The baseline assessment analysis for total cost of ownership of the pilot demonstrations of the ESCALATE project was carried out for four different powertrain configurations, dealing with modular and scalable powertrains for various vehicle configurations in long-haul trucking. The baseline TCO methodology and results for battery electric trucks (BETs), fuel cell electric trucks (FCETs) and FC range-extending BETs are analysed based on the final designs of the demonstrator vehicles and their foreseen pilot use cases and operational scenarios. As real operation data is not yet available, the analysis relies on energy use and pilot mission analysis through simulation. Overall, the TCO analysis shows several key factors affecting the relative competitiveness of the different zero-emission powertrains and vehicles. Long-haul operations pose clear challenges to vehicle design and long-range vehicles on single charge or refill show increased curb weight, limiting allowable payload due to GVW limits. The best payload capacity is shown for opportunity charging BETs and FCETs. BETs are generally the closest competitor to conventional trucks, but a key factor is the relative energy price difference between diesel, electricity (private or public) and hydrogen. Energy sourcing will be an important factor for end users to enable competitive shift to zero-emission options. Access to cheap private electricity or local green hydrogen may facilitate a choice between the options.

Hybrid heavy-duty vehicles powered by multiple fuel cells (FCs) offer opportunities to improve energy efficiency and support sustainable powertrain operation through powertrain-level optimization. This study investigates optimal gear shifting to reduce the electrical-power demand of the electric machine (EM) and optimal power distribution among multiple FCs with different ageing states. A longitudinal vehicle model determines the wheel power demand and propagates the operating point backward through the drivetrain. An optimization-based gear-selection strategy identifies the gear that minimizes the required EM power, while a closed-form optimization method optimally distributes a given total FC power demand among multiple FCs according to the specific electrical energy output and remaining useful life of each FC. An active-set procedure enforces FC operating limits. The methods are evaluated using a Paris–Munich ESCALATE drive cycle and several FC age configurations. Depending on the operating point, optimal gear selection reduces EM power demand by up to 50 kW, while optimal FC power distribution reduces hydrogen-consumption rate by up to $3.1\%$ and $3.3\%$ compared with equal power distribution for dual and three-FC configurations, respectively. The optimized allocation may also have implications for long-term FC ageing and maintenance planning, providing an additional perspective for future assessments of powertrain sustainability.