An Overview of Drone Energy Consumption Factors and Models

Beigi, Pedram; Rajabi, Mohammad Sadra; Aghakhani, Sina

doi:10.1007/978-3-030-72322-4_200-1

Cited by 31 publications

(4 citation statements)

References 95 publications

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“…In general, in order to reduce logistics costs or protect the environment from pollution such as CO 2 emissions, there are two approaches in the literature: in the first approach, special transport vehicles that produce low pollution, such as drones, are used. The amount of CO 2 emitted by these vehicles and logistics costs could be optimized by planning and modeling logistics networks [20,21]. The second approach is to reduce logistics costs and environmental pollution by providing structures and methods for creating a distribution and collection logistics network.…”

Section: Literature Reviewmentioning

confidence: 99%

A Mathematical Optimization Model for the Pharmaceutical Waste Location‐Routing Problem Using Genetic Algorithm and Particle Swarm Optimization

Aghakhani,

Pourmand,

Zarreh

2023

Mathematical Problems in Engineering

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Pharmaceutical waste management is a significant concern that poses risks to human and environmental health. The ineffective management of expired and unused medications can harm individuals and communities. This study proposes a novel approach to address the issue of pharmaceutical waste management by developing a location-routing problem (LRP) model using mixed-integer linear programing (MILP) to optimize the collection and disposal of pharmaceutical waste. The proposed model aims to minimize transportation costs, construction of collection centers, disposal costs, and carbon dioxide emissions, making it a cost-effective and environmentally sustainable approach to managing pharmaceutical waste. Initially, the feasibility, validity, and efficiency of the proposed model are examined by solving the problem in the GAMS software using CPLEX solver for small-scale problems. Sensitivity analyses are conducted to ensure the accuracy, reliability, robustness, and usefulness of the mathematical model for decision-making. In view of the inherent computational complexity of the proposed model, which is classified as nondeterministic polynomial time-hard and poses considerable difficulties when exact solutions are sought for large-scale problems, the present study resorts to two metaheuristic algorithms, specifically particle swarm optimization (PSO) and genetic algorithm (GA), as a means minimizing the computational burden. The results indicate that GA outperforms PSO in terms of objective function and solution time, with an average improvement of approximately 1% and 20%, respectively. The proposed model and algorithms provide a comprehensive approach to addressing the critical issue of pharmaceutical waste management, benefiting the healthcare industry, and society as a whole.

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Section: Literature Reviewmentioning

confidence: 99%

A Mathematical Optimization Model for the Pharmaceutical Waste Location‐Routing Problem Using Genetic Algorithm and Particle Swarm Optimization

Aghakhani,

Pourmand,

Zarreh

2023

Mathematical Problems in Engineering

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“…[20][21][22] Fundamental to their efficient operation is the design of the wings, which provide both propulsion and control. Because the energy density of current power sources limits the power available for such miniaturized drones, [23] light, flexible wings are essential to reduce the power demands of a flapping system. [24,25] However, despite their indisputable importance, the wing designs of current, flight-capable, miniature-flapping drones are still relatively simple, ranging from basic rectangular shapes to insect-wing-shaped membranes fixed on a frame of radiating wing veins.…”

Section: Doi: 101002/adem202300861mentioning

confidence: 99%

Tailoring the Mechanical Properties of High‐Fidelity, Beetle‐Inspired, 3D‐Printed Wings Improves Their Aerodynamic Performance

Filc,

Gilon,

Gershon

et al. 2023

Adv Eng Mater

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Miniature flapping drones can potentially operate in small spaces, using lightweight membranous wings. Designing these flexible wings appropriately is crucial for effective flight performance. 3D‐printing allows not only to fabricate high‐fidelity, insect‐inspired wings, but also to further improve their design and shorten the development period for miniature flapping drones1. Here, a bioinspired approach was used to develop 3D‐printed wings based on the rose chafer beetle wings. By modulating the wing structure, we designed 12 different wing models that differ in the shape of the veins’ cross‐section, tapering geometry, and membrane thickness. The mechanical and aerodynamic properties of these models were compared, to establish guidelines linking wing form to function. We show that i) the geometry of the veins’ cross‐section offers a powerful tool for engineering in‐plane and out‐of‐plane deformations; ii) tapering veins improve the wings’ mechanical stability, and iii) the membrane merges the mechanics of the individual veins into an integrated aerodynamically favorable structure. These resulted in 16% higher lift and 27% improvement in lift production efficiency (N/Watts) in a revolving wing set‐up. Designing light, flexible, robust, and aerodynamically efficient wings presents a formidable engineering challenge ‐ that insects have solved. Reverse engineering these intricate structures is empirically described herein.This article is protected by copyright. All rights reserved.

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“…The first method involves constructing a model of the UAV's energy consumption and optimizing its relevant parameters to minimize energy consumption during flight. These models typically include various aspects such as flight speed, attitude control, sensors, and communication systems [20][21][22]. The second method involves reducing energy consumption and extending the mission time of the UAV through rational trajectory planning and movement strategies within the defined trajectory [23,24].…”

Section: Introductionmentioning

confidence: 99%

Multiobjective Energy Consumption Optimization of a Flying–Walking Power Transmission Line Inspection Robot during Flight Missions Using Improved NSGA-II

Wang,

Qin,

Jia

et al. 2024

Applied Sciences

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In order to improve the flight efficiency of a flying–walking power transmission line inspection robot (FPTLIR) during flight missions, an accurate energy consumption model is constructed, and a multiobjective optimization approach using the improved NSGA-II is proposed to address the high energy consumption and long execution time. The energy consumption model is derived from the FPTLIR kinematics to the motor dynamics, with the key parameters validated using a test platform. A multiobjective optimization model is proposed that considers many constraints related to the FPTLIR during missions, offering a comprehensive analysis of the energy consumption and execution time. The NSGA-II algorithm is improved by integrating the Cauchy variation operator and the simulated annealing algorithm, which is used to construct the multiobjective optimization approach. Simulation and experimental results demonstrate that the proposed model accurately predicts the energy consumption of the FPTLIR across different paths and flight conditions with an average relative error ranging from 0.76% to 3.24%. After optimization, energy savings of 5.33% and 5.01% are achieved for on-line and off-line missions, respectively, while maintaining the shortest execution time at the given energy level. The energy consumption optimization approach significantly improves the flight efficiency of the system, providing a reference for analyzing and optimizing energy consumption of inspection robots.

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An Overview of Drone Energy Consumption Factors and Models

Cited by 31 publications

References 95 publications

A Mathematical Optimization Model for the Pharmaceutical Waste Location‐Routing Problem Using Genetic Algorithm and Particle Swarm Optimization

A Mathematical Optimization Model for the Pharmaceutical Waste Location‐Routing Problem Using Genetic Algorithm and Particle Swarm Optimization

Tailoring the Mechanical Properties of High‐Fidelity, Beetle‐Inspired, 3D‐Printed Wings Improves Their Aerodynamic Performance

Multiobjective Energy Consumption Optimization of a Flying–Walking Power Transmission Line Inspection Robot during Flight Missions Using Improved NSGA-II

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