Starting a few decades ago, the unmanned wheeled vehicle research has drawn
lately more attention, especially for off-road environment. As the demand to use
electric vehicles increased, the need to conceptualize the use of electrically driven
vehicles in autonomous operations became a target. That is because in addition to the
fact that they are more environmentally friendly, they are also easier to control. This
also gives another reason to enhance further the energy economy of those unmanned
electric vehicles. Off-road vehicles research was always challenging, but in the
present work the nature of the off-road land is utilized to benefit from in order to
enhance the energy consumption of those vehicles. An algorithm for energy
consumption optimization for electrically driven unmanned wheeled vehicles is
presented. The algorithm idea is based on the fact that in off-road conditions, when
the vehicle passes a ditch or a hole, the kinetic energy gained while moving downhill
could be utilized to reduce the energy consumption for moving uphill if the
dimensions of the ditch/hole were known a distance ahead. Two manipulated
variables are evaluated: the wheels DC motors supply voltage and the DC armature
current. The developed algorithm is analysed and compared to the PID speed
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controller and to the open-loop control of DC motors. The developed predictive
controller achieved encouraging results compared to the PID speed control and also
compared to the open-loop control. Also, the use of the DC armature current as a
manipulated variable showed more noticeable improvement over using the DC input
voltage. Experimental work was carried out to validate the predictive control
algorithm. A mobile robot with two DC motor driven wheels was deployed to
overcome a ditch-like hindrance. The experimental results verified the simulation
results. A parametric study for the predictive control is conducted. The effect of
changing the downhill angle and the uphill angle as well as the size of the prediction
horizon on the consumed electric energy by the DC motors is addressed. The
simulation results showed that, when using the proposed approach, the larger the
prediction horizon, the lower the energy consumption is.
| Identifer | oai:union.ndltd.org:uottawa.ca/oai:ruor.uottawa.ca:10393/23984 |
| Date | January 2013 |
| Creators | Mohammed, Mostafa Ahmed Ismail |
| Contributors | Necsulescu, Dan |
| Publisher | Université d'Ottawa / University of Ottawa |
| Source Sets | Université d’Ottawa |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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