A proposed framework for minimum energy consumption in electric VTOL aircrafts

• Ano de defesa: 2020
• Autor(a) principal: Brito, Willian Caruso de
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
• Palavras-chave em Português: Aeronaves elétricas; Air taxi travel; Algoritmo Genético; Aprendizado de máquina; Baterias; Batteries; Consumo de energia; Desempenho de pouso; Electric aircraft; Empuxo rotativo; Energy consumption; eVTOL; Genetic algorithm; Landing performance; Machine learning; Melhoria de desempenho; Optimization; Otimização; Performance improvement; Táxi aéreo; Tiltrotor
• Link de acesso: https://www.teses.usp.br/teses/disponiveis/18/18161/tde-04022021-080802/

In order to improve commute time for small distance trips and relieve large cities traffic, a new transport category has been the subject of research and new designs worldwide. The air taxi travel market promises to change the way people live and commute by using the concept of vehicles with the ability to take-off and land vertically and to provide passenger\'s transport equivalent to a car, with mobility within large cities and between cities. Today\'s civil air transport remains costly and accounts for 2% of the man-made CO2 emissions. Taking advantage of this scenario, many companies have developed their own Vertical Take Off and Landing (VTOL) design, seeking to meet comfort, safety, low cost and flight time requirements in a sustainable way. Thus, the use of green power supplies, especially batteries, and fully electric power plants is the most common choice for these arising aircrafts. However, it is still a challenge finding a feasible way to handle with the use of batteries rather than conventional petroleum-based fuels. The batteries are heavy and have an energy density still below from those of gasoline, diesel or kerosene. Therefore, despite all the clear advantages, All Electric Aircrafts (AEA) still have low flight autonomy and high operational cost, since the batteries must be recharged or replaced. In this sense, this dissertation addresses a way to optimize the energy consumption in a typical mission of an aerial taxi aircraft. The approach and landing procedure was chosen to be the subject of an optimization algorithm, while final programming can be adapted for take-off and flight level changes as well. A generic VTOL tiltrotor aircraft with full electric power plant model was used to fit the derived dynamic equations of motion. Although a tiltrotor design is used as a proof of concept, it is possible to adapt the optimization to be applied for other design concepts, even those with independent motors for hover and cruise flight phases. For a given trajectory, the best set of control variables are calculated to provide time history response for aircraft\'s rotors RPM, thrust direction and elevators deflexion that, if followed, results in the minimum electric power consumption through that landing path. Methodology includes modeling an electric tiltrotor design, solving the aircraft dynamics through the trajectory using a trim routine, elaborating learning methods for classification to address safety, comfort and design constraints and creating a genetic algorithm for optimization. For the tested cases, performance improvement ranged from 10 to 20% compared with mean energy of possible solutions. Results are highly dependent on the constraints.