Adaptive Estimation of Li-ion Battery Model Parameters

A Master of Science thesis in Electrical Engineering by Daniyal Ali entitled, "Adaptive Estimation of Li-ion Battery Model Parameters," submitted in May 2016. Thesis advisor is Dr. Shayok Mukhopadhyay and thesis co-advisor is Dr. Habib-ur Rehman. Soft and hard copy available.

Saved in:
Bibliographic Details
Main Author: Ali, Daniyal (author)
Format: doctoralThesis
Published: 2016
Subjects:
Online Access:http://hdl.handle.net/11073/8327
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1864513434115112960
author Ali, Daniyal
author_facet Ali, Daniyal
author_role author
dc.contributor.none.fl_str_mv Mukhopadhyay, Shayok
Rehman, Habib-ur
dc.creator.none.fl_str_mv Ali, Daniyal
dc.date.none.fl_str_mv 2016-06-06T06:03:58Z
2016-06-06T06:03:58Z
2016-05
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.identifier.none.fl_str_mv 35.232-2016.19
http://hdl.handle.net/11073/8327
dc.language.none.fl_str_mv en_US
dc.subject.none.fl_str_mv Adaptive Parameter Estimation
Li-ion Battery
Universal Adaptive Stabilization
Lithium ion batteries
dc.title.none.fl_str_mv Adaptive Estimation of Li-ion Battery Model Parameters
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/doctoralThesis
description A Master of Science thesis in Electrical Engineering by Daniyal Ali entitled, "Adaptive Estimation of Li-ion Battery Model Parameters," submitted in May 2016. Thesis advisor is Dr. Shayok Mukhopadhyay and thesis co-advisor is Dr. Habib-ur Rehman. Soft and hard copy available.
format doctoralThesis
id aus_8d61331e58bd48a206ceff6c02a755f3
identifier_str_mv 35.232-2016.19
language_invalid_str_mv en_US
network_acronym_str aus
network_name_str aus
oai_identifier_str oai:repository.aus.edu:11073/8327
publishDate 2016
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
spelling Adaptive Estimation of Li-ion Battery Model ParametersAli, DaniyalAdaptive Parameter EstimationLi-ion BatteryUniversal Adaptive StabilizationLithium ion batteriesA Master of Science thesis in Electrical Engineering by Daniyal Ali entitled, "Adaptive Estimation of Li-ion Battery Model Parameters," submitted in May 2016. Thesis advisor is Dr. Shayok Mukhopadhyay and thesis co-advisor is Dr. Habib-ur Rehman. Soft and hard copy available.This work presents a novel application of a high gain adaptive observer-based technique for Lithium-ion (Li-ion) battery modeling. The model used in this work was originally developed by Chen and Mora. However, in Chen and Mora's original work, the parameters required for the battery model were estimated through intensive experimentation. In contrast, this work presents an adaptive observer for estimating the battery model parameters. This results in the reduction of experimental effort required to estimate battery model parameters. The selected model (Chen and Mora's model) requires twenty one parameters to accurately model a Li-ion battery. This work initially proposes three variations of a high gain adaptive observer-based technique to adaptively tune fifteen of the required parameters accurately. The remaining six parameters related to the shape of the no-load electromotive-force (EMF) curve are obtained via a voltage relaxation test. Based on observations made during simulations of the above proposed techniques, an improved estimation technique is proposed in the latter half of this document, and experimental results validating the proposed technique are presented. Experiments show that the model obtained through this technique is independent of the magnitude and type of load. The improved parameter estimation technique is justified using rigorous mathematical analysis. The proposed improved technique can be used either online or offline for estimating battery model parameters. This may be valuable for automatically updating battery models parameters on-board future smart vehicles in real time.College of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE)Mukhopadhyay, ShayokRehman, Habib-ur2016-06-06T06:03:58Z2016-06-06T06:03:58Z2016-05info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdfapplication/pdf35.232-2016.19http://hdl.handle.net/11073/8327en_USoai:repository.aus.edu:11073/83272025-06-26T12:30:43Z
spellingShingle Adaptive Estimation of Li-ion Battery Model Parameters
Ali, Daniyal
Adaptive Parameter Estimation
Li-ion Battery
Universal Adaptive Stabilization
Lithium ion batteries
status_str publishedVersion
title Adaptive Estimation of Li-ion Battery Model Parameters
title_full Adaptive Estimation of Li-ion Battery Model Parameters
title_fullStr Adaptive Estimation of Li-ion Battery Model Parameters
title_full_unstemmed Adaptive Estimation of Li-ion Battery Model Parameters
title_short Adaptive Estimation of Li-ion Battery Model Parameters
title_sort Adaptive Estimation of Li-ion Battery Model Parameters
topic Adaptive Parameter Estimation
Li-ion Battery
Universal Adaptive Stabilization
Lithium ion batteries
url http://hdl.handle.net/11073/8327