Course Structure Overview
The Auto Electrical program at Govt Polytechnic Ganai Gangoli is designed to provide students with a comprehensive understanding of automotive electrical systems and their integration with modern electronics. The curriculum is structured over 8 semesters, with each semester building upon the previous one to ensure a progressive learning experience.
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | AE-101 | Engineering Mathematics I | 3-1-0-4 | - |
| 1 | AE-102 | Physics for Engineers | 3-1-0-4 | - |
| 1 | AE-103 | Basic Electrical Engineering | 3-1-0-4 | - |
| 1 | AE-104 | Computer Programming Fundamentals | 2-0-2-3 | - |
| 1 | AE-105 | Engineering Drawing and Graphics | 2-0-2-3 | - |
| 1 | AE-106 | Environmental Science and Engineering | 2-0-0-2 | - |
| 2 | AE-201 | Engineering Mathematics II | 3-1-0-4 | AE-101 |
| 2 | AE-202 | Chemistry for Engineers | 3-1-0-4 | - |
| 2 | AE-203 | Electrical Circuits and Networks | 3-1-0-4 | AE-103 |
| 2 | AE-204 | Data Structures and Algorithms | 3-1-0-4 | AE-104 |
| 2 | AE-205 | Engineering Mechanics | 3-1-0-4 | - |
| 2 | AE-206 | Professional Communication Skills | 2-0-0-2 | - |
| 3 | AE-301 | Electromagnetic Fields and Waves | 3-1-0-4 | AE-203 |
| 3 | AE-302 | Digital Electronics and Logic Design | 3-1-0-4 | AE-203 |
| 3 | AE-303 | Microprocessor Architecture | 3-1-0-4 | AE-204 |
| 3 | AE-304 | Control Systems Engineering | 3-1-0-4 | AE-201 |
| 3 | AE-305 | Automotive Components and Systems | 3-1-0-4 | - |
| 3 | AE-306 | Signals and Systems | 3-1-0-4 | AE-201 |
| 4 | AE-401 | Analog Electronics | 3-1-0-4 | AE-302 |
| 4 | AE-402 | Embedded Systems | 3-1-0-4 | AE-303 |
| 4 | AE-403 | Vehicle Dynamics and Control | 3-1-0-4 | AE-305 |
| 4 | AE-404 | Power Electronics | 3-1-0-4 | AE-203 |
| 4 | AE-405 | Sensors and Instrumentation | 3-1-0-4 | - |
| 4 | AE-406 | Project Work I | 0-0-6-6 | - |
| 5 | AE-501 | Advanced Digital Electronics | 3-1-0-4 | AE-401 |
| 5 | AE-502 | Automotive Electronics and Control Systems | 3-1-0-4 | AE-402 |
| 5 | AE-503 | Electric Vehicle Engineering | 3-1-0-4 | AE-404 |
| 5 | AE-504 | Smart Transportation Systems | 3-1-0-4 | - |
| 5 | AE-505 | Renewable Energy Integration in Vehicles | 3-1-0-4 | - |
| 5 | AE-506 | Project Work II | 0-0-6-6 | - |
| 6 | AE-601 | Advanced Control Systems | 3-1-0-4 | AE-403 |
| 6 | AE-602 | Automotive Cybersecurity | 3-1-0-4 | AE-502 |
| 6 | AE-603 | Advanced Driver Assistance Systems (ADAS) | 3-1-0-4 | - |
| 6 | AE-604 | Vehicle Diagnostics and Predictive Maintenance | 3-1-0-4 | - |
| 6 | AE-605 | Automotive Software Engineering | 3-1-0-4 | - |
| 6 | AE-606 | Project Work III | 0-0-6-6 | - |
| 7 | AE-701 | Capstone Project | 0-0-12-12 | - |
| 7 | AE-702 | Industrial Training | 0-0-6-6 | - |
| 8 | AE-801 | Research and Innovation | 0-0-12-12 | - |
| 8 | AE-802 | Final Thesis | 0-0-12-12 | - |
Advanced Departmental Elective Courses
Electronics and Embedded Systems in Automotive Applications: This course focuses on the integration of electronic components and embedded systems within automotive environments. Students learn about microcontroller architecture, real-time operating systems, and sensor networks used in modern vehicles.
Power Electronics for Electric Vehicles: Designed to explore the principles and applications of power electronics in electric vehicles. Topics include battery management systems, motor drives, DC-DC converters, and AC-AC inverters used in EVs.
Advanced Driver Assistance Systems (ADAS): This course delves into the technologies that enhance vehicle safety and driver assistance. It covers perception systems, decision-making algorithms, and control strategies for autonomous driving features.
Vehicle Diagnostics and Predictive Maintenance: This elective introduces students to diagnostic tools and techniques used in modern vehicles. It emphasizes predictive maintenance using data analytics and machine learning to prevent failures and optimize performance.
Smart Transportation Systems: Students explore the integration of information technology and transportation systems. The course covers traffic management, intelligent transport systems (ITS), and smart mobility solutions.
Automotive Cybersecurity: This course addresses the growing concern of cybersecurity in connected vehicles. It covers network security protocols, secure communication methods, and threat detection mechanisms for automotive systems.
Automotive Software Engineering: Focused on software development practices specific to automotive applications, this course covers software lifecycle management, testing methodologies, and compliance with automotive standards like ISO 26262.
Rename: Renewable Energy Integration in Vehicles: This course explores the integration of renewable energy sources into vehicle systems. It includes solar panels, fuel cells, and hybrid power systems designed to reduce dependency on fossil fuels.
Control Systems for Autonomous Vehicles: Students learn advanced control theory applied to autonomous vehicles. The course covers path planning, trajectory tracking, and adaptive control algorithms used in self-driving cars.
Advanced Microprocessor Architecture: This elective explores the architecture and design of modern microprocessors used in automotive applications. It includes instruction sets, pipeline design, and performance optimization techniques.
Simulation and Modeling in Automotive Systems: This course teaches simulation tools and modeling techniques for automotive systems. Students learn to model complex systems using MATLAB/Simulink and validate them against real-world data.
Project-Based Learning Philosophy
The department strongly believes in project-based learning as a core component of the curriculum. This approach ensures that students gain practical experience while applying theoretical concepts to real-world problems. The program includes mandatory mini-projects in the early semesters and a final-year thesis or capstone project.
Mini-projects are designed to be team-based, allowing students to collaborate and develop soft skills such as communication, leadership, and teamwork. These projects are typically completed over 2-3 months and are evaluated based on technical merit, presentation quality, and peer feedback.
The final-year thesis is a significant undertaking that spans several months. Students select their projects under the guidance of faculty mentors who provide expert supervision and support. The thesis process includes literature review, experimental design, data collection, analysis, and documentation. Students are encouraged to present their findings at conferences or publish papers in academic journals.
Faculty mentors play a crucial role in guiding students through their project journey. They help students identify relevant research areas, develop project proposals, and refine their technical skills. The department also organizes workshops and seminars on research methodologies, data analysis, and presentation skills to further support student learning.