EECS 598-14: Advanced Energy Storage, @University of Michigan, Ann Arbor, Spring 2020
(Response rate: 91.3%; Teacher’s feedback 4.8/5)
This course primarily focuses on introducing and comparing different energy storages, such as pumped-storage, compressed air energy storage, batteries, capacitive energy storage, fuel cells, and flywheels, with special applications to electrified vehicles and renewable energy systems where energy storage plays a crucial role. The course will focus on reviewing principles and recent progress in energy storage systems, with the goals of improving the performance and lifespan of electrified vehicles as well as integrating renewable energy (e.g., wind and solar energy) into the grid.
ME6401: Topics in Mechatronics, @NUS, Fall 2022
(Response rate: 55%; Teacher’s feedback 4.5/5)
Several mechatronics-related examples will be illustrated in this course, and based on mechatronics-oriented projects, this course will provide students with amazing opportunities to work on the corresponding projects, thereby gaining in-depth understanding and insights into the field.
ME5414: Optimization Techniques for Dynamic Systems, @NUS
(Spring 2023: Response rate: 90%; Teacher’s feedback 4.8/5)
The course covers optimization approaches in linear and nonlinear programming. Topics include optimality conditions for constrained systems, Simplex Algorithm, Semidefinite Programming, Functional & variation, Linear Quadratic Regulator, Model Predictive Control, Dynamic Programming, and their applications in the design and analysis of Dynamical Systems.
ME5422: Computer Control and Applications, @NUS
(Fall 2023: Response rate: 41%; Teacher’s feedback 4.7/5)
This course introduces the concepts and methods that are fundamental to the design and implementation of computer/microprocessor-based control schemes, with an emphasis on industrial automation. Topics covered include: discrete-time systems and z-transform; sampling and reconstruction; open-loop and closed-loop discrete-time systems; system time-response characteristics; stability analysis techniques; digital controller design; pole-assignment design and state estimation; system identification of discrete-time systems; and numerical simulation computer control systems using MATLAB.
IE2141: System Thinking and Dynamics, Tutorials @NUS
(Spring 2022: Response rate: 61%; Teacher’s feedback 4/5)
(Spring 2023: Response rate: 70%; Teacher’s feedback 4.1/5)
The course aims to introduce students to the fundamental concepts and underlying principles of system thinking, design and dynamics. It will provide students with an understanding of systems thinking and applying systems dynamics modelling to describe and simulate real world problems. At the end of the course, students should have the necessary knowledge and abilities to define, analyse, design, and develop a system dynamics model that simulates a specific problem and recommend solutions for different scenarios.