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Optimizing the electric multirotor aerial vehicle performance through inertia-preserved velocity and SOE estimation

Author

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  • Abdelkhalek, Mostafa
  • Bayezit, Ismail
  • Tatar, Ali

Abstract

This paper introduces advanced frameworks to enhance the performance of electric multirotors for Urban Air Mobility (UAM) applications. Key contributions include the battery State-of-Energy (SOE) estimation model, which is based on aerodynamics and momentum theory. Additionally, a discrete-time state-space framework integrates vehicle dynamics with SOE, refined using an Extended Kalman Filter (EKF). Furthermore, an algorithm and a Model Predictive Control (MPC) method are introduced to enhance energy efficiency during horizontal forward flight trajectory (Cruise Phase). These approaches utilize inertia-preserved velocity to produce Impulse Horizontal Thrusts (IHT) rather than Continuous Horizontal Thrusts (CHT). Simulation results indicate approximately 26% energy savings achieved with these strategies, highlighting their potential to boost the efficiency and feasibility of UAM substantially.

Suggested Citation

  • Abdelkhalek, Mostafa & Bayezit, Ismail & Tatar, Ali, 2025. "Optimizing the electric multirotor aerial vehicle performance through inertia-preserved velocity and SOE estimation," Applied Energy, Elsevier, vol. 401(PA).
    • Handle: RePEc:eee:appene:v:401:y:2025:i:pa:s0306261925012991
    DOI: 10.1016/j.apenergy.2025.126569
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    References listed on IDEAS

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    4. Straubinger, Anna & Rothfeld, Raoul & Shamiyeh, Michael & Büchter, Kai-Daniel & Kaiser, Jochen & Plötner, Kay Olaf, 2020. "An overview of current research and developments in urban air mobility – Setting the scene for UAM introduction," Journal of Air Transport Management, Elsevier, vol. 87(C).
    5. Myeong-hwan Hwang & Hyun-Rok Cha & Sung Yong Jung, 2018. "Practical Endurance Estimation for Minimizing Energy Consumption of Multirotor Unmanned Aerial Vehicles," Energies, MDPI, vol. 11(9), pages 1-11, August.
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