Multi-Objective Optimization of a Regenerative Rotorcraft Powerplant: Quantification of Fuel Economy and Environmental Impact

A computationally efficient and cost effective simulation framework has been proposed to perform a multidisciplinary design and optimization of a conceptual regenerative rotorcraft powerplant configuration at mission level. A generic rotorcraft model, representative of a modern twin-engine light civil rotorcraft has been investigated, operating under a representative passenger air taxi mission. The design space corresponding to the conceptual regenerative engine thermodynamic cycle parameters as well as engine and mission design outputs in terms of low pressure compressor pressure ratio, high pressure compressor pressure ratio, turbine entry temperature, mass flow, heat exchanger effectiveness, engine design point specific fuel consumption, engine weight, mission fuel burn and mission CO₂ and NO_x emissions has been thoroughly investigated through the application of a latin hypercube sampling, design of experiment approach. The interdependencies between the various engine design inputs/outputs are quantified by establishing the corresponding linear correlations between the aforementioned engine inputs/outputs as well as for the corresponding mission output parameters. A multi-objective Particle Swarm Optimizer is employed to derive Pareto front models quantifying the optimum interrelationship between the mission fuel burn and NO_x emissions inventory. The acquired engine cycle design parameters corresponding to the span of the Pareto front suggest that the heat exchanger design effectiveness is the key design parameter representing the interdependency between engine fuel economy and environmental impact. The acquired optimum engine models, obtained from the Pareto front, are subsequently deployed for the design of conceptual rotorcraft engine configurations, targeting improved mission fuel economy, enhanced payload-range capability and overall environmental impact.