The increasing need to slow down climate change for environmental protection demands further advancements toward regenerative energy and sustainable mobility. While individual mobility applications are assumed to be satisfied with improving battery electric vehicles (BEVs), the growing sector of freight transport and heavy-duty applications requires alternative solutions to meet the requirements of long ranges and high payloads. Fuel cell hybrid electric vehicles (FCHEVs) emerge as a capable technology for high-energy applications. This technology comprises a fuel cell system (FCS) for energy supply combined with buffering energy storages, such as batteries or ultracapacitors. In this article, recent successful developments regarding FCHEVs in various heavyduty applications are presented. Subsequently, an overview of the FCHEV drivetrain, its main components, and different topologies with an emphasis on heavy-duty trucks is given. In order to enable system layout optimization and energy management strategy (EMS) design, functionality and modeling
Several publications have shown that it is beneficial to design a driver assistance system using a shared control structure. For the steering task this structure can be realized with a setup in which driver and automation can apply a torque on the steering wheel in parallel. Thereby both, driver and assistance system, interact with the vehicle and each other over the haptical channel. In the system the driver is given and cannot be changed. The question is how to design the assistance system controller as an ideal complement to the driver. In this paper a formal design concept is applied to this problem which utilizes the fact that adding a controller to the overall system has to lead to a Nash equilibrium. Remaining degrees of freedom are used to optimize the designed controller with respect to a global objective function that specifies overall system performance. We refer the concept as "cooperative shared control design". For the concept driver and vehicle are modeled as a differential game. We show systematically that this concept can be used to determine the optimal assistance system if the driver characteristics are known. Simulations prove the applicability of this concept.
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