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The fuel cell engine is considered to be the ultimate technical direction for the development of vehicle power. The on-board hydrogen supply system is important in fuel cell system. However, the on-board hydrogen supply system is diversified, and the management is mostly integrated in the engine controller. Thus, the fuel cell engine controller is excessive coupled with design of on-board hydrogen supply system. In order to improve the portability and compatibility of the fuel cell engine controller, an independent controller of the on-board hydrogen supply system is designed. Meanwhile, the hardware and software are developed to control 35Mpa gaseous hydrogen storage system. After being tested in a high-pressure environment, the controller can detect temperature, pressure and ambient hydrogen concentration of the hydrogen supply system. Simultaneously, it can drive and control the hydrogen cylinder valve.

This paper is contributed to determining model parameters for DMFCs. Theoretical evaluations are carried out to set up the relationship between the unknown and measurable parameters or variables. A laboratory-scale liquid-feed cell was simulated under different operating conditions. The resulting measurable static performance curves are used as basic information. Some key kinetic and physical parameters can be determined or estimated for a DMFC model.

It is recognized that the heavier vehicles, the more emissions, thus the more imperative to electrify. In this study, long haul heavy-duty trucks are referred as HDTs, which are recognized as one of the hard-to-electrify vehicle segments, though the automotive industry has gained trending advantages of electrifying both light-duty cars and SUVs. Since big rigs such as Class 8 HDTs have significant road-block challenges for electrification due to the demanding long-hour work cycles in all weathers, this study focuses on quantifying those electrification challenges by taking advantage of the public data of Class 8 tractors & trailers. Tesla Semi is the research target though its vehicle spec data is sorted out with fragmentary information in the public domain. The key task is to analyze the battery capacity requirements due to environmental temperature and inherent aging over the lifespan.