Projects/Group-Works
Cleaning and Hail Protection System for Solar Panels
University of Trento – Master’s Degree in Mechatronics Engineering
Group members: Filippo Avi, Alberto Giora, Matteo Manzini, Edoardo Murgia, Andrea Silvan
Supervisor: Prof. Emiliano Rustighi
Academic Year: 2023/2024
Course: Mechanical Design for Mechatronics
Overview
We developed a multifunctional system to protect photovoltaic panels from hail and ensure optimal performance through autonomous cleaning. The solution integrates a retractable anti-hail net and a rolling brush cleaning mechanism, both actuated by a shared motor-transmission unit.
Key Features
- Automatic hail detection using a laser disdrometer sensor (ZDM-100)
- Rolling shutter and cleaning brush powered by a single electric motor
- Stress and motion analysis of shafts and gear train
- Finite Element Analysis (FEM) for mechanical verification
- Low-maintenance design, easy installation on standard panel arrays
- Water-resistant and IP67-rated components
Skills Applied
- Mechanical design (CAD, FEM, shaft and gear sizing)
- Mechatronic integration (sensor-actuator coupling)
- System simulation and power transmission analysis
- Team collaboration and report writing (80+ page technical report)
Autonomous Driving System for Traffic Lights
University of Trento – Master’s Degree in Mechatronics Engineering
Student: Edoardo Murgia
Supervisor: Prof. Rosati Papini Gastone Pietro
Academic Year: 2024/2025
Course: Intelligent Vehicles and Autonomous Driving
Overview
I developed a longitudinal control system for an autonomous vehicle to manage interactions with traffic lights, reproducing human-like driving behaviors. The project combines optimal control methods with biologically inspired decision-making strategies and was implemented in C++ with the aid of MATLAB for optimization.
Key Features
- Minimum-jerk optimal control problem to generate smooth and realistic trajectories
- Definition of stop and pass motion primitives, with constraints on position, velocity, and acceleration
- Action selection mechanism based on a receding-horizon approach and inspired by basal ganglia decision processes
- Low-level PI controller to track optimal trajectories and handle wind-up issues
- Integration of MATLAB optimal solutions into C++ code for real-time implementation
Skills Applied
- Optimal control formulation and problem solving (minimum-jerk trajectories)
- Control system design (PI control, stability analysis)
- C++ programming and MATLAB simulation
- Application of biologically inspired decision models
- Scientific reporting and technical presentation