Description: Artificial intelligence (AI) has significantly revolutionized research activities and industrial applications in image processing and natural language processing. Likewise, the synergy of power electronics and computer science is expected to unleash great potentials in power electronic systems as well with their transition towards data-rich ones. From the power electronics perspective, this course aims to focus on two essential aspects of this interdisciplinary field, i.e., artificial intelligence and advanced data analytics. It is organized following a typical pipeline when implementing data-driven solutions in power electronics, ranging from the initial data collection to the final decision-makings. As a 3-day course, it includes fundamentals, tools, applications, hands-on exercises, and outlook, which are specifically tailored for power electronic applications. Combining with several case studies where AI has shown great benefits, the attendees are expected to establish solid foundations and skills of AI and data analytics to address core challenges in data-driven applications in power electronics.
Day-1: Fundamentals | ||
08:30 – 08:45 | Course introduction | Huai Wang |
08:45– 10:15 | Data and analytic methods in power electronics | Shuai Zhao |
10:15 – 10:30 | Coffee break |
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10:30 – 12:00 | Artificial intelligence tools in power electronics | Shuai Zhao |
Lunch |
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13:00 – 14:15 | Neural network for power electronic applications I: Fundamentals | Shuai Zhao |
14:15 – 14:30 | Coffee break |
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14:30 – 16:00 | Neural network for power electronic applications II: Hands-on implementation | Shuai Zhao |
Day-2 : Applications and Examples | ||
09:00 – 10:15 | Artificial Neural Network based Thermal Model Considering the Cross-Coupling Effects of Power Modules | Yi Zhang |
10:15 – 10:30 | Coffee break |
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10:30 – 12:00 | AI-based design and implementation of Model Predictive Control Algorithm | Mateja Novak |
Lunch |
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13:00 – 14:15 | Physics-informed AI to Handle Adversarial Data in Power Electronics | Subham Sahoo |
14:15 – 14:30 | Coffee break |
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14:30 – 15:15 | Digital twin & Condition and health monitoring in power electronics | Huai Wang |
15:15 – 16:00 | Project introduction | Shuai Zhao |
Day-3: Outlook and Project Exercise | ||
09:00 – 10:15 | Frontiers of data-driven research in power electronics and beyond | Shuai Zhao |
10:15 – 10:30 | Coffee break |
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10:30 – 12:00 | Project & Exercise (2 projects for each participant) P1: Digital twin-based condition monitoring of Buck converter P2: Physics-informed neural network for dynamic systems P3: AI-aided tuning of control parameters | Shuai Zhao, Mateja Novak,
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Lunch |
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13:00 – 16:00 | Project exercise and support | Shuai Zhao, Mateja Novak |
Prerequisites:
- Fundamentals of power electronics
- Fundamentals of probabilistic models and statistical analysis
- Experience with MATLAB/Python
* Please get familiar with Python basics and set up your Google Colab account before the course. A tutorial of Google Colab can be found: https://www.tutorialspoint.com/google_colab/google_colab_tutorial.pdf
* Matlab installed with the predictive maintenance toolbox. You may find more details in the below link: https://www.mathworks.com/products/predictive-maintenance.html
Form of evaluation: The course is accompanied by a hands-on team project so that the theoretical tools introduced in the course can be implemented in real applications. The course evaluation will be based on the project report.
Organiser: Professor, Huai Wang, hwa@energy.aau.dk; Assistant Professor, Shuai Zhao szh@energy.aau.dk
Lecturers: Professor, Huai Wang, hwa@energy.aau.dk, Aalborg University, Assistant Professor,
Shuai Zhao, szh@energy.aau.dk, Aalborg University,
Assistant Professor, Subham Sahoo sssa@energy.aau.dk, Aalborg University
Postdoc, Mateja Novak nov@energy.aau.dk, Aalborg University
Postdoc, Yi Zhang yiz@energy.aau.dk, Aalborg University
ECTS: 3
Date/Time: Apr.26-28, 2023
Deadline: 5 April 2023
Place: AAU Energy, Aalborg
Max no. of participants: 30
Price: 6000 DKK for PhD students outside of Denmark and 8000 DKK for the Industry excl. VAT
The Danish universities have entered into an agreement that allows PhD students at a Danish university (except Copenhagen Business School) the opportunity to free of charge take a subject-specific course at another Danish university.
Payment: A Online link will be annonced after deadline for registration
Important information concerning PhD courses: We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3.000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.
- Teacher: Mateja Novak
- Teacher: Subham Sahoo
- Teacher: Huai Wang
- Teacher: Shuai Zhang
- Teacher: Yi Zhang
- Teacher: Shuai Zhao