Semester-wise syllabus outline for an M.Tech in Automotive Engineering

Semester 1: Core Fundamentals 

1. Vehicle Dynamics & Control 

   - Longitudinal/lateral dynamics, suspension systems, stability control, tire modeling (Pacejka’s model). 

2. Automotive Powertrain Technology 

   - Internal combustion engines (ICE), hybrid/electric powertrains, transmission systems, emissions control. 

3. Materials Science for Automotive Applications 

   - Lightweight materials (CFRP, aluminum alloys), crashworthiness, fatigue analysis. 

4. Computer-Aided Vehicle Design 

   - CAD tools (CATIA, SolidWorks), finite element analysis (FEA) for chassis/body design. 

5. Lab 1: Basic Automotive Systems 

   - Engine disassembly/assembly, drivetrain testing, CAD modeling projects. 

Semester 2: Advanced Systems & Electives 

1. Advanced Powertrains 

   - Turbocharging, fuel injection systems, battery management systems (BMS) for EVs, hydrogen fuel cells. 

2. Automotive Electronics & Embedded Systems 

   - ECU programming, sensors/actuators, CAN bus, ADAS (Advanced Driver Assistance Systems). 

3. Aerodynamics & NVH (Noise, Vibration, Harshness) 

   - CFD for vehicle aerodynamics, noise reduction techniques, vibration isolation. 

4. Elective 1 (e.g., Hybrid & Electric Vehicles or Autonomous Vehicle Technology) 

5. Lab 2: Simulation & Testing 

   - MATLAB/Simulink for control systems, ANSYS/GT-Power for engine simulation, crash testing simulations (LS-DYNA). 

Semester 3: Specialization & Project Work 

1. Elective 2 (e.g., AI in Automotive Systems or Advanced Manufacturing Processes) 

2. Elective 3 (e.g., Vehicle Cybersecurity or Sustainable Automotive Design) 

3. Automotive Manufacturing & Quality Control 

   - Lean manufacturing, Industry 4.0 (IoT, robotics), Six Sigma, ISO/TS 16949 standards. 

4. Project Work Part 1 

   - Industry-collaborated projects (e.g., EV battery thermal management, autonomous navigation algorithms). 

5. Professional Workshops 

   - Training on tools (CarSim, AVL Cruise), certification courses (Automotive SPICE, SAE standards). 

Semester 4: Thesis/Dissertation 

- Independent Research Thesis

  - Focus areas: 

    - EV battery optimization, 

    - Autonomous vehicle perception systems (LiDAR, radar fusion), 

    - Alternative fuels (biofuels, hydrogen), 

    - Lightweight composite structures. 

  - Thesis submission and defense. 

Elective Options (Semesters 2–3): 

- Vehicle Telematics & Connectivity (V2X) 

- Crashworthiness & Passive Safety Systems 

- Automotive Thermal Management 

- Robotics in Automotive Assembly 

- Machine Learning for Predictive Maintenance 

- Motorsport Engineering 

Key Tools & Software:

- Design & Simulation: CATIA, ANSYS, MATLAB/Simulink, CarSim, AVL Fire, GT-Power. 

- Programming: Python (for AI/ML), C/C++ (embedded systems), ROS (Robotic Operating System). 

- EV/Autonomous Focus: Battery simulation (COMSOL), ADAS toolkits (NVIDIA DriveWorks), AUTOSAR. 

Lab/Practical Focus: 

1. Powertrain Testing: Dyno testing for ICE/EV performance, emissions analysis. 

2. Autonomous Vehicle Prototyping: Sensor integration (LiDAR, cameras), path-planning algorithms. 

3. Crash Simulation: Virtual crash testing (LS-DYNA), occupant safety analysis. 

4. Manufacturing Workshops: 3D printing of automotive components, robotic welding.