A Data-Driven Approach for Performance Evaluation of Autonomous eVTOLs

Mrinmoy Sarkar; Xuyang Yan; Biniam Gebru; Abdul-Rauf Nuhu; Kishor Datta Gupta; Kyriakos G. Vamvoudakis; Abdollah Homaifar

doi:10.36227/techrxiv.20327208

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A Data-Driven Approach for Performance Evaluation of Autonomous eVTOLs

Abdul-Rauf Nuhu·Mrinmoy Sarkar·Xuyang Yan·Biniam Gebru·Abdul-Rauf Nuhu·Kishor Datta Gupta·Kyriakos G. Vamvoudakis·Abdollah Homaifar

July 20, 2022DOI: 10.36227/techrxiv.20327208

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Abstract

<p>In this paper, we develop a data-driven performance-based evaluation framework for a novel electric vertical takeoff and landing aircraft (eVTOL) in the context of Urban Air Mobility (UAM) applications. First, a two-stage comprehensive simulation framework is developed to generate a benchmark database for the performance evaluation of both UAS Traffic Management (UTM) algorithms and high-fidelity eVTOL dynamical models. In the developed simulation framework, we implement UTM algorithms and incorporate real-world constraints, e.g., vertiport infrastructures and different wind conditions. From the developed simulation framework, we generate 1,213,010 flight profiles. These flight profiles are used in a model based eVTOL performance evaluation tool as inputs to compute the physical performance of 3 types of eVTOLs. Due to the high computational cost of model-based eVTOL performance evaluation approaches, a clustering-based sampling procedure is employed to reduce the redundancy in the generated flight profiles and utilize the re-sampled flight profiles to form an eVTOL performance analysis dataset. We then train and compare several machine learning models on the eVTOL performance analysis dataset to predict: performance variables-flight conditions, aerodynamic coefficients, aircraft electronics, electric motor and propeller efficiencies. Finally, we deploy the proposed data-driven models in the framework and reduce the eVTOL performance inference time to real-time. The implementation of the proposed framework can be found on GitHub: https://github.com/mrinmoysarkar/eVTOL_performance_evaluation.git</p>

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Sarkar, M., Yan, X., Gebru, B., Nuhu, A., Gupta, K., Vamvoudakis, K., & Homaifar, A. (2022). A Data-Driven Approach for Performance Evaluation of Autonomous eVTOLs. Unpublished manuscript. https://doi.org/10.36227/techrxiv.20327208

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A Data-Driven Approach for Performance Evaluation of Autonomous eVTOLs

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