A study of various energy- and exergy-based optimisation metrics for the design of high performance aircraft systems

This paper shows the advantages of applying exergy-based analysis and optimisation methods to the synthesis/design and operation of aircraft systems. In particular, an Advanced Aircraft Fighter (AAF) with three subsystems: a Propulsion Subsystem (PS), an Environmental Control Subsystem (ECS), and an Airframe Subsystem - Aerodynamics (AFS-A) is used to illustrate these advantages. Thermodynamic (both energy and exergy based), aerodynamic, geometric, and physical models of the components comprising the subsystems are developed and their interactions defined. Off-design performance is considered as well and is used in the analysis and optimisation of system synthesis/design and operation as the aircraft is flown over an entire mission. An exergy-based parametric study of the PS and its components is first presented in order to show the type of detailed information on internal system losses which an exergy analysis can provide and an energy analysis by its very nature is unable to provide. This is followed by a series of constrained, system synthesis/design optimisations based on five different objective functions, which define energy-based and exergy-based measures of performance. The former involve minimising the gross takeoff weight or maximising the thrust efficiency while the latter involve minimising the rates of exergy destruction plus the rate of exergy fuel loss (with and without AFS-A losses) or maximising the thermodynamic effectiveness. A first set of optimisations involving four of the objectives (two energy-based and two exergy-based) are performed with only PS and ECS degrees of freedom. Losses for the AFS-A are not incorporated into the two exergy-based objectives. The results show that as expected all four objectives globally produce the same Optimum vehicle. A second set of optimisations is then performed with AFS-A degrees of freedom and again with two energy- and exergy-based objectives. However, this time one of the exergy-based objectives incorporates AFS-A losses directly into the objective. The results are that with this latter objective, a significantly better Optimum Vehicle is produced. Thus, an exergy-based approach is not only able to pinpoint where the greatest inefficiencies in the system occur but appears at least in this case to produce a superior optimum vehicle as well by accounting for irreversibility losses in subsystems (e.g., the AFS-A) only indirectly tied to fuel usage.