As the last in line of our PhD interview series of our project partner RWTH, we spoke with Maximilian Pietruck, who also coordinated the exchange between the students and POLIS as the interviewer. The researcher is providing the ESCALATE pilots with data for the development of modular powertrains.
Please describe your research to a wider stakeholder audience and highlight innovative aspects.
My research focuses on the economic and thermal challenges of fuel cell trucks. Economic aspects, like the comparably high purchasing- and operating costs, and the thermal management of the fuel cell require solutions to guarantee the operability of such trucks.
Additionally, these two facets are both connected to soft- and hardware aspects. On the hardware side, application-specific component dimensioning provides valuable benefits. In contrast to the state of the art, a modular design and holistic optimisation of the drive and thermal components can improve performance and range while also reducing costs. On the software side, a predictive operating strategy provides significant improvements.
Thermally critical situations can be recognised at an early stage, and countermeasures such as predictive charging of the battery and cooling of the components help to maintain the vehicle’s performance. Furthermore, both approaches can be combined to be able to use even smaller and more cost-effective components from the get-go.
What is the connection with the ESCALATE project? How do you benefit from the project, and what synergies exist?
My research is entirely part of ESCALATE and is connected to the development of modular powertrains. The technologies developed will later be used in the five pilot vehicles.
The vehicle manufacturers provide basic information and framework conditions regarding the prototypes to be developed. For example, the available installation space serves as an input variable for the component dimensioning.
The future vehicle users are also involved in the development. They know exactly where the pilot vehicle will later be used. This allows me to estimate the load profile of the application in the best possible way and design the components to suit it.
In general, a large number of partners from a wide variety of domains are involved in the project. Their specific expertise helps me to refine my analyses at the system level and gain detailed insights.
With your expertise and the perspective of your research, where do you currently see the biggest challenge in a large-scale deployment of zero-emission trucks?
Fuel cell trucks perform well and represent a promising alternative to diesel-powered long-distance trucks. However, the total cost of ownership (TCO) plays a very important role in the commercial vehicle sector. A fleet operator will only accept higher costs for fuel cell trucks if another user criterion, such as range or maximum payload, is significantly better, giving them a clear advantage. Due to the high hydrogen costs, the operating costs currently outweigh the purchase costs and represent the greatest leverage. Oversizing the fuel cell can help here, as the operating points are shifted to the direction of partial load and efficiency increases, respectively, consumption is reduced. But the optimum between purchase and operating costs is quickly reached. I therefore see the hydrogen infrastructure as the biggest challenge.
What do you think could be the impact (or lack thereof) of projects like ESCALATE on the promotion of zHGV technology/solutions?
Demonstrating the functionality of electrified trucks using the pilot vehicles will hopefully change the minds of some sceptical fleet operators and encourage them to try out these new drives for themselves. Our research in the project also shows that the disadvantages of these vehicles can be minimised through intelligent approaches. The component dimensioning I developed enables cost savings of up to 20%, while the predictive operating strategy improves efficiency by around 7%. As soon as more fleet operators use such vehicles and production volumes increase, economies of scale will reduce costs even further.
Since FCEVS are rare, what are your real-world data sources?
The actual application of the long-distance truck depends on the drive type. The vehicle user provides me with the route, and I determine the corresponding load profile using up-to-date map, traffic and weather data. Vehicle-specific data is somewhat more difficult to obtain. However, it is helpful that many drive components, e.g. the electric motors and the battery, are also used in battery electric vehicles, and suitable data is more widely available. Fortunately, I was also able to access real data for the fuel cell, as Ballard, a well-known fuel cell manufacturer, was part of the consortium.