This course is an introduction to hybrid and plug-in electric vehicles. Equipped with a motor, battery, and gasoline engine, plug-in electric vehicles offer a viable solution to reduce gasoline consumption, emissions and fuel costs since they operate partly or entirely on inexpensive electricity that can be obtained from local, renewable, and green energy sources. In this course, student will learn the fundamentals of electrified vehicle design, control and optimization. Course will cover the topics such as vehicle component modeling, powertrain architectures, hybridization methods, energy management algorithms (rule based control, dynamic programming, and predictive control), battery state of charge estimation, battery cell balancing, powertrain performance analysis, optimal component sizing algorithms (DIRECT, GA, and PSO) hardware-in-the-loop-simulation, driver-in-the-loop simulation, EV-smart grid integration, vehicular networks (CAN bus and OBD-2 scanners), vehicle routing algorithms (Dijkstra and A*) and etc. Students will learn how to use PSAT/Autonomie software as well as Matlab/Simulink to design and analyze vehicle powertrains. Students will also learn how to design battery tests and run them using battery test stations and environmental chambers which are available in laboratory. Students equipped with the skills and knowledge that they will gain in this course will be highly sought-after in automotive industry in US and China. There will be biweekly assignments and a poster session at the end of the course where students will demonstrate their projects.