Range, Endurance, and Optimal Speed Estimates for Multicopters

Abstract

Multicopters are among the most versatile mobile robots. Their applications range from inspection and mapping tasks to providing vital reconnaissance in disaster zones and to package delivery. The range, endurance, and speed a multirotor vehicle can achieve while performing its task is a decisive factor not only for vehicle design and mission planning, but also for policy makers deciding on the rules and regulations for aerial robots. To the best of the authors' knowledge, this work proposes the first approach to estimate the range, endurance, and optimal flight speed for a wide variety of multicopters. This advance is made possible by combining a state-of-the-art first-principles aerodynamic multicopter model based on blade-element-momentum theory with an electric-motor model and a graybox battery model. This model predicts the cell voltage with only 1.3% relative error ( 43.1mV ), even if the battery is subjected to non-constant discharge rates. Our approach is validated with real-world experiments on a test bench as well as with flights at speeds up to 65km/h in one of the world's largest motion-capture systems. We also present an accurate pen-and-paper algorithm to estimate the range, endurance and optimal speed of multicopters to help future researchers build drones with maximal range and endurance, ensuring that future multirotor vehicles are even more versatile.

Autonomous Drone Racing: A Survey

“…For example, in search-andrescue scenarios, drones must be able to rapidly navigate in complex environments in order to maximize their spatial coverage. Put more simply, drones that can fly fast, fly farther [4].…”

“…On most multicopters, the motors are not equipped with closed-loop motor speed control but controlled by a 'throttle' command which controls the duty cycle of a PWM (pulse-width-modulation) signal applied to the motors. The actual rotational speed that the motor achieves is a function of the throttle command as well as other parameters such as the battery voltage and the drag torque of the rotor [4]. Therefore, in order to have a dynamics model for the motors we need a model of the battery to calculate the voltage applied to the motors.…”

“…50-100 C) [41], [42]. Graybox battery models for the voltage that are based on a one-time-constant (OTC) equivalent circuit [43], [44] are much more suitable for drone racing tasks as shown in [4], because they are applicable to the extremely high loads experienced during a racing scenario. In combination with either a polynomial or a constant-efficiency motor model such OTC models can be used to accurately simulate the battery voltage during agile flight [4].…”

“…Graybox battery models for the voltage that are based on a one-time-constant (OTC) equivalent circuit [43], [44] are much more suitable for drone racing tasks as shown in [4], because they are applicable to the extremely high loads experienced during a racing scenario. In combination with either a polynomial or a constant-efficiency motor model such OTC models can be used to accurately simulate the battery voltage during agile flight [4]. Given a simulation of the battery voltage, one can measure the performance characteristics of a given motor-propeller combination to determine the mapping of throttle command and voltage to resulting steady-state propeller speed Ω ss .…”

Crash 2 Squash: An Autonomous Drone for the Traversal of Narrow Passageways

“…Furthermore, the traversal speed is reduced to trade off more stability at the expense of larger energy consumption and therefore length of the mission. [ 21 ] These are the main reasons why a gap‐to‐drone ratio of is the current limit for morphing drones (Figure 1D).…”