More Electric Aircraft (MEA) technologies aim at reducing greenhouse gas emissions to make local and global air transport easier [6], while at the same time being cost-effective, reliable and promoting the production of more energy-efficient vehicles. The primary goal of this research is, therefore, to establish a framework for determining whether MEA technology applied to a specific aircraft subsystem will be useful. Goal of this paper is the development of a tool that can assist in evaluating the Wing Ice Protection System (WIPS) fuel consumption of MEA airliners of any size and flight. A method is provided for calculating the mass of ice formed when an Airbus A320 aircraft is subjected to a series of in-flight icing conditions during Climb and Descent. These in-flight icing conditions consist of humidity due to precipitation, and the air temperatures lying between the freezing ranges of 273.15 K to 253.15 K. The case study used in this paper modifies the existing study by using an icing air temperature of 256 K and an icing duration of 130.5 seconds for the Climb Case and 151.5 seconds for the Descent Case. The study utilizes publicly available aircraft data and Appendix C, CS-25 EASA icing aviation standards [6]. Power and fuel consumption of conventional Wing Ice Protection System (p-WIPS) and electro thermal Wing Ice Protection System (e-WIPS) was computed. Results revealed a significant reduction in e-WIPS power usage, ranging from 13% to 50% depending on the p-WIPS configuration chosen.

This paper is about investigating the differences in fuel consumption of conventional and equivalent electricalsubsystems of passenger aircraft. The goal is to develop a framework that can help evaluate fuel consumptionof passenger aircraft, both conventional aircraft and More Electric Aircraft (MEA), for a given size of aircraftand a given stretch of flight.The work presented in this paper originates from pre-studies within MEA research performed by the ReliabilityCentered Asset Management (RCAM) research group at KTH in collaboration with SAAB that has been doneon a passenger aircraft with comparable size to the Airbus A320. The main difference to the prior study isthe addition of subsystem weight, passenger scaling effects, environmental dependencies and flight profile, alladded to increase the accuracy and diversity of the model. The fuel consumption is based on studies of existingtechnology for several passenger aircraft from Airbus and Boeing. The main focus was the EnvironmentalControl System (ECS).A numerical model of passenger aircraft including the ECS was constructed in MATLAB with different levelsof electrification, a conventional ECS or a fully electric ECS. A special case with an Airbus A320 with 180passengers doing a round trip between Copenhagen and Stockholm on a hot day was studied.The results show possible fuel savings in the magnitude of 4% to 8% when electrifying the ECS for the casestudied and for aircraft with 156 to 700 passengers.

This paper is about investigating the differences in fuel consumption of conventional and equivalent electrical subsystems of passenger aircraft. The goal is to develop a framework that can help evaluate fuel consumption of passenger aircraft, both conventional aircraft and More Electric Aircraft (MEA), for a given size of aircraft and a given stretch of flight. The work presented in this paper originates from pre-studies within MEA research performed by the Reliability Centered Asset Management (RCAM) research group at KTH in collaboration with SAAB that has been done on a passenger aircraft with comparable size to the Airbus A320. The main difference to the prior study is the addition of subsystem weight, passenger scaling effects, environmental dependencies and flight profile, all added to increase the accuracy and diversity of the model. The fuel consumption is based on studies of existing technology for several passenger aircraft from Airbus and Boeing. The main focus was the Environmental Control System (ECS). A numerical model of passenger aircraft including the ECS was constructed in MATLAB with different levels of electrification, a conventional ECS or a fully electric ECS. A special case with an Airbus A320 with 180 passengers doing a round trip between Copenhagen and Stockholm on a hot day was studied. The results show possible fuel savings in the magnitude of 4% to 8% when electrifying the ECS for the case studied and for aircraft with 156 to 700 passengers.

As the global population and economy grow, the amount of people traveling around the world also increases.This creates a need for the aerospace industry to develop more energy efficient vehicles. The concept ofelectrification of vehicles has been adopted by the aviation industry in order to reduce environmental impactsand lower operating costs. Although much research has been done on various more electric aircrafttechnologies, almost all of them are conducted only for one subsystem, lacking the aim of optimizing the totalenergy outtake from the engines by all subsystems. This paper aims to fill this gap by applying optimizationtechniques to decide systematically when novel technologies are worthwhile, in terms of energy efficiency.Hence, the goal of this paper is to develop a methodology for evaluating when different MEA technologies arebeneficial to implement in future airplanes. In this proposed approach, a Matlab model has been developedwhich takes publicly available non-propulsive power demands and efficiencies of various subsystems intoaccount, integrates those with real flight data from a case study, and as a result gives the user a comparisonof non-propulsive fuel burn. The result is a fuel burn of 1088.5 kg for conventional, 756.5 kg for more-electric,and 351.5 kg for all-electric architectures, depending on the level of electrification. The difference in total fuelburn between the conventional and all electric cases, including fuel consumption for propulsion, represents areduction of total fuel burn on the order of 10 percent. Since as many electrical loads as possible are integratedinto the proposed approach, this model can also be used for generator sizing as discussed in the results sectionof the case study.