Multi-Objective Supervisory Control in More-Electric Aircraft Using Model Predictive Control: An ORCHESTRA Application

Abstract

The crucial issue of supervising and managing electrical energy in the context of aircraft electrification, known as More-Electric Aircraft (MEA), is addressed in this paper. In the pursuit of developing energy-efficient solutions with reduced environmental impact, this research contributes valuable insights into innovative control strategies crucial for advancing aircraft electrification technologies. Through optimization techniques, the management of energy aims to maximize the proposed objectives. With a focus on controlling battery power for charging, discharging, and load shedding, this study employs Model Predictive Control (MPC) alongside an optimizer solving a mixed-integer linear programming (MILP) problem. Constraints encompass various aspects, including battery charging, maximum generator power, battery absorption, discharge limits, and converter power limitations. Theoretical results and detailed simulations demonstrate the effectiveness of the proposed approach in finding a good compromise among the objectives subjected to the system constraints. Practical validation of the proposed approach is conducted through the European project ORCHESTRA, utilizing comprehensive system simulations in Matlab/Simulink (2022b).

Keywords

• more-electric aircraft
• model predictive control
• optimized power management