This article addresses the architecture development for a commercial vehicle fuel
cell electric powertrain by establishing a clear multi-step formalized workflow
that employs a unique technoeconomic solution for architecture selection. The
power capability of the fuel cell, the energy capacity and chemistry of the
electrical energy storage (battery), the DC-DC converter (including the input
current rating and isolation resistance requirements), the traction drive
solution, the on-board hydrogen storage solution, and the real-time power-split
management of the fuel cell and the battery are all considered and developed in
this effort. The methods were used to select architecture for Class 8 urban,
regional, and line haul applications. When compared to traditional
load-following power-split controllers, an energy management power-split
controller can increase system energy efficiency by up to 19.5%. The
energy-efficient power-split controller may increase the required battery
capacity for an equivalent life by up to 2.6 times. The impact on the total cost
of ownership (TCO) for a variety of financial cases demonstrates that high
C-rate capable batteries have the potential to provide better TCO solutions over
a six-year vehicle life than low C-rate capable batteries. To achieve TCO parity
with the 600 A non-isolated DC-DC converter case, the specific choice of the
fuel cell DC-DC converter to achieve a target power output based on current
levels (from 500 A to 2400 A) shows that efficiency decreases and cost increases
due to the higher current, requiring fuel cell prices to decrease by
$50–$100/kW, $60–$110/kW, and $100–$220/kW for urban, regional, and line haul
applications, respectively. Key recommendations for powertrain system
architectures are provided, with specifics based on vehicle dynamics, mission
and application characteristics, end customer use-case profile, critical
powertrain component costs, and architecture selection cost function. This study
rigorously demonstrates the interplay of the above parameters, with a focus on
TCO, and provides application decision-makers with a mechanism and well-defined
set of impact factors to consider as part of their architecture selection
process.
