Simulink Student Challenge Winners
MathWorks announces the winners of the 2024 Simulink Student Challenge. Congratulations and thanks to all the students who entered.
1st Place
Driver-in-the-loop Simulator
Politecnico di Milano, Italy – Daniele Chimisso
The Driver-in-the-Loop (DiL) simulator developed by the DYNAMIS PRC Formula Student team serves as a versatile tool for vehicle analysis, driver training, and more. This simulator integrates all vehicle subsystems and models—such as the battery, control systems, and suspension—into a unified architecture.
The simulator offers extensive customization options, particularly in its graphics, powered by Unreal Engine®. Features include colliding cones, real-time telemetry, a custom HUD, and a user-friendly GUI, showcasing its wide-ranging capabilities.
This video provides an overview of the DiL simulator's functionality and highlights its current level of correlation with real-world scenarios, demonstrating its value as a comprehensive simulation tool.
2nd Place
Reinforcement Learning-Based Control for Autonomous Mobile Robot (AMR)
Sejong University – Jinyoung Jeong (Team AIV)
This project focuses on developing robust navigation control technology for indoor autonomous robots using reinforcement learning. With the growing demand for reliable indoor service robots, this research addresses key challenges in stability, safety, and efficiency.
The approach integrates perception, decision-making, and action execution through learning-based control mechanisms. Reinforcement learning enables robots to adapt to dynamic environments, ensuring safe obstacle and human avoidance while optimizing navigation paths to improve energy efficiency.
This work provides a practical solution to enhance the safety and performance of autonomous indoor navigation, meeting the demands of evolving robotics applications.
3rd Place
Building and Analyzing an EV Model using Simulink
Hanoi University of Science and Technology – Nguyen (BK- AUTO)
This study addresses the challenges of improving energy efficiency in electric vehicles (EVs), with a focus on extending range per charge. Using MATLAB® and Simulink®, the team developed a dual-motor electric vehicle model based on the VinFast VF8 Eco, a Vietnam-manufactured EV.
The model incorporates key components, including the driver and driving cycle, longitudinal vehicle dynamics, battery, electric motor, braking system, and tires. Validation of the model was conducted by comparing simulation results with experimental data obtained from Kistler equipment.
With this validated model, the research explores strategies for torque distribution across drive axles and regenerative braking control to optimize energy consumption. This work contributes to advancements in EV technology while supporting the development of sustainable and environmentally friendly transportation solutions.
