Date of Award


Publication Type

Master Thesis

Degree Name



Electrical and Computer Engineering

First Advisor

Kar, Narayan


Electric Vehicles, Hybrid Energy Storage Systems




In electric vehicles, batteries are unable to entirely store the large amount of power from regenerative braking which is generated over a short time period. Batteries also have a lower efficiency when required to supply peaking power. Alternatively supercapacitors can handle peaking power at the expense of lower energy storage capacities. This is why hybrid energy storage systems using a battery and a supercapacitor are being researched. There exist multiple configurations and control strategies for these systems and recently some are beginning to take drive cycle data into consideration. The objective of this research is to design an intelligent algorithm for controlling the balancing of energy between a supercapacitor and a battery. By using machine learning methods, it’s able to learn from offline data where the optimal balancing can be calculated. The algorithm can then operate online, predicting how to balance the system which should improve the overall efficiency.