Modelling of HEV Lithium-Ion High Voltage Battery Pack using Dynamic Data

Abstract

A new approach is proposed for developing a model for High Voltage (HV) Lithium-ion (Li-Ion) battery pack using Hybrid Electrical Vehicle (HEV) drive cycles data. A variety of drive cycle's data have been collected from the test vehicle at various operating conditions. The equivalent electrical circuit for the HV battery is formulated using mathematical equations and discrete state space equations. The Open Circuit Voltage (OCV), Offset Voltage at Zero Load conditions (VZL), battery pack internal resistance (Rbatt) are considered as various components of the mathematical equations and battery pack RC filter states are represented using discrete state space equations at various battery temperature (Batt Temp) conditions (-70C to 450C). The parameter estimation problem is then considered as the problem of simultaneously estimating the parameters of all the coefficients formulated in the battery pack mathematical and state space equations. This is mathematically posed as a constrained optimization problem and a variant of genetic algorithm (GA) is used to solve it. Modelling is done using MATLAB®/Simulink® tools. The developed model is validated on actual vehicle drive cycle data. The results obtained by the proposed approach are closely matching with the actual battery response under different drive cycles. The distinction of the approach is that it does not call for any lab tests, additional instrumentation and cell level measurements yet serves the purpose of fair fidelity model for the design, analysis and control of the HEV powernet.