電気回路研究室

In motor drive systems, various energy losses occur, such as copper loss generated by current, mechanical loss due to friction, and inverter loss stemming from power electronic circuits. Since these losses vary depending on the operating speed and torque conditions, driving at a constant speed is not always the most efficient approach.

In this research, we utilize motor loss maps to design speed trajectories that minimize the total energy loss across the entire drive duration—from start to stop. To optimize these trajectories, we primarily employ two approaches: the Variational Method for deriving theoretical optimal solutions, and Genetic Algorithms (GA) for computational optimization.

Furthermore, we evaluate the validity of our theories through a multi-faceted approach, moving beyond MATLAB/Simulink simulations to include experimental verification using actual machines (synchronous and induction motors).

Electric vehicles (EVs) offer significant advantages over internal combustion engine (ICE) vehicles, including a torque response that is hundreds of times faster and the ability to accurately monitor torque magnitude. Our research leverages these characteristics to develop advanced traction control systems for challenging conditions, such as icy roads.

The objective of this research is to enhance both the safety and driving performance of electric vehicles by appropriately controlling motor torque according to road conditions, thereby preventing excessive tire slip.

Specifically, we are developing algorithms to estimate slip ratios and road friction coefficients with high precision, allowing road surface changes to be reflected in torque control within milliseconds. In addition to MATLAB/Simulink simulation analysis, we conduct experimental testing using small-scale electric vehicle prototypes to verify the effectiveness of our proposed methods from multiple perspectives.

Supplying power from "DC" sources, such as solar power and storage batteries, to the "AC" power grid (utility grid) used in homes and factories requires high-precision power conversion via grid-connected inverters. However, interactions with grid-side impedance can cause inverter operation to become unstable, making a steady power supply difficult to maintain.

Toward the realization of Smart Grids, our research focuses not only on improving conversion efficiency but also on developing control methods to maintain the stability of the entire power network. Specifically, we propose "Negative-Sequence Compensation Control" to eliminate output current distortion caused by parameter imbalances in LCL filters, as well as "Control using Lyapunov Functions" to guarantee system stability even under conditions with grid interference.

In addition to simulation analysis using MATLAB and SaberRD, we conduct experiments using actual inverter circuits and simulated power grids. Through these multi-faceted evaluations, we pursue the power electronics technology necessary to support the resilient power infrastructure of the next generation.