Mission Management for Fuel Cell Electric Trucks

Thesis Background
Sustainability including climate change are the challenges of our generation. Our contribution is to offer leading transport and infrastructure solutions enabling societies to prosper in a sustainable way. At Volvo group, we are committed to the ambitions and climate change goals of the Paris Agreement. From a lifecycle perspective, most of the emissions occur during the use phase of our products. Therefore, our priority is to develop solutions that reduce the carbon emissions from transportation. One such transport solution that we are working on today is Fuel Cell Electric Vehicle (FCEV) for demanding long-haul applications, that is to complement the Battery Electric Vehicles (BEV), which have a limited range.


We are Vehicle Energy Management team at Group Trucks Technology (GTT). As the team’s name suggests, we work in the area of energy management, where we optimize the vehicle energy using the predicted information such as topography, curvature, and speed limits from the road ahead of the vehicle. Our goal is to deliver a platform solution to optimize the energy consumption for all three powertrain variants in Volvo (ICE, Fuel Cell and BEV (Battery Electric Vehicles).


We have been working in this technology area for several years, not just internal projects, but also within some European projects. We have also had two thesis workers in spring 2023 in this area. [1].


With this master-thesis, we hope to build upon the knowledge we have gained so far and take it further.
Problem Motivating the thesis
These new technologies bring several operational and engineering challenges compared to conventional ICE (Internal Combustion Engine) trucks, some of which we want to solve by doing Mission Management, by optimizing over the whole transport mission.
Operational Challenges for a FCEV
The amount of energy that can be stored in a Fuel Cell truck is significantly lower compared to a diesel truck, which significantly lowers the range one can drive with a single refueling. Moreover, as Hydrogen refueling stations are expensive to build, the density of fueling stations are going to be low, also resulting in ques at the stations. Also, the fuel prices may vary between stations.
Technical Challenges for a FCEV
Batteries in a Fuel Cell Electric trucks is smaller compared to BEVs (Battery Electric Vehicles), so to recuperate/break with max capacity its desirable to empty the battery before a downhill.
Fuel Cell systems have a slow transient response, and transients and turning the fuel cells On and Off has an impact on the FC health.

Doing a global optimization of the whole transport mission, considering the location of fueling stations and fuel price, vehicle characteristics, topography, mission requirements, traffic, weather etc. has a potential to solve these challenges.








Description of thesis work
In the prior thesis work done by Sundström and Bragde [1], we explored the limitations and benefits of having such an optimization layer with full mission information. The problem was formulated to optimize the Total cost of operation (TCOP), where speed was one of the optimization variables among other variables like FC power, battery power, fuelling stop etc. In this thesis we will work with a fixed speed (user input) to reduce the numerical complexity and explore other aspects like traffic and robust selection of fuel stations. There is a probability that the refueling slot proposed by the optimization is missed because of traffic or other disruptions. In this thesis, we want to explore how to make robust selection of refueling options that update with time.
Objective or Research Question
How can we optimize the total cost of operation (TCOP) of the mission for a FCEV application, for a fixed cruising set speed (user input)?
What are the important parameters and dynamics to consider for mission management of FCEV?
How to improve robustness of the proposed plan by incorporating traffic scenarios, and risk of missing a booked slot at refueling stations.
How to formulate the optimization problem considering temporal variables like traffic, que times, fuel price etc.?

Deliverables (flexible)
Formulation of the optimization problem.
Integration with Complete Vehicle simulation models (provided by Volvo).
Simulation analysis is done on a few use cases and input parameters (provided by Volvo).

References
[1] A. Bragde , D. Sundberg (2023) Mission Management for fuel cell heavy-duty trucks, URL: https://odr.chalmers.se/bitstreams/c1823eca-d0fa-4e0d-b9d3-2620fa9d7354/download
Suitable background


Master students in Automotive, Control, Mechatronics or Engineering Physics.
Interest in Control, Optimization
Good MATLAB/Simulink skills
Please submit your CV and motivation letter.



Thesis Level: Master

Language: English


Starting date: 15 January 2024


Number of students: 1 or 2


Physical location: Mostly at Volvo GTT, Lundby, Gothenburg


Tutor:
Saurabh Suman(+46-765538677), saurabh.suman@volvo.com
Olof Lindgärde(+46 76 5535910), olof.lindgarde@volvo.com