Optimal design of self-adaptive motor with the hot

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Capacity adaptive electric 11 Optimal design of revolution measurement system

1 Introduction

most oil fields in China use pumping units for oil production, and beam pumping units are mainly used. When driving this kind of pumping unit, the load is very large, so it is forced to choose a larger capacity motor, resulting in the phenomenon of "big horse pulling small car" during normal operation. Especially for the late oil wells that have been exploited for a long time, the motor often runs in idle state, wasting a lot of power resources. In order to meet the needs of energy saving and improve the efficiency of mechanical mining, a capacity adaptive motor is developed in this paper. The machine has main and auxiliary structures, and the stator winding can realize 8/12 pole transformation; Under the control of the controller, it can realize the start of two machines, and automatically realize the single machine operation of the main and auxiliary machines or the joint operation of the main and auxiliary machines according to the load of the production well, so that the motor is always in a better operation range, so as to achieve the purpose of energy saving and consumption reduction

in fact, this kind of motor integrates the main and auxiliary motors through the coaxial rotor; The stator winding uses the phase-shifting and pole changing method for 8/12 transformation. 12 pole as the front pole is the main working pole, and the normal 60 phase band is adopted; 8 very nearly normal 120 phase band. The winding has only 6 ends, so as to facilitate the switching control of two pole states

it can be seen that the motor can provide 6 power outlets through pole changing and combined operation of main and auxiliary machines. Therefore, the design must take into account four single machine schemes and two combined schemes at the same time. In order to reduce the production cost, the motor adopts the stator and rotor punching inner diameter and outer diameter consistent with the Y Series High 8-pole motor with the same center; At the same time, the stator and rotor punching plates of the main and auxiliary motors adopt the same groove type and size respectively

with the help of optimization theory and combined with the characteristics of the motor, this paper establishes a mathematical model of optimal design to comprehensively optimize the overall scheme. By studying several global optimization algorithms [], this paper introduces simulated annealing algorithm into the optimization calculation process. In the framework of this algorithm, the SUMT penalty function method is used to turn the nonlinear constrained optimization problem into a series of irreducible. In this way, the experimental results will produce deviations or invalid beam extremum problems to solve, and the algorithm is adaptively improved in combination with practice, and satisfactory results are achieved

2 mathematical model of optimal design

the problem of motor optimal design can be reduced to a constrained nonlinear programming form:

establishing the mathematical model of motor optimal design is to correctly select the optimization variable set, objective function f and constraint function GJ in combination with reality

in this paper, the slot size of the stator and rotor, the length of the iron core, the wire gauge and the number of turns of the stator winding of the motor are selected as the optimization variables. Obviously, the change of slot size will cause the performance of the four single machine schemes of 8/12 pole main and auxiliary motors to change, so it can be regarded as a common variable; However, the changes in the length of the iron core, wire gauge and the number of turns of the stator winding of the main and auxiliary motors only cause the performance of the two 8/12 pole single machines to change, so they are regarded as non common variables. It can be seen that the optimization variable set is to select the effective material cost of the motor as the objective function by the common variable subset and two non common variable subsets and

according to the optimization principle of common variables and non common variables [4], the objective function can be written as follows

select the efficiency, power factor, maximum torque, starting current, starting torque and thermal load of the motor as the constraints of each single machine scheme, a total of 24 constraints; In order to facilitate the algorithm to make a realistic judgment on the violation degree of different constraints, the constraint function is written in the form of per unit value. At the same time, in order to improve the performance of the main and auxiliary motors when they operate together, the slip ratio of the two motors under the same pole state is constrained

the 26 constraints of the motor optimal design problem are sorted out as follows

where i=1, 2, 3 and 4 are the indicators of the main and auxiliary machine design schemes for 12 pole and 8 pole respectively; The subscript with 0 is the standard value of the constraint; E1 and E2 are two small positive numbers; SN1 and SN2 are the rated slip rates of main and auxiliary motors when they are 12 poles respectively; The s test result is the rated slip rate of the main and auxiliary motors when 94n3 and Sn4 are 8 poles respectively; Other symbols are the same as the identifiers used in motor design

using SUMT penalty function method, the above constrained optimization problem is transformed into a series of unconstrained extreme value problems, then the augmented objective function can be written in the following form

α J is the weighting coefficient for different constraints; Rk is the penalty factor

two methods of simulated regression are used At present, the most commonly used method is to install large deformation on both ends of the collet to prevent the sample from sliding Fire algorithm pair none

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