In an ever-evolving landscape of emission regulations, charging infrastructure,
customer demands, fuel/energy costs and decarbonization goals, heavy-duty
on-road vehicle manufacturers continue to evaluate alternative powertrain
technologies. While most heavy-duty vehicle manufacturers now have battery
electric vehicles (BEVs) in their portfolio, significant challenges of charging
infrastructure, range anxiety, payload capacity reduction and upfront costs have
contributed to their lower adoption rates. Plug-in hybrid electric vehicles
(PHEVs) have significant potential of leveraging upcoming BEV infrastructure and
component supply chains to reduce operating costs while still maintaining longer
range and payload capacity benefits of conventional ICE powertrains.
This article applies a model-based approach to evaluate multiple Class 7–8
heavy-duty powertrain configurations. A system-level (1D) model of the
conventional diesel ICE-based truck was developed in GT-Suite and validated
against on-road test data. Using the diesel ICE model as a baseline,
system-level models for different hybrid configurations were adapted, and their
powertrain architecture was optimized at the system level. Additionally, an
equivalent consumption minimization strategy (ECMS) for energy management was
also optimized for each of the hybrid powertrain configurations to maximize fuel
efficiency and emission benefits. All the hybrid configurations were then
compared against the conventional diesel ICE Class 8 truck in terms of
performance (acceleration, top speed, gradeability and startability), fuel
economy (real-world cycles and certification cycles), emissions, and range for
long-haul applications. Unique to this approach is the simultaneous
co-optimization of powertrain component sizing and supervisory control logic by
utilizing a Genetic Algorithm–based optimization approach. Results indicate that
all parallel hybrid architectures (P2, P2–P3, and P4) achieve performance
(acceleration, top speed, gradeability, and startability) parity or improvement
compared to baseline diesel architecture. P2-based architectures demonstrated a
12–14% improvement in fuel economy on representative real-world cycles when
operating in a blended charge-depleting–charge-sustaining mode of operation, and
a 4–6% improvement in fuel economy when operating in charge-sustaining mode
alone. By quantifying these results across diverse topologies, this work
addresses a significant research gap in the holistic evaluation of Class 8
hybrids, specifically, the trade-off between multi-speed electric drives,
system-level mass increases, and real-world fuel economy, that remains
underexplored in current literature.
