Vehicular design, especially for hybrid electric vehicles, is multifaceted and necessarily objective oriented. Whether designing for total cost, performance, societal impact, or any other factor there can be a number of possible solutions but limited optimal solutions. While many efforts to achieve particular vehicle characteristics through systems engineering achieve acceptable designs, they are extremely resource consuming and often restricted to utilization of a handful of available components. Design complexity often exists when designers must choose between different vehicle architectures or powertrain characteristics. Evaluating design options equivalently often entails undergoing multiple design iterations to fully understand the strengths and weaknesses of selected concepts.
Through the use of numerical vehicle modeling, simulation, and optimization many theoretical vehicle configurations can be compared quickly and inexpensively. To aid in this reduction of resources, models are selectively limited to key system components. Each of these components is represented in dynamic operational blocks that can be interchanged and rearranged to accurately characterize a system and provide defensible results. Through the formulation presented in this study, more details, objectives, and methods become available for comparing advanced vehicles across architectures. The main techniques used for setting up the models, simulations and optimizations are discussed along with results of test runs based on chosen vehicle objectives. Utility for the vehicular design efforts are presented through comparisons of available simulation and future areas of improvement are directed.