| CO1 | Illustrate the architecture, drivetrain configurations, and fundamental vehicle dynamics of electric and hybrid electric vehicles |
| CO2 | Design and evaluate suitable electric and hybrid vehicle drive schemes based on available energy sources, drive cycle requirements, and vehicle performance objectives. |
|
CO3 |
Analyze energy storage systems, charging infrastructure technologies and their standards. |
| CO4 | Demonstrate the application of machine learning and AI in Smart grids and electric vehicles |
Course Articulation Matrix: Correlation level [ 1: low, 2: medium, 3: High]
| PO | PO1 | PO2 | PO3 | PSO1 | PSO2 |
| CO | |||||
| CO1 | 2 | 1 | 3 | 1 | – |
| CO2 | 2 | 1 | 3 | 2 | – |
| CO3 | 2 | 1 | 3 | 2 | – |
| CO4 | 2 | 1 | 3 | 2 | – |
Review of Conventional Vehicle, Types of EVs, Architecture and concepts of hybrid electric power trains. Vehicle Dynamics, Tractive Effort & Analysis, Energy Storage Requirements in Electric Vehicles, Types of energy storage technologies for EV, Charging and discharging characteristics: Battery Management System, Cell balancing, Pre-charge circuit. Battery Swapping Technologies, Thermal Management in EV battery. EV charging standards, V2X and enabling technologies. Electric Propulsion systems: EV Motor drives, Configuration and control of Drives and Sizing. Energy Management Strategies, Vehicle Testing and Validation-MIL, SIL, HIL, VIL, E-mobility business, and electrification challenges. Connected Mobility and Autonomous Mobility. Case study/Simulation/Hardware experiments.