Antonakis, AristeidisNikolaidis, TheoklisPilidis, Pericles2017-05-042017-05-042017-04-30Antonakis A, Nikolaidis T, Pilidis P. (2017) Multi-objective climb path optimization for aircraft/engine integration using Particle Swarm Optimization. Applied Sciences, Volume 7, Issue 5, April 2017, Article number 4692076-3417http://dx.doi.org/10.3390/app7050469https://dspace.lib.cranfield.ac.uk/handle/1826/11848In this article, a new multi-objective approach to the aircraft climb path optimization problem, based on the Particle Swarm Optimization algorithm, is introduced to be used for aircraft–engine integration studies. This considers a combination of a simulation with a traditional Energy approach, which incorporates, among others, the use of a proposed path-tracking scheme for guidance in the Altitude–Mach plane. The adoption of population-based solver serves to simplify case setup, allowing for direct interfaces between the optimizer and aircraft/engine performance codes. A two-level optimization scheme is employed and is shown to improve search performance compared to the basic PSO algorithm. The effectiveness of the proposed methodology is demonstrated in a hypothetic engine upgrade scenario for the F-4 aircraft considering the replacement of the aircraft’s J79 engine with the EJ200; a clear advantage of the EJ200-equipped configuration is unveiled, resulting, on average, in 15% faster climbs with 20% less fuel.enAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/aircraft/engine integrationtrajectory optimizationmulti-objective optimizationparticle swarm optimizationArticle