Course

Elective Streams Electric and Hybrid Vehicles

Unit 1

Hybrid Vehicle Architecture: Introduction to various electric and hybrid vehicle architectures – battery technologies utilized in these vehicles, encompassing different battery chemistries, performance metrics, and the significance of battery management systems (BMS) – Powertrain architectures and their impact on energy efficiency.

Unit 2

Modelling techniques for energy storage systems: Simulation tools for analysing battery performance and behaviour – Case studies and practical applications in energy storage modelling – Control algorithms for optimizing energy flow and efficiency – Regenerative braking systems and energy recovery – State-of-charge (SoC) and state-of-health (SoH) estimation.

Unit 3

Optimization methods for improving vehicle range and efficiency: Energy management strategies for different driving conditions and scenarios – Integration of predictive and adaptive control algorithms for optimal energy usage- Industry practices and innovations in energy management for electric and hybrid vehicles – Emerging trends and future directions in the field.

Course Objectives

1. To introduce electric and hybrid vehicle architectures, battery technologies, and powertrain impacts.
2. To familiarize in modeling techniques, simulation tools, and control algorithms for energy storage systems.
3. To inculcate various optimization methods and energy management strategies to improve vehicle performance
4. To introduce industry practices, innovations, and future trends in energy management for electric and hybrid  Vehicles.

Course Outcomes

Text Books / References

1. Simona Onori, Lorenzo Serrao, “Hybrid Electric Vehicles Energy Management Strategies” , Springer Publications, 2nd edition, 2019.
2. Sheldon Williamson, “Energy Management Strategies for Electric and Plug-in Hybrid Electric Vehicles”

, Springer Publications, 2016.

3. Christopher Rahn and Chao-Yang Wang, “Battery Systems Engineering”, Wiley Publications, 2013.