Walter Scott, Jr. College of Engineering

Graduate Exam Abstract

Syed Azam
M.S. Final
May 21, 2018, 9:00 am - 10:30 am
ECE Conference Room
BATTERY IDENTIFICATION, PREDICTION AND MODELLING
Abstract: In the paper a process of modelling
batteries for energy management
systems has been discussed.
With the increase demand of energy
management modelling, it is crucial
that modelling of the components
in an energy management model be
done properly, effectively, and with
least amount of
time. The process introduced in this
paper requires only one discharge
data to model a battery. The
internal parameters identified focuses
on the electrical behaviour rather than
on electrochemical
aspects of the battery. The battery
model presented here helps to predict
the discharge behavior
of the battery in multiple discharging
scenarios. In this modelling process,
Online Parameter Identification
technique has been used to identify
the parameters of the battery. The
parameters of the
battery identified in this paper to
predict the discharge behavior of a
battery are internal resistance,
polarization constant, nominal voltage
and actual capacity of a battery.
Shepherd’s equation and
MATLAB’s optimization toolbox was
used to identify the parameters
Adviser: Dr. Peter M Young
Co-Adviser: NA
Non-ECE Member: Dan Zimmerle, Powerhouse Energy Campus
Member 3: Dr. George Collins, ECE Department
Addional Members: NA
Publications:
1. https://doi.org/10.1109/ICCNC.2017.7876217
2. http://www.internetworkingindonesia.org/Issues/Vol8-No2-2016/iij-vol8-no2-2016.html
Program of Study:
ECE565
ECE530
ECE465
ECE611
ECE512
ECE569
ECE520
ECE699