Abstract

Developing successful fuel cell hybrid vehicles (FCHVs), to be destined to the widest deployment within the entire transport sector, is nowadays considered as a highly strategic target to fully meet well known environmental and regulatory constraints at international level. This happens thanks to the intrinsic overall superior features of fuel cell propulsion when compared to both electric and hybrid vehicles, such as high fuel-economy, reduced tank-to-wheel environmental impact and good ranges. Successful achievement of the above-introduced challenging goal motivates the research activity presented and discussed in this paper, namely the development of an advanced mathematical tool featuring co-optimization capabilities. The reason for such a requirement lies in the well-known strong interactions and mutual influence between selected design criteria and adopted control strategies. Therefore, a comprehensive model of a generic FCHV architecture and a specification independent control strategy, thus adaptable to different fuel cell system and battery sizes, were preliminary developed. Then, they were integrated and embedded within a modular constrained optimization algorithm, which was conceived in such a way as to simultaneously find the optimal FCHV powertrain design, as well as real-time applicable control strategies. Suitable design and energy management criteria were investigated on a selected driving cycle, in such a way to explore several powertrain configurations (i.e. more hybrid, as well as more plugin and range-extender like FCHV). This allowed verifying the suitability of the proposed procedure to yield solutions ensuring low hydrogen consumption (i.e. fuel economy as high as 135 km/kg) and full alignment with targeted energy management policies. Discussion of results, together with the physical meaning of main design and control variables provided as outcomes, underline the effectiveness of the proposed tool in providing a solid support in the preliminary design of cost-effective fuel cell powertrains destined to a variety of applications and driving habits.

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