Intelligent-based hybrid-electric propulsion system for aero vehicle
| dc.contributor.advisor | Tsourdos, Antonios | |
| dc.contributor.advisor | Economou, John T. | |
| dc.contributor.author | Wang, Siqi | |
| dc.date.accessioned | 2023-09-28T09:09:43Z | |
| dc.date.available | 2023-09-28T09:09:43Z | |
| dc.date.issued | 2020-03 | |
| dc.description.abstract | To address the sustainability challenges for air transport, electrified aviation delivers promising benefits to the whole air transportation system. Focusing on reducing environmental impact and raising competitiveness, this thesis presents a research regarding the Distributed Series Hybrid-electric Propulsion System for aero vehicles, which involves study fields of system configuration design, component sizing and energy management strategies. Based on the state-of-art of hybrid-electric aircraft and hybrid-electric propulsion systems, the study firstly improved the conventional series hybrid configuration by adopting distributed propulsion technology and more electric aircraft concept. These improvements can compensate for the drawbacks caused by the conventional series hybrid layout, so that the new designed propulsion system has the potential to reduce system weight and increase fuel economy. After that, a comprehensive sizing method was particularly designed for the proposed system. The engine, as the primary power source, was firstly selected via the battery parametrisation criteria. Then, other components were selected according to a proposed sizing flowchart by using the genetic algorithm. System performance can also be demonstrated during the sizing process. Finally, three different control methods had been applied to manage energy flows. The first supervisory controller is a deterministic rule-based controller, which was designed based on human experiences and can reduce 12% fuel consumption. The second is a battery-friendly fuzzy controller. It was particularly designed to improve the battery operating environment and can simultaneously achieve a 5% improvement on fuel economy compared to the rule-based. The third controller applied model predictive control algorithm, which can further improve the fuel efficiency by 4% and reveal the relationship between the fuel consumption and emissions. | en_UK |
| dc.description.coursename | Aerospace | en_UK |
| dc.identifier.uri | https://dspace.lib.cranfield.ac.uk/handle/1826/20282 | |
| dc.language.iso | en | en_UK |
| dc.publisher | Cranfield University | en_UK |
| dc.publisher.department | SATM | en_UK |
| dc.rights | © Cranfield University, 2020. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright holder. | en_UK |
| dc.subject | Hybrid-electric Aircraft | en_UK |
| dc.subject | Hybrid-electric Propulsion System | en_UK |
| dc.subject | Series Hybrid System | en_UK |
| dc.subject | Sizing | en_UK |
| dc.subject | Fuzzy Controller | en_UK |
| dc.subject | MPC Controller | en_UK |
| dc.subject | Energy Management | en_UK |
| dc.title | Intelligent-based hybrid-electric propulsion system for aero vehicle | en_UK |
| dc.type | Thesis or dissertation | en_UK |
| dc.type.qualificationlevel | Doctoral | en_UK |
| dc.type.qualificationname | PhD | en_UK |