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Probabilistic design optimization of wind turbine gear transmission system based on dynamic reliability

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Abstract

In this paper, a probabilistic design optimization method for wind power gear drive system has been put forward based on the dynamic reliability. A pure torsional dynamic model of 1.5 MW wind turbine gear transmission system is developed which is based on lumped parameter method with incorporation of gear meshing stiffness and transmission error. By taking the wind load and the gear parameters as random variables, the variation in dynamic reliability of the system with time is obtained. The probabilistic optimization design model of the wind turbine gear transmission system with minimum displacement and volume is built. The parameters affecting the dynamic performance and reliability are taken as optimization design variables. The system reliability, the effects of random parameters on the reliability, the normal meshing condition and gear strength are taken as constraint conditions. We choose the gear transmission system of a 1.5 MW wind turbine for the system optimization and experimental verification. The results show that the system optimization based on dynamic reliability can reduce the volume of the system by 17.94 % and the system reliability is also guaranteed. Moreover, the vibration of each component of the system is reduced which is beneficial for smooth operation of the gear transmission system of wind turbine.

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Correspondence to Junkai Fan.

Additional information

Recommended by Associate Editor Jin Woo Lee

Huitao Chen received the Ph.D. degree in mechanical engineering from Chongqing University, Chongqing, China, in 2012. He is currently an researcher in Henan Polytechnic University. His research interests include optimization design of transmission system, modeling and dynamics of transmission system.

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Chen, H., Fan, J., Jing, S. et al. Probabilistic design optimization of wind turbine gear transmission system based on dynamic reliability. J Mech Sci Technol 33, 579–589 (2019). https://doi.org/10.1007/s12206-019-0112-9

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  • DOI: https://doi.org/10.1007/s12206-019-0112-9

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