ELEC3206: Semester 2, 2025

Units ELEC3206 Semester 2 2025 [Normal day]

Unit outline_

ELEC3206: Electrical Energy Conversion Systems

Semester 2, 2025 [Normal day] - Camperdown/Darlington, Sydney

Overview

This unit of study aims to give students a good understanding of electrical energy conversion techniques and equipment. Students who successfully complete this unit will: Have a broad view of electrical energy conversion systems including transformers, DC machines, induction machines and synchronous machines; Be able to analyse and solve problems in transformers and electric machines; Have gained confidence in their ability to undertake more advanced study in the power area. The following specific topics are covered: magnetic circuits, inductance, sinusoidal excitation, hysteresis and eddy current loss, permanent magnets, electromechanical energy conversion, singly-excited and doubly-excited systems, transformers, single-phase, equivalent circuit parameters, three-phase transformers, autotransformers, DC machines, separate excitation, shunt excitation, series excitation, and compound excitation, efficiency, armature reaction, induction machines, revolving field, equivalent circuit, squirrel cage machines, measurements of the parameters, DC resistance test, no-load test, blocked-rotor test, synchronous machines, field relationships, power-angle relationships, salient pole machines.

Unit details and rules

Academic unit	School of Electrical and Computer Engineering
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	Following concepts are assumed knowledge for this unit of study: familiarity with circuit theory, electronic devices, ac power, capacitors and inductors, and electric circuits such as three-phase circuits and circuits with switches, the use of basic laboratory equipment such as oscilloscope and power supply
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Jian Guo Zhu, jianguo.zhu@sydney.edu.au

Assessment

The census date for this unit availability is 1 September 2025

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Written exam ?	Final exam Final exam	50%	Formal exam period	2 hours	AI prohibited
Outcomes assessed:
Portfolio or journal	Lab report Group report for each lab experiment	24%	Multiple weeks	-	AI allowed
Outcomes assessed:
Written test ?	Mid-sem quiz In-semester quiz	10%	Week 07 Due date: 17 Sep 2025 at 09:00 Closing date: 17 Sep 2025	50 minutes	AI prohibited
Outcomes assessed:
Research analysis	Assignment Essay on a required topic	16%	Week 11 Due date: 24 Oct 2025 at 23:59 Closing date: 31 Oct 2025	-	AI allowed
Outcomes assessed:
= group assignment ?

Assessment summary

Lab report: 6 laboratory experiments.
Mid-sem quiz: to monitor students’ progress and provide feedback to students.
Assignment: assignment on current research and development of electrical energy conversion systems.
Final exam: final exam.
Participation: to encourage students to actively participate in tutorial discussions.

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name	Mark range	Description
High distinction	85 - 100
Distinction	75 - 84
Credit	65 - 74
Pass	50 - 64
Fail	0 - 49	When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see sydney.edu.au/students/guide-to-grades.

For more information see guide to grades.

Use of generative artificial intelligence (AI)

You can use generative AI tools for open assessments. Restrictions on AI use apply to secure, supervised assessments used to confirm if students have met specific learning outcomes.

Refer to the assessment table above to see if AI is allowed, for assessments in this unit and check Canvas for full instructions on assessment tasks and AI use.

If you use AI, you must always acknowledge it. Misusing AI may lead to a breach of the Academic Integrity Policy.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

Academic integrity

The University expects students to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

Our website provides information on academic integrity and the resources available to all students. This includes advice on how to avoid common breaches of academic integrity. Ensure that you have completed the Academic Honesty Education Module (AHEM) which is mandatory for all commencing coursework students

Penalties for serious breaches can significantly impact your studies and your career after graduation. It is important that you speak with your unit coordinator if you need help with completing assessments.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

Learning support

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Support for students

The Support for Students Policy reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

Weekly schedule

WK	Topic	Learning activity
Week 01	M0: UoS Introduction; M1: Review of electric power circuits;	Lecture (2 hr)
Week 01	Lab 0, Groups A&B	Practical (1.5 hr)
Week 02	M2: Magnetic circuits;	Lecture (2 hr)
	Tutorial 1: Week 2 - Group A, Week 3 - Group B	Tutorial (2 hr)
	Lab 1: Week 2 - Group B, Week 3 - Group A	Practical (3 hr)
	Lab 1 Report: Week 2 - Group B, Week 3 - Group A	Independent study (5 hr)
Week 03	M3: Transformers;	Lecture (2 hr)
Week 04	M3: Transformers;	Lecture (2 hr)
	Tutorial 2: Week 4 - Group A, Week 5 - Group B	Tutorial (2 hr)
	Lab 2: Week 4 - Group B, Week 5 - Group A	Practical (3 hr)
	Lab 2 Report: Week 4 - Group B, Week 5- Group A	Independent study (5 hr)
Week 05	M4: DC machines and control;	Lecture (2 hr)
Week 06	M4: DC machines and control;	Lecture (2 hr)
	Tutorial 3: Week 6 - Group A, Week 7 - Group B	Tutorial (2 hr)
	Lab 3: Week 6 - Group B, Week 7 - Group A	Practical (3 hr)
	Lab 3 Report: Week 6 - Group B, Week 7 - Group A	Independent study (5 hr)
Week 07	M5: AC machinery fundamentals;	Lecture (2 hr)
Week 07	Assignment	Independent study (7 hr)
Week 08	M6: Induction machines;	Lecture (2 hr)
	Tutorial 4: Week 8 - Group A, Week 9 - Group B	Tutorial (2 hr)
	Lab 4: Week 8 - Group B, Week 9 - Group A	Practical (3 hr)
	Lab 4 Report: Week 8 - Group B, Week 9 - Group A	Independent study (5 hr)
	Assignment	Independent study (7 hr)
Week 09	M6: Induction machines;	Lecture (2 hr)
Week 09	Assignment	Independent study (7 hr)
Week 10	M7: Synchronous machines;	Lecture (2 hr)
	Tutorial 5: Week 10 - Group A, Week 11 - Group B	Tutorial (2 hr)
	Lab 5: Week 10 - Group B, Week 11 - Group A	Practical (3 hr)
	Lab 5 Report: Week 10 - Group B, Week 11 - Group A	Independent study (5 hr)
	Assignment	Independent study (7 hr)
Week 11	M7: Synchronous machines;	Lecture (2 hr)
Week 11	Assignment	Independent study (7 hr)
Week 12	M8: Special motors;	Lecture (2 hr)
	Tutorial 6: Week 12 - Group A, Week 13 - Group B	Tutorial (2 hr)
	Lab 6: Week 12 - Group B, Week 13 - Group A	Practical (3 hr)
	Lab 6 Report: Week 12 - Group B, Week 13 - Group A	Independent study (5 hr)
Week 13	Recap & Revision	Lecture (2 hr)

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

Electric Machinary Fundamentals

All readings for this unit can be accessed through the Library eReserve, available on Canvas.

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

Outcomes
Graduate qualities

At the completion of this unit, you should be able to:

LO1. instigate inquiry for knowledge development, drawing on varied information sources and media formats and synthesise the information most pertinent to the design of AC or DC machines for particular application
LO2. work in a team and promote creative team interaction to encourage contribution from all members so as to deliver specific engineering projects and assignments
LO3. analyse, design and control an AC or DC machine for a particular application
LO4. perform calculations on machines using power quality concept and electrical circuit theories to the extent of the information presented
LO5. explain the theory of machinery.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

No changes have been made since this unit was last offered.

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links