Flight-Path Optimization for a Hybrid-Electric Aircraft

Author:

Papadopoulos Konstantinos I.1,Nasoulis Christos P.1,Gkoutzamanis Vasilis1,Kalfas Anestis I.1

Affiliation:

1. Aristotle University of Thessaloniki, Laboratory of Fluid Mechanics and Turbomachinery, Department of Mechanical Engineering, GR-54124, Thessaloniki, Greece

Abstract

Abstract This study aims to illustrate a sequence that optimizes the flight-path trajectory for a hybrid-electric propulsion system at mission level, in addition to identifying the respective optimum power management strategy. An in-house framework for hybrid-electric propulsion system modeling is utilized. A hybrid-electric commuter aircraft serves as a virtual test-bench. Vectorized calculations, decision variable count and optimization algorithms are considered for reducing the computational time of the framework. Performance improvements are evaluated for the aircraft's design mission profile. Total energy consumption is set as the objective function. Emphasis lies on minimizing the average value and standard deviation of the energy consumption and timeframe metrics. The best performing application decreases computational time by two orders of magnitude, while retaining equal accuracy and consistency as the original model. It is employed for creating a dataset for training an artificial neural network against random mission patterns. The trained network is integrated into a surrogate model. The latter part of the analysis evaluates optimized mission profile characteristics with respect to energy consumption, against a benchmark flight-path. The combined optimization process decreases the multi-hour-scale timeframe by two orders of magnitude to a 3-minute sequence. Using the novel framework, a 12% average energy consumption benefit is calculated for short, medium and long regional missions, against equivalent benchmark profiles.

Publisher

ASME International

Subject

Mechanical Engineering,Energy Engineering and Power Technology,Aerospace Engineering,Fuel Technology,Nuclear Energy and Engineering

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3