Convex Optimization Methods for Powertrain Sizing of Electrified Vehicles by Using Different Levels of Modeling Details

Abstract

This study investigates the impact of different levels of modeling details on the problem of optimizing the total cost of ownership of a fuel-cell hybrid electric vehicle. In this optimization, the objective function is a weighted sum of operational and component costs over a driving cycle. The former includes the consumed hydrogen and electrical energy, and the latter includes the sum of the battery, fuel-cell, and electric-motor costs. Three methods with different levels of modelling details are investigated; in the first method, the power split between the two power sources together with component sizes are optimized, while assuming nonlinear loss functions for the components. In the second method, the efficiencies of the components are approximated by constant values. In the third method, the problem is simplified further by considering the energy split between the battery and the fuel-cell. As shown in the results, a more detailed model gives more accurate results at the price of increased computation time. However, the simplified models can give similar results as the detailed model in most cases. In some problems though, the model simplifications lead to results that differ notably from those obtained by using the detailed model.