Data Driven UAM Flight Energy Consumption Prediction and Risk Assessment

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Data Driven UAM Flight Energy Consumption Prediction and Risk Assessment

Data Driven UAM Flight Energy Consumption Prediction and Risk Assessment

Y. Ayalew / W. Bedada / A. Homaifar / K. Freeman

With the current technological advancements revolutionizing the concept of Urban Air Mobility (UAM) and package delivery, there is also, a concurrent need to quantify the operational safety of these vehicles in terms of their associated risk. Conducting safe flight operations is critical for UAM vehicles which are electrically Vertical Takeoff and Landing (eVTOL) vehicles, to operate in current Air traffic control. In this paper, a data-driven method for UAM vehicle energy consumption prediction and risk quantification with conditional value-at-risk based on energy consumption distribution is presented. Significant factors affecting energy consumption, such as density altitude, aircraft design, airspeed, and collision avoidance algorithms, are considered in the data-driven based energy consumption prediction of different eVTOL

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Title :

Data Driven UAM Flight Energy Consumption Prediction and Risk Assessment

Contributors:

Y. Ayalew (author) / W. Bedada (author) / A. Homaifar (author) / K. Freeman (author)

Publication date :

2022

Size :

13 pages

Type of media :

Report

Type of material :

No indication

Language :

English

Keywords :

Aeronautics , Data-driven , Density altitude , Energy consumption , Evtol , Flight risk assessment , Prediction , Risk , Uam

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