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According to European Union strategies, hydrogen technologies have a significant potential for the decarbonization of the automotive sector. Fuel Cells are considered a highly sustainable alternative to internal combustion engines for hybrid powertrain solutions. Since experimental tests on real prototypes are extremely costly in terms of time and resources, they represent a limit to the development rapidity of such complex vehicles. Consequently, simulation models are gaining further importance for their intrinsic time- and cost-saving characteristics, while their predictive capability is crucial. Accordingly, the development of the so-called “digital twins” able to accurately represent the real-time digital counterpart of a physical system has become an important research issue.

Hydrogen plays a crucial role towards the decarbonization of the transport sector, whilst most of the challenges for a widespread diffusion of hydrogen-based technologies are related to storage technologies. The use of Metal Hydrides (MH) has been widely recognized as a potential solution thanks to their advantages in terms of high degree of safety, high volumetric storage density, comparatively low operating pressure, the possibility of operation at room temperature and relatively low cost. Since the hydrogenation and dehydrogenation of MH are respectively highly exothermic and endothermic reactions, thermal management of the storage tank is one of the most critical issues to ensure safe and effective operations.

Hydrogen technologies have been widely recognized as effective means to reduce Greenhouse Gases emissions, a crucial issue to target a Carbon-free world aimed by the European Green Deal. Within the road transport sector, electric vehicles with a hybrid powertrain, including battery packs and hydrogen Fuel Cells (FCs), are gaining importance owing to their adaptability to a wide variety of applications, high driving mileages and short refueling times. The control strategy is crucial to achieve a proper management of the energy flows, to maximize energy efficiency and maximize components durability and state of health. This work is focused on the design of an integrated Energy Management Strategy (EMS), whose aim is to minimize the hydrogen consumption, by operating the FC mainly in the high efficiency region while the battery pack works according to a charge sustaining mode. The proposed EMS is composed of a control algorithm and a supervisor.

In the face of the pressing climate crisis, a pivotal shift towards sustainability is imperative, particularly in the transportation sector, which contributed to nearly 22% of global Greenhouse Gas emissions in 2021. In this context, diversifying energy sources becomes paramount to prevent the collapse of sustainable infrastructure and harness the advantages of various technologies, such as Fuel Cell (FC) Hybrid Electric Vehicles. These vehicles feature powertrains comprising hydrogen FC stacks and battery packs, offering extended mileage, swift refueling times, and rapid dynamic responses. However, realizing these benefits hinges upon the adoption of a rigorously validated simulation platform capable of accurately forecasting vehicle performance across diverse design configurations and efficient Energy Management Strategies. Our study introduces a comprehensive microcar hybrid prototype model, encompassing all subsystems and auxiliaries.

Hydrogen technologies are among the main candidates to reduce carbon emissions in the automotive transport sector. Among the innovative solutions, Electric Vehicles (EVs) featuring hybrid powertrains, combining battery packs and hydrogen Fuel Cell (FC) stacks, are gaining prominence in our pursuit of sustainability objectives. Nonetheless, realizing the full potential of these hybrid vehicles hinges on the implementation of efficient Energy Management Strategies (EMS). In this study, we present an integrated EMS approach to achieve extended driving ranges and reduced energy consumption. This is achieved primarily by operating the FC within its high-efficiency range, while ensuring that the battery packs operate in a charge-sustaining mode. The EMS is crafted through an adaptive algorithm that takes into account various driving conditions to establish the most suitable sub-optimal control strategy.