We are seeking two highly motivated PhD students who are interested in pursuing research at the interface of control systems and optimization for clean aviation technologies. Electrified airplanes promise to enable clean and fast mobility alternatives to current kerosene-powered solutions, but their development is still restricted by technological limitations. In this context, the development and integration of hydrogen-based electrified propulsion systems pose challenges to the aviation industry that require interdisciplinary approaches. This project explores an integrated power plant system where a propeller is powered by a hydrogen-burning gas turbine and an electric motor which, in turn, is powered by a solid oxide fuel cell (SOFC) and a battery. The steam generated by the SOFC is fed to the burner of the gas turbine to reduce emissions. Within this research context the following two PhD positions are opened with the aim to devise high-level online control strategies to operate such a strongly interconnected system.

PhD 1: The first position aims at identifying computationally tractable optimization models for power and energy distribution via quasi-steady-state (QSS) modeling methods. The goal is to strike a trade-off between model accuracy and computational tractability, identifying appropriate model structures for the individual components, and validating the resulting models via high-fidelity simulations capturing the strong interconnections between the thermal and the chemical-electrical parts. These models will then be integrated within numerical optimal control frameworks and used for numerical optimization purposes by PhD 2. For this position, knowledge and experience in aerospace and aircraft engineering, and (convex) optimization will be preferred.

PhD 2: The second position is aimed at computing global high-level control strategies. To this end, the candidate is expected to use rule-based methods to devise simple, suboptimal energy management algorithms based on efficiency models, and also leverage the optimization models identified by PhD 1 to derive and compute optimal control policies for fixed-operating point and transient scenarios. Such policies are to be implemented online (e.g., similar to ECMS in automotive) and fed to low-level controllers. To this end, Model Predictive Control (MPC) algorithms will also be investigated. For this position, knowledge and demonstrated experience with optimal control, MPC and optimization tools (such as CasADi, IPOPT and Yalmip) will be preferred.

These positions are part of a joint interdisciplinary Horizon Europe project between the Control Systems Technology section in the Department of Mechanical Engineering at TU/e, the German Aerospace Center (DLR), Cranfield University, Università degli Studi di Genova, Safran and Karlsruhe Institute of Technology. During the project, the candidates will have opportunities to mentor students at many levels and take part in international scientific events.