Electrically Assisted Propulsion & Power Systems for Short-Range Missions

Electrically Assisted Propulsion & Power Systems for Short-Range Missions: Electrification of a Conventional Airbus A320neo

Tan, Sheng Chien (TU Delft Aerospace Engineering; TU Delft Flight Performance and Propulsion)

Gangoli Rao, A. (mentor)
Lammen, Wim (graduation committee)
Dong, J. (graduation committee)
Vos, Roelof (graduation committee)

Delft University of Technology

Aerospace Engineering

2018-04-12

Over the last 50 years, the global airline industry has seen resilient growth in the demand for passenger travel; this trend is expected to continue in the coming decades. With kerosene being the predominant source used as jet fuel, this increase in air traffic is expected to result in the depletion of non-renewable fossil fuels and undesired climate changes on a global scale. Therefore, the industry is currently exploring the electrification of aircraft, taking into account advanced concepts such as more electric aircraft (MEA) and hybrid electric propulsion systems (HEPS). This thesis addresses a combination of these two concepts characterised as an electrically assisted propulsion & power system (EAPPS). This system integrates a conventional turbofan engine with a network of electrical components, providing assistance to the aircraft propulsion and non-propulsive power systems. This secondary electrical system can be activated throughout the flight mission to assist the turbofan engine and increase the overall system efficiency. The amount of electrical power relative to the total power is defined as the power split ratio.
The objective of this study is to evaluate how gradual modifications in this EAPPS affect the overall performance of an Airbus A320neo (new engine option) aircraft in a short-range mission of 1,000 km. The proposed changes include the conversion to an electrical architecture of the non-propulsive power systems, the implementation of a fuel cell system, the installation of photovoltaic panels on the outer skin of the aircraft and the downscaling of the turbofan engine. To analyse these effects accordingly, two separate simulation models were developed within the MATLAB environment to perform and verify a series of trade studies at two different time frames: near future (2020+) and far future (2040+).
The results revealed that each modification has proven to be advantageous in terms of overall fuel and energy consumption; however, turning the A320neo into a MEA is the most effective approach. The inclusion of fuel cell and photovoltaic systems brings minor benefits, but also increases the complexity of the system. Nonetheless, the derived optimal setups for the 2020+ and 2040+ scenarios feature all modifications, but with a different power management strategy and engine scaling.
The optimal power management strategy for 2020+ includes fully electric taxiing, a take-off power split of 17%, a climb power split of 9% and a downscaled engine of 90%. Compared to the conventional A320neo, this setup will lower the fuel and energy consumption by 17% and 13%, correspondingly. Also, the CO₂ emissions are reduced by 16%. By 2040+, the optimal take-off power split increases to 26% and the climb power split to 43%. This allows the CFM LEAP-1A engine to be scaled down to 85%. The total relative savings of fuel, energy and CO₂ emissions equal 28%, 18% and 27%, respectively. The impact of the projected technological development in a time period of 20 years, from 2020+ to 2040+, is witnessed through the increased use of electrically assisted propulsion and significant greater amounts saved with respect to fuel, energy and engine emissions.

aircraft flight performance
battery system optimisation
commercial aviation
EAPPS
electrically assisted propulsion and power systems
electric propulsion
environmental impact assessment
fuel cells
gas turbines
HEPS
hybrid electric propulsion
non-propulsive power systems
photovoltaics
power management strategy
sustainability
system modelling

http://resolver.tudelft.nl/uuid:12ff33e4-78ce-43f0-893f-43e0b15b8e1e

2018-04-12

Student theses

master thesis

© 2018 Sheng Chien Tan