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Path Planning of Electric VTOL UAV Considering Minimum Energy Consumption in Urban Areas

Author

Listed:
  • Yafei Li

    (School of Air Traffic Management, Civil Aviation University of China, Tianjin 300300, China)

  • Minghuan Liu

    (School of Air Traffic Management, Civil Aviation University of China, Tianjin 300300, China)

Abstract

As a new mode of transportation in the future, electric vertical take-off and landing unmanned aerial vehicles (eVTOL UAV) can undertake the task of logistics distribution and carry people in urban areas. It is challenging to carry out research designed to plan the path of eVTOL UAVs which can have a safe and sustainable operation mode in urban areas. Therefore, this work proposes a method for planning an obstacle-free path for eVTOL UAVs in urban areas with the goal of minimizing energy consumption. It aims to improve the safety and sustainability of eVTOL UAV operations. Based on variations of air density with height, a more accurate formula for calculating battery energy consumption of eVTOL UAV is derived. It is used in the vertical takeoff and landing phase and horizontal flight phase, respectively. Considering the influence of buildings on eVTOL UAV operation, a path planning method applicable to complex urban environments is proposed. The safe nodes of eVTOL UAV flight are obtained by using Voronoi diagrams based on building locations. Then, the complete shortest and obstacle-free path is obtained by using a Dubins geometric path and Floyd algorithm. After obtaining the obstacle-free paths for all flight height zones, the battery energy consumption of the eVTOL UAV in each flight height zone is calculated. Then, the flight height with the minimum energy consumption is obtained. The simulation results show that the path length obtained by the proposed path planning method is shorter than that obtained by particle swarm optimization; the total battery energy consumption changes in the same pattern in the low-altitude areas and high-altitude areas; the difference between the maximum and minimum energy consumption in the small area enables the eVTOL UAV to cover about 350 m more, and about 420 m more in the large area. Therefore, in future high-frequency UAV mission flights, choosing the altitude with the lowest energy consumption can reduce UAV operator costs. It can also significantly increase UAV transport range and make UAVs operate more sustainably.

Suggested Citation

  • Yafei Li & Minghuan Liu, 2022. "Path Planning of Electric VTOL UAV Considering Minimum Energy Consumption in Urban Areas," Sustainability, MDPI, vol. 14(20), pages 1-23, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:20:p:13421-:d:945799
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    References listed on IDEAS

    as
    1. Peng Han & Xinyue Yang & Yifei Zhao & Xiangmin Guan & Shengjie Wang, 2022. "Quantitative Ground Risk Assessment for Urban Logistical Unmanned Aerial Vehicle (UAV) Based on Bayesian Network," Sustainability, MDPI, vol. 14(9), pages 1-13, May.
    2. repec:cdl:itsrrp:qt8nh0s83q is not listed on IDEAS
    3. Cheng, Chun & Adulyasak, Yossiri & Rousseau, Louis-Martin, 2020. "Drone routing with energy function: Formulation and exact algorithm," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 364-387.
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    Cited by:

    1. Zhang, Honggang & Liu, Zhiyuan & Dong, Yu & Zhou, Hongyue & Liu, Pan & Chen, Jun, 2024. "A novel network equilibrium model integrating urban aerial mobility," Transportation Research Part A: Policy and Practice, Elsevier, vol. 187(C).
    2. Honghai Zhang & Tian Tian & Ouge Feng & Shixin Wu & Gang Zhong, 2023. "Research on Public Air Route Network Planning of Urban Low-Altitude Logistics Unmanned Aerial Vehicles," Sustainability, MDPI, vol. 15(15), pages 1-17, August.
    3. Yiwei Na & Yulong Li & Danqiang Chen & Yongming Yao & Tianyu Li & Huiying Liu & Kuankuan Wang, 2023. "Optimal Energy Consumption Path Planning for Unmanned Aerial Vehicles Based on Improved Particle Swarm Optimization," Sustainability, MDPI, vol. 15(16), pages 1-16, August.

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