A Multi-Criteria Solution Approach for UAV Engine Selection in Terms of Technical Specification

Yıl 2022, , 1000 - 1013, 31.12.2022

Ukbe Usame Uçar , Aylin Adem , Burak Tanyeri

https://doi.org/10.17798/bitlisfen.1150200

Cited By: 2

Öz

Unmanned Aerial Vehicles are electronic systems that are used extensively in every field today and that develop and change very quickly with technology. UAVs are used extensively in many areas, especially in logistics processes, search and rescue activities, military operations, fight to forest fires, photography, monitoring and inspection of agricultural processes. Furthermore, considering their hobby use, it is understood that UAVs have a large commercial market and a high economic value. UAV systems contain many electronic and mechanical systems and many performance criteria can be found for UAV systems. The main ones of these performances are stabilization and engine power. The most important system affecting these performance criteria is the engine. In this study, engine alternatives available in the market for UAVs with take-off weights of 750 to 800 grams were evaluated in terms of mechanical and physical criteria of engine systems, and as a result, the ideal engine model was determined by Analytical Hierarchy method for maximum stabilization and velocity purposes. The article is the first in the literature in terms of the problem obtained and the application of the AHP method to this problem. Thanks to the study, it is aimed to create a Decision Support System for both UAV manufacturers and UAV users so that they can choose the ideal models in engine selection processes.

Anahtar Kelimeler

Unmanned Aerial Vehicle, Engine, AHP, Decision Support System, Multi-Criteria Decision Making.

Kaynakça

• [1]. Uçar U. Ü., and İşleyen S. K., “A new solution approach for UAV routing problem with moving target – heterogeneous fleet”, Journal of Polytechnıc, 22(4): 999-1016, (2019).
• [2]. Uçakcıoğlu, B., and Eren, T. (2017). Investment Selection Project in Air Defense Industry with Analytic Hierarchy Process and VIKOR Methods. Harran University Journal of Engineering, 2(2), 35-53.
• [3]. Ulukavak, M., and Miman, M. (2019). Selection of The Most Proper Unmanned Aerial Vehicle for Transportation in Emergency Operations by Using Analytic Hierarchy Process. International Journal of Environment and Geoinformatics, 8(1), 78-91.
• [4]. Özaslan, İ. H. , Kocaoğlu, B. and Odabaşoğlu, Ş. (2021). Türkiye’de Pistonlu Tek Motorlu Uçak Seçiminde Çok Kriterli Karar Verme Ahp ve Topsis Yöntemlerinin Kullanılması . Journal of Aviation Research , 3 (2) , 243-263 . DOI: 10.51785/jar.955683
• [5]. Zhao, Y., Lou, W., Wang, J., Liu, W., and Su, Z. (2019, October). Evaluation of the unmanned aerial vehicle (UAV) recovery system based on the analytic hierarchy process and grey relational analysis. In 2019 IEEE International Conference on Unmanned Systems (ICUS) (pp. 285-290). IEEE.
• [6]. Tuba, Z., Vidnyánszky, Z., Bottyán, Z., Wantuch, F., and Hadobács, K. (2013). Application of Analytic Hierarchy Process in fuzzy logic–based meteorological support system of unmanned aerial vehicles1. AARMS, AARMS, 12(2), 221–228.
• [7]. Yan, Y., Pei, W., Sun., W, And Ye, J. (2019, October). Research on Maintenance Quality Evaluation Method for Unmanned Aerial Vehicle. In 2019 IEEE 3rd Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC) (pp. 237-240). IEEE.
• [8]. Yıldızbaşı, A., and Gür, L. (2020). A decision support model for unmanned aerial vehicles assisted disaster response using AHP-TOPSIS method. European Journal of Science and Technology, (20), 56-66.
• [9]. Wang, J. R., Tsai, Y. L., Wu, L. N., and Lin, Y. C. (2013, December). The power system design of small unmanned aerial vehicle. In Proceedings of the 2013 IEEE/SICE International Symposium on System Integration (pp. 838-843). IEEE.
• [10]. HE, M. L., Jilin, H., and Xiaole, A. (2016). Genetic Algorithm Based on Analytic Hierarchy Process PID Parameter Tuning of UAV Control System. 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics (AMEII 2016).
• [11]. Lai, C. K., and Whidborne, J. F. (2012, October). Automated return-to-route maneuvers for unmanned aircraft systems. In 2012 IEEE/AIAA 31st Digital Avionics Systems Conference (DASC) (pp. 8C4-1). IEEE.
• [12]. Canetta, L., Mattei, G., and Guanziroli, A. (2017, June). Multi criteria analysis applied on value chain definition in unmanned aerial vehicle (UAV) sector. In 2017 International Conference on Engineering, Technology and Innovation (ICE/ITMC) (pp. 1096-1103). IEEE.
• [13]. Gur, O., and Rosen, A. (2009). Optimization of propeller based propulsion system. Journal of Aircraft, 46(1), 95-106.
• [14]. Gaggero, S., Tani, G., Villa, D., Viviani, M., Ausonio, P., Travi, P., and Serra, F. (2017). Efficient and multi-objective cavitating propeller optimization: an application to a high-speed craft. Applied Ocean Research, 64, 31-57.
• [15]. Dundar Ö., Bilici M. and Ünler T. (2020). Design and performance analyses of a fixed wing battery VTOL UAV. Engineering Science and Technology, an International Journal, 23, 1182–1193.
• [16]. Bayraktar, Ö., and Güldaş, A. (2020). Optimization of Quadrotor’s Thrust and Torque Coefficients and Simulation with Matlab/Simulink. Journal of Polytechnic, 23(4), 1197-1204.
• [17]. Foeth, E. J., and Lafeber, F. (2015). Systematic propeller optimization using an unsteady Boundary Element Method. In Fourth International Symposium on Marine Propulsors (SMP15); Austin, TX, USA.
• [18]. Lee Y., Park E-T., Jeong J., Shi H., Kim J., Kang B-S. and Song W. (2020). Weight optimization of hydrogen storage vessels for quadcopter UAV using genetic algorithm. International Journal of Hydrogen Energy, 45, 33939-33947.
• [19]. Bacciaglia, A., Ceruti, A., and Liverani, A. (2020). Controllable pitch propeller optimization through meta-heuristic algorithm. Engineering with Computers, 1-15.
• [20]. Zhang H., Song B., Li F. and Xuan J. (2021). Multidisciplinary design optimization of an electric propulsion system of a hybrid UAV considering wind disturbance rejection capability in the quadrotor mode. Aerospace Science and Technology, 110, 106372.
• [21]. Podsędkowski, M., Konopiński, R., Obidowski, D., and Koter, K. (2020). Variable Pitch Propeller for UAV-Experimental Tests. Energies, 13(20), 5264.,
• [22]. ElGhazali, A. F., and Dol, S. S. (2020). Aerodynamic Optimization of Unmanned Aerial Vehicle through Propeller Improvements. Journal of Applied Fluid Mechanics, 13(3), 793-803.
• [23]. Sinibaldi, G., and Marino, L. (2013). Experimental analysis on the noise of propellers for small UAV. Applied Acoustics, 74(1), 79-88.
• [24]. Kuantama, E., and Tarca, R. (2017). Quadcopter thrust optimization with ducted-propeller. In MATEC Web of Conferences (Vol. 126, p. 01002). EDP Sciences.
• [25]. Larocca, F., D’ambrosıo, D., Raıola, L., Tutor, A., and Zambonı, E. F. (2019). Topological optimization of a drone propeller using commercial CFD code. Master’s Thesis in Aerospace Engineering Thesis. Polıtecnıco Dı Torıno.
• [26]. Kapsalis S., Panagiotou P. and Yakinthos K. (2021). CFD-aided optimization of a tactical Blended-Wing-Body UAV platform using the Taguchi method. Aerospace Science and Technology, 108, 106395.
• [27]. Dahal, C., Dura, H. B., and Poudel, L. (2021). Design and Analysis of Propeller for High Altitude Search and Rescue Unmanned Aerial Vehicle. International Journal of Aerospace Engineering, 2021, 1-13
• [28]. ElGhazali, A. F., and Dol, S. S. (2020). Aerodynamic Optimization of Unmanned Aerial Vehicle through Propeller Improvements. Journal of Applied Fluid Mechanics, 13(3), 793-803.
• [29]. Andria, G., Di Nisio, A., Lanzolla, A. M. L., Spadevecchia, M., Pascazio, G., Antonacci, F., and Sorrentino, G. M. (2018, June). Design and performance evaluation of drone propellers. In 2018 5th IEEE International Workshop on Metrology for AeroSpace (MetroAeroSpace) (pp. 407-412). IEEE.
• [30]. Iannace, G., Ciaburro, G., and Trematerra, A. (2019). Fault diagnosis for UAV blades using artificial neural network. Robotics, 8(3), 59.
• [31]. Dumıtrache, A., Prıcop, M. V., Nıculescu, M. L., Cojocaru, M. G., and Ionescu, T. (2017). Desıgn And Analysıs Methods For Uav Rotor Blades. Scientific Research & Education İn The Air Force-Afases, 1.
• [32]. Rakhade, R. D., Patil, N. V., Pardeshi, M. R., and Mhasde, C. S. Optimal Choice of Agricultural Drone using MADM Methods. International Journal of Technological Innovation in Modern Engineering and Science (IJTIMES), e-ISSN, 2455-2585.
• [33]. Sah, B., Gupta, R., & Bani-Hani, D. (2021). Analysis of Barriers to Implement Drone Logistics. International Journal of Logistics Research and Applications, 24(6), 531-550.
• [34]. Zhang, J. Z., Srivastava, P. R., & Eachempati, P. (2021). Evaluating The Effectiveness of Drones in Emergency Situations: A Hybrid Multi-Criteria Approach. Industrial Management & Data Systems.
• [35]. Zhou, C., Yin, J., Rong, A., Guo, D., and Li, J. (2021, June). Research on UAV Fire Fight based on Analytic Hierarchy Process. In Proceedings of the 2021 International Conference on Control and Intelligent Robotics (pp. 16-22).
• [36]. Zoltan, T., Vidnyánszky, Z., Bottyán, Z., Wantuch, F., and Hadobács, K. (2013). Application of analytic hierarchy process in fuzzy logic-based meteorological support system of unmanned aerial vehicles.
• [37]. Ardil, C. (2021). A Comparative Analysis of Multiple Criteria Decision Making Analysis Methods for Strategic, Tactical, and Operational Decisions in Military Fighter Aircraft Selection. International Journal of Aerospace and Mechanical Engineering, 14(7), 275-288.
• [38]. Adem, A., Yilmaz Kaya, B., and Dağdeviren, M. (2022). Technology Analysis for Logistics 4.0 Applications: Criteria Affecting UAV Performances. In Intelligent and Fuzzy Techniques in Aviation 4.0 (pp. 497-520). Springer, Cham.
• [39]. Moaddab, H., Ebrahimi, M., and Ahangar, M. N. (February - 2020). Civil Unmanned Aerial Vehicle Assessment for Short Range Monitoring Gas Pipeline Using AHP Methodology. 18th Int. Conference of Iranian Aerospace Society Amirkabir University of Technology.
• [40]. Hsiao, S., and Peng, P. (2020) Using FCE and FAHP to Explore the multirotor drone appearance preference, in Boess, S., Cheung, M. and Cain, R. (eds.), Synergy - DRS International Conference 2020, 11-14 August.
• [41]. Khan, M. S., Shah, S. I. A., Javed, A., Qadri, N. M., and Hussain, N. (2021, January). Drone selection using multi-criteria decision-making methods. In 2021 International Bhurban Conference on Applied Sciences and Technologies (IBCAST) (pp. 256-270). IEEE.
• [42]. Wang, J. R., Tsai, Y. L., Wu, L. N., and Lin, Y. C. (2013, December). The power system design of small unmanned aerial vehicle. In Proceedings of the 2013 IEEE/SICE International Symposium on System Integration (pp. 838-843). IEEE.
• [43]. https://bilgeis.net/docs/40_B2_1.pdf Accesed: 21.09.2021
• [44]. Saaty, T. L., “How to make a decision: the analytic hierarchy process”, Euro. J. Oper. Res., 48: 9-26, (1970) [45]. Şenol M, Adem A, Dağdeviren M, (2019). A Fuzzy MCDM Approach to Determine the Most Influential Logistic Factors, Journal of Polytechnic, 22(3), 793 – 800.
• [46]. Dağdeviren M, Yavuz S, Kılınç N. (2009). Weapon selection using the AHP and TOPSIS methods under fuzzy environment. Expert Systems with Applications, 36, 8143-8151.
• [47]. Saaty, T. L., The Analytic Hierarchy Process, Mcgraw-Hill, New York (1980).
• [48]. Dağdeviren, M., “Decision making in equipment selection: an integrated approach with AHP and PROMETHEE”, J. Intel. Manuf., 19: 397-406, (2008)
• [49]. Dağdeviren, M, Eren, T., "Analytic hierarchy process and use of 0-1 goal programming methods in selecting supplier firm", J. Fac. Eng. Archit., Gazi Univ. Cilt 16, 41-52, (2001)