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Optimal Design And Performance Analysis Of Linear Switched Reluctance Motor For Ocean Wave Power Generation

Posted on:2022-07-11Degree:MasterType:Thesis
Country:ChinaCandidate:D Q XiongFull Text:PDF
GTID:2480306554486684Subject:Master of Engineering
Abstract/Summary:PDF Full Text Request
Ocean energy is a promising renewable energy pattern due to sufficient reserves and various utilization forms.The kinetic energy of sea wave has been widely studied and applicated.The efficiency of direct-drive wave power generation system without conversion device is generally higher than that of conversion systems such as hydraulic turbine and rotating motor.The linear switched reluctance motor has a wide operating speed range and high reliability during normal operation.Without permanent magnets,its allocation costs are lower.The key issues that should be resolved are low efficiency and energy density in the application of wave power generation..the key point is to optimize of output efficiency and energy density of linear switched reluctance motor and analyze ists electromagnetic characteristics.A sensitivity hierarchical optimization method based on entropy method is proposed to formulate the multi-parameter and multi-objective optimization model,which can achieve the enhancement of efficiency and energy density for flat linear switched reluctance motor.It provides a quick and effective reference method for the optimization design of multi-objective motors with complex parameters.The main constructions are as shown follow :Firstly,the topology of cylindrical and flat switched reluctance motors is introduced,and its advantages and disadvantages are analyzed according to the characteristics of the magnetic circuits.In order to accurately understand the correlation between the power generation efficiency,energy density and parameter variables of the motor,the analytical function of the key parameters in the power generation process are derived based on the flat linear switched reluctance motor for the determination of the variables of the multi-objective optimization model of the motor.Then,a three-dimensional finite element model of the linear switched reluctance motor is established and simulated,and the two-dimensional calculation results under low current and saturated current were compared respectively.It was verified that the three-dimensional structure can be replaced by the two-dimensional simulation model with a large number of calculation points,which can reduce the calculation burden and simulation time.At the same time,on the basis of the two-dimensional finite element model,a block diagram of the overall optimization process considering the simulated annealing algorithm,response surface method,and single parameter scanning method is proposed.And the entropy method is used to calculate and determine the proportional weight of the multi-objective function and the sensitivity indices.The sensitivity of the structural parameters is completed and the optimization analysis at each level is performed to ensure that the optimization timeliness while fully considering the interaction between the parameters.Finally,according to the motor structure size determined by optimization,the 2D finite element model is established and simulated under different operating conditions.Comparing the electromagnetic performance indicators of motor efficiency,thrust and magnetic density before and after optimization,it is verified that the effectiveness of the proposed optimization method.At the same time,according to the applicable scenarios of ocean wave power generation,it is proposed that an installation plan for the vertical operation of the motor.The characteristics of the motor under the phenomenon of unbalanced air gap that may occur during operation are studied,which provides a strong reference basis for the production of the prototype platform and the selection of the size of related parts.
Keywords/Search Tags:Wave power generation, Linear switched reluctance generator, Multi-objective optimization, Finite element performance analysis
PDF Full Text Request
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