Battery Energy Management Techniques for Electric Vehicle Traction System
A Master of Science thesis in Electrical Engineering by Ahmed Sayed AbdelAal AbdelAziz entitled, “Battery Energy Management Techniques for Electric Vehicle Traction System”, submitted in November 2019. Thesis advisor is Dr. Shayok Mukhopadhyay and thesis co-advisor is Dr. Habibur Rehman. Soft copy i...
Saved in:
| Main Author: | |
|---|---|
| Format: | doctoralThesis |
| Published: |
2019
|
| Subjects: | |
| Online Access: | http://hdl.handle.net/11073/16559 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1864513440818659328 |
|---|---|
| author | AbdelAziz, Ahmed Sayed AbdelAal |
| author_facet | AbdelAziz, Ahmed Sayed AbdelAal |
| author_role | author |
| dc.contributor.none.fl_str_mv | Mukhopadhyay, Shayok Rehman, Habib-ur |
| dc.creator.none.fl_str_mv | AbdelAziz, Ahmed Sayed AbdelAal |
| dc.date.none.fl_str_mv | 2019-11 2020-01-20T09:55:51Z 2020-01-20T09:55:51Z |
| dc.format.none.fl_str_mv | application/pdf application/pdf |
| dc.identifier.none.fl_str_mv | 35.232-2019.48 http://hdl.handle.net/11073/16559 |
| dc.language.none.fl_str_mv | en_US |
| dc.subject.none.fl_str_mv | Battery energy management Field-oriented control Induction motor Model predictive control Fuzzy logic controller Weight tuning |
| dc.title.none.fl_str_mv | Battery Energy Management Techniques for Electric Vehicle Traction System |
| 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 Ahmed Sayed AbdelAal AbdelAziz entitled, “Battery Energy Management Techniques for Electric Vehicle Traction System”, submitted in November 2019. Thesis advisor is Dr. Shayok Mukhopadhyay and thesis co-advisor is Dr. Habibur Rehman. Soft copy is available (Thesis, Approval Signatures, Completion Certificate, and AUS Archives Consent Form). |
| format | doctoralThesis |
| id | aus_ced05b82162164383fca7f9b3da54d05 |
| identifier_str_mv | 35.232-2019.48 |
| language_invalid_str_mv | en_US |
| network_acronym_str | aus |
| network_name_str | aus |
| oai_identifier_str | oai:repository.aus.edu:11073/16559 |
| publishDate | 2019 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Battery Energy Management Techniques for Electric Vehicle Traction SystemAbdelAziz, Ahmed Sayed AbdelAalBattery energy managementField-oriented controlInduction motorModel predictive controlFuzzy logic controllerWeight tuningA Master of Science thesis in Electrical Engineering by Ahmed Sayed AbdelAal AbdelAziz entitled, “Battery Energy Management Techniques for Electric Vehicle Traction System”, submitted in November 2019. Thesis advisor is Dr. Shayok Mukhopadhyay and thesis co-advisor is Dr. Habibur Rehman. Soft copy is available (Thesis, Approval Signatures, Completion Certificate, and AUS Archives Consent Form).Dependency of the modern society on fossil fuels has created significant levels of environmental pollution. Therefore, the automotive industry is moving towards a cleaner transportation system in the form of battery electric vehicles (BEV). A major issue with BEVs is the rapid decline in the battery runtime and lifetime represented by the State of Charge (SOC) and State of Health (SOH) respectively. Consequently, this work focuses on controlling the speed of an induction motor driven electric vehicle (EV) traction system while minimizing the SOC and SOH degradation of a Lithium-ion (Li-ion) battery bank. The first objective is designing a battery energy management (BEM) technique for an indirect field oriented (IFO) induction motor drive system using two cascaded fuzzy logic controllers (CSFLC). In this technique, the first fuzzy logic controller (FLC) generates the desired current to regulate the motor speed while the second FLC limits the current based on the battery SOC. In the second technique, a model predictive controller (MPC) regulates the motor speed while an FLC adjusts the input weight of the MPC (named FMPC), which takes the battery SOC into account when generating the current. The above mentioned controllers are implemented on an EV traction system with the New European Drive Cycle (NEDC) and the Supplemental Federal Test Procedure (US06). There is a decrease in SOC degradation of 8.1% and 5.88%, decrease in SOH degradation of 8.3% and 6.4%, and a reduction of 8.21% and 5.36% in energy consumption for the CSFLC with the NEDC and US06 drive cycles respectively. There is a decrease in SOC degradation of 4.29% and 6.57%, decrease in SOH degradation of 4.3% and 6%, and a reduction of 4.37% and 6.1% in energy consumption for the FMPC with the NEDC and US06 drive cycles respectively. The absolute average error in motor speed for the CSFLC is 3.7 RPM and 6.93 RPM as compared to the 1.28 RPM and 1.69 RPM for the FLC. While, the FMPC has 3.02 RPM and 3.13 RPM motor speed error as compared to 1.17 RPM and 1.19 RPM for the MPC with the NEDC and US06 drive cycles.College of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE)Mukhopadhyay, ShayokRehman, Habib-ur2020-01-20T09:55:51Z2020-01-20T09:55:51Z2019-11info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdfapplication/pdf35.232-2019.48http://hdl.handle.net/11073/16559en_USoai:repository.aus.edu:11073/165592025-06-26T12:23:47Z |
| spellingShingle | Battery Energy Management Techniques for Electric Vehicle Traction System AbdelAziz, Ahmed Sayed AbdelAal Battery energy management Field-oriented control Induction motor Model predictive control Fuzzy logic controller Weight tuning |
| status_str | publishedVersion |
| title | Battery Energy Management Techniques for Electric Vehicle Traction System |
| title_full | Battery Energy Management Techniques for Electric Vehicle Traction System |
| title_fullStr | Battery Energy Management Techniques for Electric Vehicle Traction System |
| title_full_unstemmed | Battery Energy Management Techniques for Electric Vehicle Traction System |
| title_short | Battery Energy Management Techniques for Electric Vehicle Traction System |
| title_sort | Battery Energy Management Techniques for Electric Vehicle Traction System |
| topic | Battery energy management Field-oriented control Induction motor Model predictive control Fuzzy logic controller Weight tuning |
| url | http://hdl.handle.net/11073/16559 |