Identification and Neural Networks – 6 CFU (since 24-25)

Identification and Neural Networks – 6 CFU (since 24-25)
2 YEAR II semester  6 CFU
Patrizio Tomei (4cfu)
Eugenio Martinelli (2cfu)
A.Y. 2023-24 ex Adaptive Systems (block C-opt) 
Giovanni Luca SANTOSUOSSO A.Y. 2024-25 not been activated
A.Y. 2025-26
(new name “Identification and Neural Networks”
Didatticaweb
Syllabus📑

Code: 80300088
SSD: ING-INF/04

 

Digital Modeling of Energy Conversion – 6 CFU (block A-B) (since 2025-26)

Digital Modeling of Energy Conversion – 6 CFU (block A-B) (since 2025-26)
1 YEAR
1 semester 6 CFU
Vincenzo MULONE (3cfu)

Pietro MELE (3cfu)

A.Y. 2025-26
didatticaweb
Syllabus📑

Code:
SSD: ING-IND-08
(by Mechatronics Engineering)

Digital Modeling of Energy Conversion 9 – Block A-B

Mechanics of Systems for Simulations – 6 CFU (block A-B) (since 2025-26)

Mechanics of Systems for Simulations – 6 CFU (block A-B) (since 2025-26)
1 YEAR
1 semester 6 CFU
(ex FUNDAMENTALS OF MECHANICS OF SYSTEMS)
Marco Ceccarelli A.Y. 2025-26 program 📑
Code: 80300216 
SSD: ING-IND-13
(by Engineering Sciences)


PREREQUISITES: knowledge of basic mechanics of rigid bodies and computation skills

SYLLABUS

Structure and classification of planar mechanical systems, kinematic modelling, mobility analysis, graphical approaches of kinematics analysis, kinematic analysis with computer-oriented algorithms, dynamics and statics modelling, graphical approaches of dynamics analysis, dynamic analysis with computer-oriented algorithms, performance evaluation, elements of mechanical transmissions.

BOOKS:

Lopez-Cajùn C., Ceccarelli M., Mecanismos, Trillas, Città del Messico
Shigley J.E., Pennock G.R., Uicker J.J., “Theory of Machines and Mechanisms”, McGraw-Hill, New York
Handnotes and papers by the teachers

Radar and Localization – 6 CFU (optC2.a)

Radar and Localization – 6 CFU (optC2.a)
2 YEAR II semester 6 CFU
Prof. Mauro Leonardi A.Y. 2025-26
 

 

(By ICT)
Code: 80300159
SSD: ING-INF/03

LEARNING OUTCOMES: Knowledge of the main applications and operations of radar systems with the necessary basic elements (both theoretical and technical-operational).

KNOWLEDGE AND UNDERSTANDING: Being aware, at the system level, performance in terms of scope, discrimination, ambiguity, Doppler filtering

APPLYING KNOWLEDGE AND UNDERSTANDING: knowing how to deal with new problems with the methods learned

MAKING JUDGEMENTS: the ability to choose among the various methods learned the proper one to face new problems and radar design.

Syllabus – Radar Systems

1. Fundamentals

  • General information on radar.

  • Spectrum usage.

  • Radar measurements:

    • Distance.

    • Radial velocity.

    • Angular location.

2. Radar Equation and Propagation

  • Fundamental radar equation.

  • Receiver and antenna noise.

  • Propagation: attenuation and reflections.

  • Losses.

3. Radar Cross Section and Target Models

  • Radar Cross Section (RCS).

  • Target fluctuation models:

    • Slow fluctuation.

    • Rapid fluctuation.

4. Target Detection

  • Detection of fixed targets.

  • Detection of moving targets.

  • Pulse integration.

5. Decision Theory and Radar Detection

  • Decision criteria.

  • Detection with a single pulse.

  • Detection with N pulses.

6. Radar Types

  • Pulsed radar.

  • Continuous Wave (CW) radar.

  • Frequency Modulated Continuous Wave (FMCW) radar.

  • Automotive radar.

COMPUTER VISION – 6 CFU (since 2024-25)

COMPUTER VISION – 6 CFU (since 2024-25)
2 YEAR II semester  6 CFU
Arianna Mencattini A.Y. 2023-24 (ex MEASUREMENT SYSTEMS FOR MECHATRONICS)

A.Y. 2024-25: Computer Vision

didatticaweb
Syllabus📑

Code: 8039787
SSD: ING/INF/07

INTEGRATED SOLUTIONS FOR SUSTAINABLE MOBILITY AND ENERGY PRODUCTION – 6 CFU (C2)

CEM
1 YEAR II semester 6 CFU
(from Mechanical)
Lorenzo BARTOLUCCI (3cfu)
Matteo BALDELLI (3cfu)
A.Y. 2024-25
Code: 80300136
SSD: ING-IND/08
  • Prerequisites: No prior kknowledge is required, although notions about energy systems and an understanding of error and data analysis can facilitate the student. All the knowledge necessary to pass he exam will be provided during the course.
  • OBJECTIVES: The goal of the course is to provide students with both a detailed and holistic view of the energy landscape for sustainable mobility and its impact on the overall energy system. The course aims to bridge the production of key energy carriers (electricity, hydrogen, biofuels, etc.) with their use in mobility, addressing issues of integration and optimization. To this end, students will expand their understanding of the fundamental physics behind these technologies, combining theoretical/modeling aspects with experimental approaches through laboratory activities. Lastly, particular attention will be given to the presentation and critical analysis of data obtained both experimentally and through numerical modeling.

 

Electric Propulsion – 6 CFU (optC2.b)

Electric Propulsion – 6 CFU (optC2.b)
1 YEAR (Block C2)
II semester 6 CFU
(from Mechanics – Energetics)
Prof. Marcello PUCCI
since A.Y. 2024-25

Syllabus📑

didatticaweb

Code: 80300151
SSD: ING-IND/32

Prerequisities

It is suggested to have the basic knowledge of Electrical Network Analysis and Power Electronics

SYLLABUS

The course will be articulated in the following way:
– Electric Vehicles
– Hybrid Electric Vehicles
– Electric Propulsion Systems for vehicles
– Series Hybrid Electric Drive Train Design
– Parallel Hybrid Electric Drive Train Design
– Energy Storage (Batteries, Supercapacitors – Ultrahigh-Speed Flywheels, Hybrid)
– Fuel Cell Vehicles
– Ship propulsion systems
– Vehicle to Grid (V2G) and Grid to Vehicle (G2V)

TEXTS

Educational material provided by the teacher

– John M. Miller, Propulsion Systems for Hybrid Vehicles, IET, 2008
– Iqbal Husain, Electric and Hybrid Vehicles: Design Fundamentals, 2010, CRC Press
– Mehrdad Ehsani, Yimin Gao, Ali Emadi, Modern Electric, Hybrid Electric, and Fuel Cell
Vehicles: Fundamentals, Theory, and Design, 2017, CRC Press