The increased interest in reducing greenhouse gas emissions has motivated renewed interest in electric vehicles technology as an alternative to current fossil-fuel based transportation equipment. Electric vehicles (EVs) are envisioned as a promising viable technology because of their friendly impact on the environment and higher efficiency over conventional vehicles that rely on fossil fuel. However, the EVs’ limited battery capacity, resulting in limited cruising range and long recharging time, hinders the widespread adoption of EVs. An essential requirement of EV motors is the ability to operate with minimum energy consumption in order to provide at least the same driving range as their Internal Combustion Engine (ICE) counterparts. Energy-optimal routing, which aims to find the least energy consuming routes, under battery constraints has been recognized as a viable approach to prolonging the cruising range of the EV battery.
This thesis addresses the problem of optimal routing for EVs and proposes a solution to overcome the difficulties of optimal energy/time routing under battery constraints. A multi-criteria path-finding technique is proposed. The proposed technique functions in two modes and solves the problem of optimal energy/time routing in EVs with worst time complexity of . First, an energy mode to solve the problem of energy-optimal routing under battery constraints is introduced. This mode computes the most energy-efficient route from a source to a destination, thus extending the limited cruising range of a battery. Second, a time mode to solve the problem of optimal travel time routing under battery constraints, by computing the most efficient travel-time route from a source to a destination, is proposed. An EV can operate under these two modes to strike a balance between power consumption and travel time so as to satisfy user constraints and needs.
In addition, a technique to reduce the effects of range anxiety on the vehicle operator is proposed. This technique computes a robust estimate of driving range. Furthermore, the technique analyzes an EV’s battery capacity required by the vehicle in order to reach a charging station. The thesis reports experimental work conducted to test and validate the proposed techniques under various driving conditions.
| Identifer | oai:union.ndltd.org:WATERLOO/oai:uwspace.uwaterloo.ca:10012/7309 |
| Date | January 2013 |
| Creators | Faraj, Mahmoud S |
| Source Sets | University of Waterloo Electronic Theses Repository |
| Language | English |
| Detected Language | English |
| Type | Thesis or Dissertation |
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