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The ultimate goals for developing hybrid power train systems are improving fuel economy, reducing emissions and providing commercially viable alternative low cost transportation solutions. To achieve these goals, during hybrid system design and development, a well defined set of targets and specifications are needed. These targets and specifications are necessary for optimizing the power train subsystems, components, successful system integration, and the development of proper control system. For developing a set of well defined targets and specifications, especially when dealing with hybrid power train systems, valid and reliable road load data and duty cycle profiles are required. This data is one of the most critical elements in sizing and control of the hybrid system components such as engines, batteries, generators, and motors.

A multi-objective optimization procedure has been developed to optimize the vehicle longitudinal acceleration and steady-state fuel economy. A 5-speed manual-transmission vehicle is adopted for the prediction of the 0 - 60 mph acceleration time. A simplified fuel economy model is used to simulate the fuel consumption under steady vehicle speed. The optimization algorithm selected is the Modified Method of Feasible Directions due to its high reliability and efficiency. A notable feature of the optimization process adopted is that the algorithm can compromise between the competing performances while meeting the requirements for the ride and handling quality of the vehicle.