• Title/Summary/Keyword: KC-100 무인화

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The Analysis of Mission Profile of the KC-100 UAV (KC-100 무인화 비행체 임무 형상 분석)

  • Lee, Jung-hoon
    • Journal of Aerospace System Engineering
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    • v.14 no.5
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    • pp.49-57
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    • 2020
  • The KC-100 has completed civil type certification with the Ministry of Land, Infrastructure, and Transport, and is currently under development as an unmanned aerial vehicle as part of the Ministry of Land, Infrastructure, and Transport. The Certification Technology of small Unmanned Airplane system (CTsUA system), which is an unmanned KC-100, is being developed to enable the installation of heavy-duty mission equipment and long-time flight missions. This study investigated the process and results of analyzing various parameters such as aircraft weight, airspeed, flight altitude, required horsepower, and fuel consumption at each stage to construct a mission profile based on the operational concept of the CTsUA system. To maintain a maximum take-off weight of 3,600 lbs (1,633 kg), the analysis determined that the weight of the application equipment for the unmanned system should be kept below 80 lbs (36 kg).

Development and Validation of Dynamic Model for KC-100 UAS (KC-100 항공기 무인화를 위한 운동모델 구축 및 검증)

  • Seong Hyeon Kim;Ji Bon Kim;Jung Hoon Lee;Eung Tai Kim;Byoung Soo Kim
    • Journal of Aerospace System Engineering
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    • v.17 no.1
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    • pp.79-87
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    • 2023
  • To design a control law of an aircraft, an accurate aircraft dynamic model is required. To obtain an aerodynamic database (DB) to build a dynamic model, a large number of wind tunnel tests are typically required. However, when flight test data of target aircraft exist such as in the process of unmanned conversion of a manned aircraft, an aircraft dynamic model can be obtained through a parameter estimation method and a DB tuning procedure. This paper describes a nonlinear model construction process and a verification method for KC-100 OPV aircraft. Flight data compatibility analysis was performed to determine suitability of the estimation method application. Linear model estimation was performed using the maximum likelihood estimation method. Results of aerodynamic DB tuning process and verification applying the FFS standard to the nonlinear model constructed are presented.