Energy Consumption Analysis of Helicopter Traction Device: A Modeling Method Considering Both Dynamic and Energy Consumption Characteristics of Mechanical Systems
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- Nuchturee, Chalermkiat & Li, Tie & Xia, Hongpu, 2020. "Energy efficiency of integrated electric propulsion for ships – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
- Ke Song & Yimin Wang & Cancan An & Hongjie Xu & Yuhang Ding, 2021. "Design and Validation of Energy Management Strategy for Extended-Range Fuel Cell Electric Vehicle Using Bond Graph Method," Energies, MDPI, vol. 14(2), pages 1-31, January.
- Somu, Nivethitha & M R, Gauthama Raman & Ramamritham, Krithi, 2020. "A hybrid model for building energy consumption forecasting using long short term memory networks," Applied Energy, Elsevier, vol. 261(C).
- Liu, Wei & Li, Li & Cai, Wei & Li, Congbo & Li, Lingling & Chen, Xingzheng & Sutherland, John W., 2020. "Dynamic characteristics and energy consumption modelling of machine tools based on bond graph theory," Energy, Elsevier, vol. 212(C).
- Borutzky, W. & Barnard, B. & Thoma, J.U., 2000. "Describing bond graph models of hydraulic components in Modelica," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 53(4), pages 381-387.
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- Marcin Żugaj & Mohammed Edawdi & Grzegorz Iwański & Sebastian Topczewski & Przemysław Bibik & Piotr Fabiański, 2023. "An Unmanned Helicopter Energy Consumption Analysis," Energies, MDPI, vol. 16(4), pages 1-28, February.
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