Optimization design of wind turbine drive train based on Matlab genetic algorithm toolbox
Description
In order to ensure the high efficiency of the whole flexible drive train of the front-end speed adjusting wind turbine, the working principle of the main part of the drive train is analyzed. As critical parameters, rotating speed ratios of three planetary gear trains are selected as the research subject. The mathematical model of the torque converter speed ratio is established based on these three critical variable quantity, and the effect of key parameters on the efficiency of hydraulic mechanical transmission is analyzed. Based on the torque balance and the energy balance, refer to hydraulic mechanical transmission characteristics, the transmission efficiency expression of the whole drive train is established. The fitness function and constraint functions are established respectively based on the drive train transmission efficiency and the torque converter rotating speed ratio range. And the optimization calculation is carried out by using MATLAB genetic algorithm toolbox. The optimization method and results provide an optimization program for exact match of wind turbine rotor, gearbox, hydraulic mechanical transmission, hydraulic torque converter and synchronous generator, ensure that the drive train work with a high efficiency, and give a reference for the selection of the torque converter and hydraulic mechanical transmission
Availability note (English)
Available from http://dx.doi.org/10.1088/1757-899X/52/5/052013Additional details
Identifiers
Publishing Information
- Journal Title
- IOP Conference Series. Materials Science and Engineering (Online)
- Journal Volume
- 52
- Journal Issue
- 5
- Journal Page Range
- [6 p.]
- ISSN
- 1757-899X
Conference
- Title
- 6. international conference on pumps and fans with compressors and wind turbines
- Acronym
- ICPF2013
- Dates
- 19-22 Sep 2013
- Place
- Beijing (China)
INIS
- Country of Publication
- United Kingdom
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 47046902
- Subject category
- S42: ENGINEERING; S36: MATERIALS SCIENCE;
- Resource subtype / Literary indicator
- Conference
- Descriptors DEI
- ALGORITHMS; DESIGN; EFFICIENCY; MECHANICAL TRANSMISSIONS; OPTIMIZATION; ROTORS; TORQUE; TRAINS; WIND TURBINES
- Descriptors DEC
- EQUIPMENT; MACHINE PARTS; MACHINERY; MATHEMATICAL LOGIC; TURBINES; TURBOMACHINERY; VEHICLES