedbyatleast 6% compared with the unconstrained identification method.

Keywords：batterycharginganddischarging；polarizationparameter；clouddata；of-lineidentification；hybrid pulse power characterization （HPPC） analogy；variable forgetting factor recursive least square （VFFRLS）algorithm

电池作为电动汽车（electricvehicles，EVs）动力电池系统和储能系统的核心组件，其性能直接影响系统的整体效率和可靠性。（剩余12488字）