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A piece of mobile mining equipment must possess sufficient power to overcome normal resistances and also resistances whose prediction and quantification is much more difficult, such as those accompanying cyclic maneuvers and emergencies. These abnormal, highly variable resistances require a quantity of reserve power. The sum of reserve power, required power, auxiliary power, and ambient corrections represents the total power requirement. Reserve power is traditionally defined as "the additional power available to a vehicle for climbing grades and for acceleration." In this study, reserve power was redefined as "the power available to a vehicle in addition to that necessary to overcome normal resistances." To date, determination of reserve power has not been properly addressed. In this study, the concept of reserve power was introduced, its purposes and demands were isolated, fundamental principles of power determination were developed, and three methods were proposed to determine its magnitude. Although these methods were specifically designed for rear dump off-highway trucks, similar analyses can be developed for other pieces of mobile equipment. The qualities of agility and ruggedness were recognized, delineated, and developed. Human factors and safety considerations were treated as underlying concerns at appropriate levels of study. A thorough literature review was conducted and three traditional methods for estimating the total power requirement were isolated, but none clearly linked the variability of operating conditions to the method. To make this connection, three approaches were proposed to systematically predict the power requirements, with emphasis on reserve power determination. A kinematic approach used velocity, acceleration, distance, and time relationships to make a first-order approximation of power. A simulation technique isolated a narrow range of acceptable horsepowers by simulating operating conditions. An optimization technique obtained a more refined estimate by considering the actual operation of a piece of equipment and the cost of operation. Results of the simulation can be used in the optimization model to provide a more direct link between operating conditions and necessary equipment characteristics. The proposed methods were compared, and the form and application of the results of each method were discussed. Field studies were then conducted to explore their feasibility and to validate the selection of key parameters. The probable uses of these approaches were emphasized, recommendations for further related work were made, and conclusions were reported.