Design of Electrical Power Architectures for All-Electric Aircraft with Emphasis on Cabling and Battery Systems
Tiantian Xu (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Jawad Ahmad (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Yawen Liang (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Gautham Ram Chandra Mouli (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Mohamad Ghaffarian Niasar (TU Delft - Electrical Engineering, Mathematics and Computer Science)
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Abstract
Electric aircraft represent a promising low-emission alternative to conventional fuel-powered aviation, driving the demand for lightweight and reliable electrical powertrain architectures. This study presents a design process for an electrical power system with an emphasis on the cabling system and battery in all-electric aircraft (AEA). Design considerations for the cabling system in power distribution architectures are discussed, including cable insulation material selection, conductor choice, sizing, and weight reduction methods. The influence of different system voltages and operating temperatures on cable weight is analyzed to identify optimal design tradeoffs. A comparison of polytetrafluoroethylene (PTFE) and perfluoroalkoxy (PFA) insulation materials, as well as aluminum and copper conductors, highlights their impact on weight and reliability, with PFA offering weight advantages under typical aerospace operating conditions. The batteries are sized based on the energy and power demands of a 90-seater AEA as a case study. After designing the components of the aircraft’s electrical power system, the electrical architectures are presented. Furthermore, a framework for evaluating the electrical power system architectures of AEAs is proposed, using two key criteria: reliability and weight. The weight of the electrical power system is then estimated based on aircraft performance requirements. The proposed framework provides practical guidelines for cable selection and architecture optimization in future AEAs.
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