Undergraduates or Masters student will have a unique opportunity to actively participate in research; developing novel concepts and applying them in experimental work.  If you are considering attending graduate school, this project is an excellence opportunity to learn about academic research and strengthen your application.

Project Description

Electric and hybrid vehicles are growing in popularity.  Battery management and control is critical to the continuing development of these technologies.  One of the challenges in battery management is estimating the state-of-charge.  State-of-charge measures how full a battery cell is. It is the fuel gauge for electric vehicles. State-of-charge cannot be measured directly. Instead it must be estimated from voltage and current measurements using a model of the battery dynamics. This is a very challenging problem.  The measured voltage of a battery cell is a non-linear function of state-of-charge, current, hysteresis states, and time-varying parameters.

The objective of this project is to implement an observer for estimating state-of-charge for Li-Ion battery cells.  Student will be responsible for developing and evaluating state-of-charge estimation algorithms. Algorithms will be evaluated by implementing them on our experimental hardware testbed. Student are encouraged propose novel estimation algorithms and experiments. 

Project Details

Recommended Coursework (undergraduate): ME-132, ME-134 or EE-128

Recommended Coursework (graduate): ME-232 or EE-221A

Hours per week: 10-20

Length of Project: At least one semester