Re, Fabrizio (2017)
Model-based Optimization, Control and Assessment of Electric Aircraft Taxi Systems.
Technische Universität Darmstadt
Dissertation, Erstveröffentlichung
Kurzbeschreibung (Abstract)
Aircraft ground operations are one important source of emissions in airports as taxi is conventionally performed by exploiting the inefficient idle thrust of the main jet engines. On-board Electric Taxi Systems (ETS) have been proposed featuring electric motors fitted in the landing gears in order to perform ground movements electrically while the main engines are off. While benefits can be expected on the ground due to the use of the Auxiliary Power Unit (APU) as power source which is more efficient in the required power range, the new system brings additional weight to the aircraft, resulting in a lower efficiency in flight and possibly even worsening the overall fuel consumption in a whole gate-to-gate mission. However, trade-offs and concrete figures regarding the expected benefits are difficult to identify in the state of the art because assessing methods for the taxi phase are often too coarse and based on too generic data and assumptions such as Thrust Specific Fuel Consumption tables, constant thrust settings and estimated taxi times.
This thesis contributes to the state of the art by presenting an integrated, model-based methodology for the assessment of aircraft systems at aircraft level in the conceptual design phase and its application to ETS. The proposed model-based process is shown to be necessary for answering key questions regarding the design of innovative aircraft subsystems in general, for performing solid comparisons and for determining suitable trade-offs while keeping the aircraft type and the specificities of the observed missions into account.
A substantial methodological contribution in the framework of the proposed approach is given by the automatic generation of energetically optimal ground path following profiles for electric taxiing based on convex optimization. Because an optimal path following profile exists for each given system architecture and variant, a sound performance comparison of different system variants is only possible if each of them can be operated according to its own optimal profile. Convex optimization permits to find a global optimum for each given problem in short computational time thanks to dedicated solving toolboxes. Convex formulations of path following problems studied in robotics and vehicle dynamics were adapted to the aircraft taxi problem. Moreover, convex formulations of relevant constraints in this problem, such as time constraints on passing predefined waypoints, were determined. The result of the convex optimization is used as input in the simulation of the mission ground phases with the integrated aircraft model.
The proposed system design methodology based on integrated simulation was instrumental for the following findings in connection with ETS. Firstly, a small system — which is lighter, but also less powerful — does not necessarily result in a further improvement of the benefits compared to larger, heavier systems because ground performance would be affected negatively. Secondly, the physical (e.g. thermal) behavior of the system during a given mission is a key factor as it has an immediate impact on the associated benefit. The optimal system architecture specifically depends on the aircraft and the missions flown; both must be taken into account in the early design phase. Thirdly, the prevailing interest for the ETS technology may be an economic one rather than an environmental one, as electric taxi may be economically viable even in case of increased mission block fuel.
Typ des Eintrags: | Dissertation | ||||
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Erschienen: | 2017 | ||||
Autor(en): | Re, Fabrizio | ||||
Art des Eintrags: | Erstveröffentlichung | ||||
Titel: | Model-based Optimization, Control and Assessment of Electric Aircraft Taxi Systems | ||||
Sprache: | Englisch | ||||
Referenten: | Klingauf, Prof. Dr. Uwe ; Rinderknecht, Prof. Dr. Stephan | ||||
Publikationsjahr: | 2017 | ||||
Ort: | Darmstadt | ||||
Datum der mündlichen Prüfung: | 2 Mai 2017 | ||||
URL / URN: | http://tuprints.ulb.tu-darmstadt.de/6239 | ||||
Kurzbeschreibung (Abstract): | Aircraft ground operations are one important source of emissions in airports as taxi is conventionally performed by exploiting the inefficient idle thrust of the main jet engines. On-board Electric Taxi Systems (ETS) have been proposed featuring electric motors fitted in the landing gears in order to perform ground movements electrically while the main engines are off. While benefits can be expected on the ground due to the use of the Auxiliary Power Unit (APU) as power source which is more efficient in the required power range, the new system brings additional weight to the aircraft, resulting in a lower efficiency in flight and possibly even worsening the overall fuel consumption in a whole gate-to-gate mission. However, trade-offs and concrete figures regarding the expected benefits are difficult to identify in the state of the art because assessing methods for the taxi phase are often too coarse and based on too generic data and assumptions such as Thrust Specific Fuel Consumption tables, constant thrust settings and estimated taxi times. This thesis contributes to the state of the art by presenting an integrated, model-based methodology for the assessment of aircraft systems at aircraft level in the conceptual design phase and its application to ETS. The proposed model-based process is shown to be necessary for answering key questions regarding the design of innovative aircraft subsystems in general, for performing solid comparisons and for determining suitable trade-offs while keeping the aircraft type and the specificities of the observed missions into account. A substantial methodological contribution in the framework of the proposed approach is given by the automatic generation of energetically optimal ground path following profiles for electric taxiing based on convex optimization. Because an optimal path following profile exists for each given system architecture and variant, a sound performance comparison of different system variants is only possible if each of them can be operated according to its own optimal profile. Convex optimization permits to find a global optimum for each given problem in short computational time thanks to dedicated solving toolboxes. Convex formulations of path following problems studied in robotics and vehicle dynamics were adapted to the aircraft taxi problem. Moreover, convex formulations of relevant constraints in this problem, such as time constraints on passing predefined waypoints, were determined. The result of the convex optimization is used as input in the simulation of the mission ground phases with the integrated aircraft model. The proposed system design methodology based on integrated simulation was instrumental for the following findings in connection with ETS. Firstly, a small system — which is lighter, but also less powerful — does not necessarily result in a further improvement of the benefits compared to larger, heavier systems because ground performance would be affected negatively. Secondly, the physical (e.g. thermal) behavior of the system during a given mission is a key factor as it has an immediate impact on the associated benefit. The optimal system architecture specifically depends on the aircraft and the missions flown; both must be taken into account in the early design phase. Thirdly, the prevailing interest for the ETS technology may be an economic one rather than an environmental one, as electric taxi may be economically viable even in case of increased mission block fuel. |
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URN: | urn:nbn:de:tuda-tuprints-62395 | ||||
Sachgruppe der Dewey Dezimalklassifikatin (DDC): | 600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften und Maschinenbau | ||||
Fachbereich(e)/-gebiet(e): | 16 Fachbereich Maschinenbau > Fachgebiet für Flugsysteme und Regelungstechnik (FSR) 16 Fachbereich Maschinenbau |
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Hinterlegungsdatum: | 02 Jul 2017 19:55 | ||||
Letzte Änderung: | 02 Jul 2017 19:55 | ||||
PPN: | |||||
Referenten: | Klingauf, Prof. Dr. Uwe ; Rinderknecht, Prof. Dr. Stephan | ||||
Datum der mündlichen Prüfung / Verteidigung / mdl. Prüfung: | 2 Mai 2017 | ||||
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