This paper proposes a cost-effective way to design and operate fuel cell hybrid electric trucks (FCHETs) where a chance-constrained optimization is formulated. The aim of the introduced problem is to minimize a summation of component cost and operational cost with consideration of fuel cell (FC) degradation and cycle life of energy buffer. We propose to decompose the problem into two sub-problems that are solved by sequential convex programming. The delivered power satisfies a cumulative distribution function of the wheel power demand, while the truck can still traverse driving cycles with a similar speed and travel time without delivering unnecessarily high power. This allows to downsize powertrain components, including electric machine, FC and energy buffer. A case study considering different energy buffer technologies, including supercapacitor (SC), lithium-ion battery (LiB), and lithium-ion capacitor (LiC) is investigated in a set of trucking applications, i.e. urban delivery, regional delivery, construction, and long-haul. Results show that the power rating of the electric machine is drastically reduced when the delivered power is satisfied in a probabilistic sense. Moreover, the configuration with LiB as the energy buffer has the lowest expense but the truck with LiC can carry more payload.
CITATION STYLE
Xun, Q., Murgovski, N., & Liu, Y. (2022). Joint Component Sizing and Energy Management for Fuel Cell Hybrid Electric Trucks. IEEE Transactions on Vehicular Technology, 71(5), 4863–4878. https://doi.org/10.1109/TVT.2022.3154146
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