Performance assessment of a multi-fuel hybrid engine for future aircraft

Feijia Yin, Arvind Gangoli Rao, Abhishek Bhat, Min Chen

Research output: Contribution to journalArticleScientificpeer-review

9 Citations (Scopus)
84 Downloads (Pure)

Abstract

This paper presents the performance assessment of a novel turbofan engine using two energy sources: Liquid Natural Gas (LNG) and kerosene, called Multi-Fuel Hybrid Engine (MFHE). The MFHE is a new engine concept consisting of several novel features, such as a contra-rotating fan to sustain distortion caused by boundary layer ingestion, a sequential dual-combustion system to facilitate “Energy Mix” in aviation and a Cryogenic Bleed Air Cooling System (CBACS) to cool the turbine cooling air. The MFHE has been envisaged as a propulsion system for a long-range Multi-Fuel Blended Wing Body (MFBWB) aircraft. In this research, we study the uninstalled characteristics of the MFHE covering three aspects: 1) the effects of CBACS on the High Pressure Turbine (HPT) cooling air requirement and its consequence on the engine cycle efficiency; 2) the cycle optimization of the MFHE; 3) the performance of the MFHE at a mission level. An integrated model framework consisting of an engine performance model, a sophisticated turbine-cooling model, and a CBACS model is used. The parametric analysis shows that using CBACS can reduce the bleed air temperature significantly (up to 400 K), thereby decreasing the HPT cooling air by more than 40%. Simultaneously, the LNG temperature increases by more than 200 K. The hybrid engine alone reduces the CO2 emission by about 27% and the energy consumption by 12% compared to the current state-of-the-art turbofan engine. Furthermore, the mission analysis indicates a reduction in NOx emission by 80% and CO2 emission by 50% when compared to the baseline aircraft B-777 200ER.
Original languageEnglish
Pages (from-to)217-227
JournalAerospace Science and Technology
Volume77
DOIs
Publication statusPublished - 2018

Keywords

  • Hybrid engine
  • Low emissions
  • Multi-fuel
  • Optimization

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