A comparison of modelling approaches for the evaluation of the electrical performance of secondary batteries in battery management systems (BMS)

Mirko D'Adamo

Key information

Authors:

Mirko D'Adamo (Mirko D'Adamo)

Supervisors:

Francisco Díaz-González; Luísa Margarida Dias Ribeiro de Sousa Martins (Luísa Margarida Martins)

Published in

October 12, 2021

Abstract

In hybrid electric vehicle battery packs, battery management systems (BMS) must approximate values that describe the pack’s current operating state. Battery state of charge(SOC) and instantaneous usable power are examples of these. The estimation process must respond to changing cell characteristics as cells age in order to produce reliable predictions over the pack’s lifespan. To suggest a system based on extended Kalman filtering(EKF) that can achieve these objectives on a lithium-ion battery pack with NMC/graphite chemistry. This report discusses several mathematical cell models that can be used in connection with this approach. The HEV implementation is a harsh environment, with rate specifications up to and above 20 degrees Celsius and very complex rate profiles. In comparison, portable-electronic devices with steady power output and fractional C rates are relatively benign. Methods for calculating SOC that work well in portable electronics cannot work well in HEVs. If the HEV requires precise SOC estimation, then highly accurate cell model is needed. When the cell model input is equal to the cell current, the target is to make the cell model output resemble the cell terminal voltage under load as near as possible at all times. In this research report, three different models for cell to estimate terminal voltage have been implemented in MATLAB/Simulink environment. The three mathematical models are further implemented in a fourth electrical model called Thevenin Model. Results are presented to demonstrate the terminal estimation voltage as close to actual voltage and SOC estimation for all the proposed cell models.