|dc.description.abstract||In recent years, electrification of powertrain has gradually become the core of research and development efforts in automotive industry. This is mainly due to the fact that electrified powertrains can effectively alleviate concerns of environmental pollution caused by internal combustion engines (ICEs) and reduce the rate of depletion of the earth's natural resources, while offering a higher efficiency and a better fuel economy.
One of the key components of every electric vehicle (EV)/hybrid electric vehicle (HEV) is the Energy Storage System (ESS). An ESS provides propulsion power to the electric drivetrain and captures regenerative braking power. Batteries and ultracapacitors are the most well-known ESS devices for automotive applications.
In battery/ultracapacitor-based powertrains, the storage units are configured as series-parallel arrangements of individual cells. In this thesis, the battery and ultracapacitor units are assumed to be composed of parallel branches of series-connected cells.
Optimal sizing of the storage unit (determining the optimum numbers of the parallel branches and series-connected cells) and the interfacing infrastructure (if any DC-DC converter exists between the storage unit(s) and the traction motor controller) can have a significant impact on the manufacturing cost of the electric vehicle and its fuel economy.
This thesis formulates the problem of optimal sizing of battery/ultracapacitor-based energy storage systems in electric vehicles. Through the course of this research, a flexible optimization platform has been developed. When solving the optimization problem, different constraints such as limits on state of charge, current, and power of the battery cells, current and power of the ultracapacitor cells, voltage conversion of the DC-DC converter, DC bus voltage, and operation characteristics of the inverter and the traction motor are taken into account. This optimization tool is used to solve the problem of optimal sizing of the storage systems for two different classes of vehicles: (i) a small-size, long-range car and (ii) a city bus. Aside from optimal sizing of the storage systems as the main objective, the developed platform provides a proper simulation tool for analyzing the performance of existing electric vehicles on the road.||en