Modeling and optimal control of range extended electric vehicles

Abstract

Over the last few years, the world has started to witness a change in vehicular technology due to increasing gasoline prices and environmental concerns. Hybrid and Electric vehicles have been introduced to society. The level of usage for these vehicles is directly related to advance in battery technology and control strategies. Modern battery technology, even after recent developments, does not allow for electric vehicle (EV) ranges to be more than a couple hundred kilometers. Even though this range is statistically sufficient for more than 80% of the journeys, most drivers suffer from range anxiety which in turn prevents EVs from becoming a viable option. As a solution, Range Extended Electric Vehicle (REEV) has been proposed. REEV has the same architecture as a Series Hybrid Electric Vehicle (SHEV) which is one of the main hybrid vehicle architectures. In SHEVs, 100% of the propulsion is provided by an Electric Motor (EM). When the state of charge (SOC) of the battery reaches low levels, the electricity necessary for the operation of EM is supplied by a generator which is driven by an Internal Combustion Engine (ICE). The main goal of this thesis is to develop, by the use of contemporary IT methodologies, a novel optimal control strategy for REEVs in order to offer better energy management and/or component life. The project can therefore roughly be divided in 2 parts, Range Extended Electric Vehicle modeling and implementation of optimal controller for energy management problem.