基于不确定性的旋翼转速优化直升机参数设计

doi:10.7527/S1000-6893.2015.0285

Abstract

Abstract:

In order to improve the quality of design schemes of helicopter with optimum speed rotor, this paper studies the design method of helicopter with optimum speed rotor, based on uncertainty multidisciplinary design optimization. First of all, the uncertainty factors of helicopter parameters are analyzed and modeled from optimal rotor speed, processing error and material deterioration, and it shows that the optimal rotor speed is the main uncertainty factor in the design of helicopter with optimum speed rotor. And then under the collaborative optimization framework, the models of helicopter flight performance, helicopter weight, flight stability, and the performance of turboshaft engine with variable rotor speed are established. Finally, the design of helicopter with optimum speed rotor based on uncertainty multidisciplinary optimization is investigated, which is based on two subsystem design tasks, i.e., hovering performance and flight stability, and one system level design task about helicopter endurance. Optimization results show that the second scheme for the helicopter with the optimum speed rotor is the best one; its probability of satisfying the constraints of required power being less than 350 kW in hover and index of flight stability being less than 0.8, is not less than 95.46%, and expectation of endurance is also bigger.

Key words: optimum speed rotor, helicopter preliminary parameters, uncertainty, multidisciplinary optimization, endurance

CLC Number:

V211.3

XU Ming, LI Jianbo, PENG Minghua, LIU Cheng. Parameter design of helicopter with optimum speed rotor based on uncertainty optimization[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2016, 37(7): 2170-2179.

References

[1] CELI R. Recent application of design optimization to rotorcraft-A survey[J]. Journal of aircraft, 1999, 36(1):176-189.
[2] CARTY A. An approach to multidisciplinary design analysis and optimization for rapid conceptual design[C]//9th AIAA/ISSMO Symposium on Multidisciplinary Analysis and Optimization. Reston:AIAA, 2002.
[3] JOHNSON W, SINSAY J D. Rotorcraft conceptual design environment[C]//The 3rd International Basic Research Conference Rotorcraft Technology. Nanjing:Nanjing University of Aeronautics and Astronatutics, 2009:33-41.
[4] VU N A, LEE J W, SHU J I. Aerodynamic design optimization of helicopter rotor blades including airfoil shape for hover performance[J]. Chinese Journal of Aeronautics, 2013, 26(1):1-8.
[5] BYRNE D M, TAGUCHI S. The Taguchi approach to parameter design[C]//40th Annual Quality Congress Transactions. Milwaukee, WI:American Society for Quality Control, 1987:19-26.
[6] KOCH P N, SIMPSON T W, ALLEN J K, et al. Statistical approximations for multidisciplinary design optimization:The problem of size[J]. Journal of Aircraft, 1999, 36(1):275-286.
[7] PADMANABHAN D, BATILL S M. An iterative concurrent subspace robust design framework[C]//Proceedings of 8th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization. Reston:AIAA, 2000:133-138.
[8] MAVRIS D V, BANDTE O, DELAURENTIS D A. Robust design simulation:A probabilistic approach to multidisciplinary design[J]. Journal of Aircraft, 1999, 36(1):298-397.
[9] DU X, CHEN W. Efficient uncertainty analysis methods for multidisciplinary robust design[J]. AIAA Journal, 2002, 38(8):1474-1478.
[10] ZANG T A, HEMSCH M J, HIBURGER M W, et al. Needs and opportunities for uncertainty based multidisciplinary design methods for aerospace vehicles:NASA/TM-2002-211462[R]. Washington, D.C.:NASA, 2002.
[11] KAREM A E. Optimum speed rotor:U.S. Patent Application NO.60/075, 509[P]. 1998-02-20.
[12] JAMES D, DAVID F. Operational benefits of an optimal widely variable speed rotor[C]//The 66th Annual Forum Proceedings of the American Helicopter Society. Philadelphia, PA:the American Helicopter Society, 2010.
[13] IWATA T, ROCK S M. Benefits of variable rotor speed in integrated helicopter/engine control:AIAA-1993-3851-CP[R]. Reston:AIAA, 1993.
[14] GU X, RENAUD J E. Implicit uncertainty propagation for robust collaborative optimization[C]//Proceedings of DETC01 ASME 2001 Design Engineering Technical Conference and Computers and Information in Engineering Conference. New York:ASME, 2001.
[15] BALLIN M G. A high fidelity real-time simulation of a small turboshaft engine:NASA TM 100991[R]. Washington, D. C.:NASA, 1988.
[16] ROTH B. A work potential perspective of engine component performance:AIAA-2001-3300[R]. Reston:AIAA, 2001.
[17] STEPNIEWSKI W Z, SHINE R A. A comparative study of Soviet vs Westhelicopter, Part 2-Evaluation of weight, maintainability, and design aspect of major component:NASA TM 10062[R]. Washington, D. C.:NASA, 1983.
[18] 徐明, 李建波, 韩东. 旋翼转速优化直升机的纵向操纵性与稳定性分析[J]. 航空动力学报, 2015, 30(6):1374-1381.XU M, LI J B, HAN D. Studies on longitudinal stability and controllability of OSR[J]. Journal of Aerospace Power, 2015, 30(6):1374-1381(in Chinese).
[19] 彭名华, 张呈林. 直升机操纵稳定性优化设计[J]. 南京航空航天大学学报, 2011, 43(3):283-288.PENG M H, ZHANG C L. Optimization design of helicopter stability and control[J]. Journal of Nanjing University of Aeronautics & Astronautics, 2011, 43(3):283-288(in Chinese).
[20] YAO W A, CHEN X Q, ZHAO Y, et al. A fractional spacecraft system assessment tool based on lifecycle simulation under uncertainty[J]. Chinese Journal of Aeronautics, 2012, 25(1):71-82.
[21] 王宇, 余雄庆. 考虑不确定性的飞行总体参数优化方法[J]. 航空学报, 2009, 30(10):1883-1888.WANG Y, YU X Q. Optimization method for aircraft conceptual design under uncertainty[J]. Acta Aeronautica et Astronautica Sinica, 2009, 30(10):1883-1888(in Chinese).
[22] SIVA C, MURUGAN M S, GANGULI R. Effect of uncertainty on helicopter performance predictions[J]//Proceedings of the Institution of Mechanical Engineers Part G Journal of Aerospace Engineering, 2010, 224(5):549-562.
[23] MURUGAN S, HARURSAMPATH D, GANGULI R. Material uncertainty propagation in helicopter nonlinear aeroelastic response and vibration analysis[J]. AIAA Jouranl, 2009, 46(9):2332-2344.
[24] JUN S, YEE K, LEE J, et al. Robust design optimization of unmanned aerial vehicle coaxial rotor considering operational uncertainty[J]. Journal of Aircraft, 2011, 48(2):353-367.S, Ganguli R. Effect of uncertainty on helicopter performance predictions[C]//Proceedings of IMechE Vol. 224 Part G: Journal of Aerospace Engi-neering, 2015:549-562.
[24] Senthil M, Dineshkumar H, Ranhan G. Material uncer-tainty propagation in helicopter nonlinear aeroelastic response and vibration analysis[J]. AIAA JOURANL, 2009, 46(9):2332-2344.
[25] Sangok J,Kwanjung Y, Jaewon L, et al. Robust design optimization of unmanned aerial vehicle coaxial rotor considering operational uncertainty[J]. JOURNAL OF AIRCRAFT, 2011, 48(2): 353-367.

Parameter design of helicopter with optimum speed rotor based on uncertainty optimization

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics

Comments

[1]	SUN Yang, CHANG Min, BAI Junqiang. Trajectory planning and control for micro-quadrotor perching on vertical surface [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(9): 325756-325756.
[2]	CHEN Zhiyuan, LI Luyi. Efficient methods for reliability sensitivity analysis of inputs with distribution parameter uncertainty [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(9): 325881-325881.
[3]	XIAHOU Tangfan, CHEN Jiangtao, SHAO Zhidong, WU Xiaojun, LIU Yu. Model validation metrics for CFD numerical simulation under aleatory and epistemic uncertainty [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(8): 25716-025716.
[4]	LI Xiaoyang, TAO Zhao, ZHANG Wei. Reliability modelling for fatigue based on uncertain differential equation [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(8): 225820-225820.
[5]	WANG Ding, YIN Jiexin, GAO Lu, YANG Bin. A novel method for TDOA localization in presence of synchronization clock bias and sensor position uncertainty [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(7): 325405-325405.
[6]	LUO Jiaqi, FU Wenhao, ZENG Xian, XIA Zhiheng. Uncertainty impact of Reynolds number on flow losses of high-lift low-pressure turbine cascade [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(7): 125427-125427.
[7]	LI Jinsheng, ZHUANG Ling, SONG Jiahong, LU Baogang, SU Wei, WU Qiao. Aircraft aerodynamic characteristic correction framework for engineering data [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(5): 125157-125157.
[8]	LI Ning, LIU Zhiyong, WANG Na, YANG Lei. Simulation on antenna servo control system based on DUEA [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(2): 324986-324986.
[9]	ZHAO Huan, GAO Zhenghong, XIA Lu. Efficient robust aerodynamic design optimization method for high-speed NLF airfoil [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(1): 124894-124894.
[10]	NIAN Peng, SONG Bifeng, XUAN Jianlin, WANG Siqi. Modeling method for propulsion system of flapping wing vehicles [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2021, 42(9): 224646-224646.
[11]	CHEN Jiangtao, ZHANG Chao, WU Xiaojun, ZHAO Wei. Quantification of turbulence model-selection uncertainties considering discretization errors [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2021, 42(9): 625741-625741.
[12]	DU Yufeng, LIN Jun, WANG Xunnian, XIONG Neng. Analysis of modes of disturbances in compressible fluid in subsonic wind tunnel [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2021, 42(6): 124424-124424.
[13]	JIA Qingxuan, DUAN Jiaqi, CHEN Gang. Uncalibrated visual servo of space robots performing on-orbit assembly alignment task [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2021, 42(6): 424063-424063.
[14]	WEI Kepeng, HU Jian, YAO Jianyong, XING Haochen, LE Guigao. Fast terminal sliding mode control of neural networks for aeromechanical actuators [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2021, 42(6): 624540-624540.
[15]	DONG Leiting, ZHOU Xuan, ZHAO Fubin, HE Shuangxin, LU Zhiyuan, FENG Jianmin. Key technologies for modeling and simulation of airframe digital twin [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2021, 42(3): 23981-023981.