Abstract

The present work proposes an in-deep analysis of a heuristic control strategy, developed in such a way as to enhance model-based design of fuel cell hybrid electric vehicles (FCHEVs). Particularly, suited normalization and denormalization techniques are proposed, so as to adapt optimized control rules to a number of FCHEV powertrains, ranging from low to high degree of hybridization. A scenario analysis was conducted to verify the effectiveness of proposed powertrain-adaptable control strategies, thus revealing their high potential, both to reduce the off-line development phase, as well as to enable simultaneous preliminary optimization of FCHEV powertrain sizing and real-time energy management.

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