Rotor Optimization Design Of Dual-Stator Brushless Doubly Fed Machine Based On Improved Particle Swarm Optimization

The rapid development of wind power generation technology puts forward higher requirements for wind power generators.Double-stator brushless doubly-fed wind turbine has a very wide development prospect in wind power due to its advantages of no brushes,adjustable power factor,high power density and low cost.Because the two sets of stator windings of the motor rely on the rotor to realize indirect coupling,reasonable rotor design is very important.The cage barrier rotor structure is adopted in this paper.Due to its special structure,the traditional method has the problem of low efficiency and poor precision to design the rotor.In this paper,an improved particle swarm optimization algorithm is proposed to optimize the cage barrier rotor structure of double stator brushless doubly-fed machine.The main research contents are as follows.Firstly,the basic structure of double stator brushless doubly fed machine is introduced.The magnetic field modulation principle and various operation modes of the double stator brushless doubly fed machine are also introduced.Secondly,aiming at the problems of local convergence and boundary convergence in cross-border of standard particle swarm algorithm,an improved particle swarm algorithm is proposed,which is improved by adding chaos search operation and using a new cross-border processing method.It is proposed to increase the precision of chaos search by adaptively controlling the scope of chaos search.The validity of the improved particle swarm optimization algorithm is verified by testing the standard particle swarm optimization algorithm,chaotic particle swarm optimization algorithm and improved particle swarm optimization algorithm respectively through standard test functions.Then,in order to improve the optimization efficiency,the response surface method is proposed to replace the finite element calculation.The basic principle and process of response surface method are studied.The experiment is arranged by the central composite surface design method.The response surface model is built by radial basis function.The relationship between objective function,constraint conditions and optimal design variables is obtained,and the built model is checked.Finally,in order to further improve the rotor coupling capability of the double-stator brushless doubly-fed motor and improve the performance of the motor,the ratio of useful harmonics to fundamental wave content in the air gap magnetic flux density and the voltage distortion rate of the power winding are taken as the optimization objectives,the rotor magnetic flux density is taken as the constraint condition,and the improved particle swarm optimization is utilized to optimize the structural parameters of the caged rotor of the double-stator brushless doubly-fed motor,such as the pole arc coefficient,the ratio of the width of the magnetic conduction layer to the non-magnetic conduction layer,the number of magnetic conduction layers and the number of short-circuit cages.By establishing a finite element analysis model,the no-load and load characteristics of the improved motor scheme and the initial motor scheme are compared and analyzed,and the effectiveness of the improved particle swarm optimization algorithm for the structural optimization of the caged rotor of the double-stator brushless doubly-fed motor is verified.