TU Delft mission simulator determines the best mission trajectory and power management for hybrid-electric aircraft

Delft University of Technology developed a mission simulator over the past year with the intention to determine the best mission trajectory and power management for both the fuel-cell aircraft (Hy4) and the hybrid-electric ICE (Panthera) aircraft.

Fig. 1: An overall optimization block diagram

The simulator is composed by an optimizer that finds the best “Control variables” by evaluating several subroutines, namely:

  • The “aerodynamic flight performance”: the flight characteristics of the aircraft are computed by considering the Equation of Motion of the aircraft by assuming a certain aircraft aerodynamics (drag polar). Ultimately, for a certain value of the Control variables, the required flight power is determined.
  • The HEPS model: in this branch, the powertrain is divided into its (sub) components following the modular approach that has been developed in the first phase of the MAHEPA project. The efficiency of each component (propeller, motor, Fuel Cells, Batteries, etc.) is then introduced by means of either actual measurements done by the other partners, or analytical models. Ultimately the Battery State of Charge, as well as the Fuel or Hydrogen utilization is calculated.
  • The optimization algorithm that computes a certain cost function set by the user (total fuel burnt over the entire mission, or total energy or mission time) in presence of given flight constraint such as no stall, battery remaining SOC etc.

The mission simulator provides two approaches to the optimization problem: the first one is single-phase, where the mission is considered as a whole. This is advantageous in terms of computational time, but some aspects cannot be fully reproduced, such as the different aerodynamics due to the deployment of the flaps. On the other hand, the multi-phase approach allows a distinction to be made between various flight segments, such as take-off, climb, cruise, etc., and specific power-intense manoeuvres. This subdivision into several segments requires additional boundary conditions and thus computational effort to solve the problem.

The flight mission parameter of the hybrid-electric Panthera aircraft are plotted in Fig. 2 considering a flight range of 1000 km. The plots are preliminary and will be validated trough the flight test of the actual aircraft in the next months.

Fig. 2: A flight mission parameter of hybrid-electric Panthera aircraft

The different colors represent different costs function. The black line refers to a minimum time mission and the red line represent minimization of the burnt fuel. It can be noted that both control variables and mission characteristics (otherwise defined as State variables) greatly differ, depending on the considered objective.

The simulator is an important step towards the comprehensive evaluation of flight characteristics, as well as to exploit the powertrain through the best management of the energy source. Due to its modular approach, it allows the consideration of different aircraft as well as different powertrains. Future activities will be dedicated to the simulator’s validation by evaluating possible solutions through actual test flights.