Power optimization of the environmental control system for the civil more electric aircraft. (1st April 2019)

• Record Type: Journal Article
• Authors: Yang, Yuanchao; Gao, Zichen
• Is Part Of: Energy. Volume 172(2019)
• Page Start: 196
• Page End: 206
• Publication Date: 2019-04-01
• Subjects: Civil more electric aircraft -- Environmental control system -- Power optimization -- Benders decomposition method -- Successively linear programming; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2019.01.115
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: As the civil aviation industry moves toward to the more-electric-aircraft (MEA) concept, environmental control system (ECS), one of the largest power consumption non-propulsive systems for civil aircraft, converts its power extraction source from bleed air to electric power and thus will introduce new challenges on ECS's design and operation management schemes. One of these challenges is for the power optimization of ECS, which was an optimal sizing and planning problem for ECS air circulation pack, but under the MEA environment will be transformed into a complex power scheduling problem integrated with the constraints on the controllable electrical power generation and varying thermal power demands determined by the aircraft's flight profiles. In this paper, we propose a complete mathematical optimization formulation for the power optimization of ECS for MEA and cast it as a non-convex nonlinear program. We provide a solution approach to tackle this problem based on a combination of Benders decomposition method and the successively linear programming technique and illustrate the capabilities of the proposed solution approach on an aircraft's ECS under the civil MEA environment. The numerical results demonstrate the effectiveness of the proposed solution approach in terms of the associated computational outcomes. Highlights: Power optimization of ECS for MEA is formulated as a nonlinear optimization problem. An efficient method is provided to solve the above problem on real ECS of civil MEA. Test results are demonstrated based on real civil MEA revealing the effectiveness.