Abstract
An optimization study of an electric vertical takeoff and landing personal air vehicle (eVTOL PAV) was performed during the conceptual design stage using the design of experiments method. In defining the initial problem, a design target parameter was set. The PAV subsystem was based on a configuration tradeoff study matrix, which was used to effectively conduct configuration selection. Initial sizing was performed using the PAV sizing program developed by this research team using Microsoft Excel and Visual Basic for Application (VBA). A screening test was performed to find parameters with high sensitivity among independent design parameters. The response surface method was used to model design target parameters, and a regression equation was estimated using the experimental design method. A Monte Carlo simulation was performed to confirm the feasibility of the generated model. To optimize the design independent parameter, a satisfaction function was selected, and the appropriateness of the data was determined using a Pareto plot and p-value.
Highlights
In 2015, individuals in San Francisco spent 230 h commuting, resulting in 500,000 h of lost productivity each day
Because the current two-dimensional traffic system cannot effectively solve traffic jams, considerable attention is being paid to a three-dimensional traffic system, based on the use of electric vertical takeoff and landing personal air vehicles (PAV)
This study conducted an optimization analysis of the design parameters and conceptual design of an electric vertical takeoff and landing (eVTOL) PAV, a new concept aircraft to be used for urban air mobility (UAM)
Summary
In 2015, individuals in San Francisco spent 230 h commuting, resulting in 500,000 h of lost productivity each day. The multicopter type has excellent vertical takeoff and landing performance and is suitable for short-distance transportation in an urban area. Kadhiresan and Duffy gave special attention to the tradeoff between configuration classes with regard to efficiency and suitability for different missions [8] They used build-up component-based weight models to size several types of configurations for varying combinations of cruise range and cruise speed, which are two of the most important variables for defining the utility of an aircraft as an on-demand mobility (ODM)/urban air mobility (UAM) vehicle. With this information, they determined the set of mission profiles for which each configuration dominates performance and efficiency.
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