CN115630556B - Motor topology optimization method based on vertex method - Google Patents
Motor topology optimization method based on vertex method Download PDFInfo
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Abstract
The invention discloses a motor topology optimization method based on a vertex method, which comprises the following steps: s1, dividing a design area of a motor into m parts, and taking a vertex position as a variable; and S2, connecting all vertexes in the same region into a polygon, taking the overlapped part of the polygon and the corresponding sub-region as the shape of one material in the sub-region, and taking the rest part in the sub-region as the other material. Determining a motor topological structure according to the distribution of materials in each subarea; s3, selecting a target to be optimized according to design requirements, and optimizing coordinate parameters of the vertex by using an intelligent optimization algorithm to obtain a series of optimal vertex positions which enable the motor performance to meet the requirements; s4, judging whether the performance of the motor meets the design requirement, and if so, finishing the design; otherwise, the step S1 is returned to. The invention can realize the automatic design of the high-performance motor on the premise of reducing human intervention.
Description
Technical Field
The invention relates to the technical field of motors, in particular to a design method for motor topology optimization.
Background
With continuous innovation and rapid development of modern industry, motors are used as common electromechanical energy conversion devices and spread in various fields of national economy. With the continuous improvement of the performance requirements of the motor, the prior topological structure is difficult to meet the requirements. Therefore, innovations in topology are urgently needed to meet the increasing performance demands on the electrical machines.
At present, the optimization of the motor topology mainly comprises parameterization of some new topological structures and then optimization of the topological structures by using an intelligent algorithm. There are three main problems with such an approach: first, to develop a new topology, the requirement for the researchers is very high, and it takes a lot of time to perform the experimental simulation. Secondly, although the new topological structure can meet the performance requirements of the motor, the structure is very complex, and parameters are difficult to abstract out to express the topological structure. Finally, even if its shape can be represented using some parameters, the results of the optimization are limited to the initial structure, making it difficult to generate new structural shapes. This means that it is difficult to jump out of the locally optimal solution and into the globally optimal solution during the optimization process.
In conclusion, the prior art cannot achieve the aim of designing a motor with high performance without depending on the existing structure, and the patent provides a method for realizing free evolution of a topological structure by using a vertex to represent the shape of the motor and optimizing the position of the vertex through an intelligent algorithm.
Disclosure of Invention
The technical problem is as follows: the invention aims to provide a motor topology optimization method based on a vertex method, which changes the shape of a material by changing the vertex parameters of the material in each subarea, thereby improving the performance of the motor and solving the problems of high requirement on practitioners and dependence on the original topology structure in the existing motor design and optimization process.
The technical scheme is as follows: the invention adopts a motor topology optimization method based on a vertex method for realizing the aim, which comprises the following steps:
the method considers the design area of the motor as the combination of materials with different shapes, uses the coordinate parameters of each vertex of the materials to represent the shape of each material, and optimizes the coordinate parameters of each vertex, namely the vertex position, by an optimization method, thereby optimizing the topological structure of the motor and achieving the aim of optimizing the performance of the motor.
The motor topology optimization method specifically comprises the following steps:
s1, dividing a design area of a motor into m block areas in a two-dimensional coordinate system, wherein the number of vertexes of the ith block area is set as
，
The abscissa and ordinate of each vertex are used as parameters, q parameters are totally included,
；
s2, connecting vertexes of the edge of a certain material in the same subarea into a polygon, taking the polygon as the shape of the material in the subarea, and taking the rest part in the subarea as another material; determining a motor topological structure according to the distribution of materials in each subarea;
s3, selecting a target to be optimized according to design requirements, and optimizing the vertex position coordinate parameters by using an intelligent optimization algorithm, so that the topological structure of the motor is changed, and new optimized vertex position coordinates are obtained;
s4, obtaining a certain material shape in the same subarea according to the optimized new vertex position coordinates, determining the motor topology, calculating the performance of the motor with the topology by using a finite element method, judging whether the performance meets the design requirement, and if so, finishing the design; otherwise, the step S1 is returned to.
The method comprises the following steps of dividing a design area of a motor into m subareas in a two-dimensional coordinate system, wherein the dividing mode is divided into uniform division and non-uniform division, and if the design area is a stator tooth area, the uniform division is adopted; if the design area is a rotor core, a non-uniform division mode is adopted.
In m blocks of subareas of the motor, the ith block is used for
The points are polygonal areas with vertexes to represent the material parts, and if the material occupies the subarea, the subarea only has one material.
The material is silicon steel sheet, permanent magnet or air.
The optimization of the coordinate parameters of the vertex position by using the intelligent optimization algorithm specifically comprises the following steps: initially generating a plurality of groups of random coordinate parameters x, wherein x is a q-dimensional vector, calculating an objective function f (x), then changing the value of x according to the value of f (x) and a specifically used intelligent algorithm, recalculating the value of f (x), and entering the next iteration; the parameter x corresponding to the minimum value of f (x) can be automatically found only by defining the value range of x and the target function f (x).
The target to be optimized is selected according to the design requirement, one or more optimization targets are selected according to the actual requirements of the specific engineering, and the topological optimization problem is modeled into a single-target or multi-target optimization problem expressed by the following mathematical expression:
where x is a q-dimensional vector, y is a set of objective functions to be minimized,
for each objective function, n is the number of objective functions,
to limit the inequality constraints of the parameter x, d is the number of inequality constraints,
to limit the equality constraints for parameter x, k is the number of equality constraints.
The targets to be optimized include average torque, torque ripple, efficiency and cost; for the purpose of minimizing torque ripple and cost requirements,
as such; for the goal of maximizing average torque and efficiency requirements,
is the reciprocal thereof; for the targets of torque and efficiency, which are related to the electromagnetic performance of the motor, the performance of the motor is calculated by using a finite element method; for the target that the cost is only related to the material use condition of the motor, the use condition of the material is directly determined according to the topology of the motor and is directly calculated.
The multiple optimization targets obtain motor topology according to the coordinate parameters, calculate a target function, calculate the electromagnetic performance of the motor by using a finite element method, and directly calculateObtaining cost, and using intelligent optimization algorithm to coordinate parameters
And optimizing, and determining the final topological structure of the motor according to the optimized parameters.
The intelligent algorithm uses a simulated annealing algorithm, a genetic algorithm or a particle swarm algorithm.
Has the beneficial effects that: after the shape of each block of partitioned material is modeled by using the vertex, the shape of the design region evolves along with the change of parameters, and different new schemes are continuously generated by the shape of the design region in the optimization process. Therefore, compared with the traditional motor design method, the motor topological structure design method reduces the intervention of a designer on the motor topological design, and can achieve the aim of improving the motor performance while reducing the human intervention and automatically evolving the motor topological structure. The method has the following beneficial effects:
(1) The motor designed based on the method can reduce human intervention and does not depend on the existing topological structure.
(2) The method is simple, has strong feasibility and is suitable for various motors.
(3) According to different target performances, the method has multiple choices, and can select a proper topology according to requirements.
Drawings
Fig. 1 is a flowchart of a design method for motor topology optimization based on a vertex method.
Fig. 2 (a) is a schematic diagram of a case where the design region is a stator core tooth portion and the division manner is uniform division, and fig. 2 (b) is a schematic diagram of a case where the design region is a motor rotor portion and the division manner is non-uniform division.
Fig. 3 is a schematic diagram of selecting a rotor as a design region, dividing a motor rotor region, and selecting the number of vertices.
Fig. 4 is a schematic view of the rotor after optimization initiation, optimization neutralization and optimization.
Fig. 5 (a) is a schematic diagram of the average torque and the fluctuation of the whole genetic algorithm optimization process changing with the optimization algebra, and fig. 5 (b) is the distribution of all optimization results and the pareto frontier.
Fig. 6 (a) is a topology corresponding to a point a in fig. 5 (B), fig. 6 (B) is a topology corresponding to a point B in fig. 5 (B), fig. 6 (C) is a topology corresponding to a point C in fig. 5 (B), and fig. 6 (D) is a topology corresponding to a point D in fig. 5 (B).
Detailed Description
The technical scheme of the invention is explained in detail by combining the examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It is also to be noted that, for the convenience of description, only some but not all of the features relevant to the present invention are shown in the drawings.
As shown in fig. 1, a flow chart of a method for optimizing a motor topology based on a vertex method disclosed by the invention is exemplarily shown.
S1, dividing a design area of a motor into m blocks of subareas in a two-dimensional coordinate system, wherein the number of vertexes of the ith block of subarea is set as
，
The abscissa and ordinate of each vertex are used as parameters, q parameters are totally included,
；
s2, connecting all vertexes of a certain material edge in the same subarea into a polygon, taking the polygon as the shape of one material in the subarea, and taking the rest part in the subarea as the other material; determining a motor topological structure according to the distribution of materials in each subarea;
s3, selecting a target to be optimized according to design requirements, and optimizing the vertex position coordinate parameters by using an intelligent optimization algorithm, so that the topological structure of the motor is changed, and new optimized vertex position coordinates are obtained;
s4, obtaining a certain material shape in the same subarea according to the optimized new vertex position coordinates, determining the motor topology, calculating the performance of the motor with the topology by using a finite element method, judging whether the performance meets the design requirement, and if so, finishing the design; otherwise, the step S1 is returned to.
The finite element method is carried by maxwell software, and the finite element method can be directly used for calculation after a motor model is drawn.
An example of optimizing a synchronous reluctance machine is as follows:
1. the synchronous reluctance motor rotor is only composed of silicon steel sheets and air, and the materials in the example are only the silicon steel sheets and the air. Considering symmetry, only 1/8 model is needed, as shown in fig. 3, the design area of the rotor of the motor is divided into 8 sub-areas, and considering symmetry, only the left 4 part is considered. The air shape of each section is represented using 6 vertices, each vertex having 2 parameters, so in this example there are 48 optimization parameters.
2. Connecting all vertexes in the same subarea into a polygon, taking the polygon as the shape of air in the subarea, and leaving part of silicon steel sheets in the subarea; and determining the topological structure of the motor according to the distribution of the materials in each subarea.
3. In this example, the optimization targets are average torque and torque ripple, and genetic algorithm is used for optimization. In the optimization process, a new generation of population is generated by a genetic algorithm (the generation of population is the coordinate parameters of a plurality of groups of vertexes); then drawing a motor with a corresponding topology in maxwell software, and calculating the performance of the motor; preserving the high-quality population according to the performance, performing intersection (replacing and recombining partial vertex parameters of two high-quality individuals in the population to generate new individual parameters) and mutation operation (changing the values of certain coordinate parameters of individual strings in the population), and entering next iteration until the maximum algebraic limit is reached.
4. And after the optimization is finished, determining the motor topology according to the new optimized coordinate parameters. And checking whether other indexes meet the design requirements. If so, completing optimization; otherwise, returning to the first step.
Fig. 4 exemplarily shows an evolution process of the motor rotor in the optimization process.
Fig. 5 (a) exemplarily shows a graph in which the average values of the average torque and the torque ripple during each iteration are changed as the number of iterations increases, when the genetic algorithm is used as the optimization method in the vertex method-based motor topology optimization method, and the objective function is selected as the average torque and the torque ripple. Fig. 5 (b) shows an exemplary distribution of all motor performance and pareto fronts during a complete optimization procedure. As can be seen from the figure, the average torque of the motor can be improved and the torque fluctuation can be reduced by adopting the invention.
Fig. 6 (a), 6 (b), 6 (c), 6 (d) exemplarily show the corresponding motor rotor topology located on the pareto front.
The invention discloses a motor topology optimization method based on a vertex method, which can further determine the final topology according to the actual condition of a motor, other performance requirements and process technology according to different results obtained by selecting an objective function.
The above embodiments are merely illustrative of the present patent and do not limit the scope of the patent, and those skilled in the art can make modifications to the parts thereof without departing from the spirit and scope of the patent.
Claims (9)
1. A motor topology optimization method based on a vertex method is characterized in that a design area of a motor is regarded as a combination of materials with different shapes, the shape of each material is represented by each vertex coordinate parameter of the material, and each vertex coordinate parameter, namely a vertex position, is optimized through an optimization method, so that the topological structure of the motor is optimized, and the aim of optimizing the performance of the motor is fulfilled;
the motor topology optimization method specifically comprises the following steps:
s1, dividing a design area of a motor into m block areas in a two-dimensional coordinate system, wherein the number of vertexes of the ith block area is set to be N i I is more than or equal to 1 and less than or equal to m, the horizontal and vertical coordinates of each vertex are taken as parameters, q parameters are in total,
the value range of the parameter cannot exceed the range of the design area;
s2, connecting all vertexes of a certain material edge in the same subarea into a polygon, taking the polygon as the shape of one material in the subarea, and taking the rest part in the subarea as the other material; determining a motor topological structure according to the distribution of materials in each subarea;
s3, selecting a target to be optimized according to design requirements, and optimizing the vertex position coordinate parameters by using an intelligent optimization algorithm, so that the topological structure of the motor is changed, and new optimized vertex position coordinates are obtained;
s4, obtaining a certain material shape in the same subarea according to the optimized new vertex position coordinates, determining the motor topology, calculating the performance of the motor with the topology by using a finite element method, judging whether the performance meets the design requirement, and if so, finishing the design; otherwise, the step S1 is returned to.
2. The vertex method-based motor topology optimization method according to claim 1, wherein a design area of a motor is divided into m partitioned areas in a two-dimensional coordinate system, the dividing manner is divided into uniform division and non-uniform division, and if the design area is a stator tooth area, the uniform division manner is adopted; if the design area is a rotor core, a non-uniform division mode is adopted.
3. The vertex method-based motor topology optimization method according to claim 2, wherein the ith block area is defined as N within m block areas of the motor i The points are polygonal areas with vertexes to represent the material parts, and if the material occupies the subarea, the subarea only has one material.
4. The vertex method-based motor topology optimization method according to claim 3, wherein the material is silicon steel sheet, permanent magnet or air.
5. The vertex method-based motor topology optimization method according to claim 1, wherein the optimizing vertex position coordinate parameters by using an intelligent optimization algorithm specifically comprises: initially generating a plurality of groups of random coordinate parameters x, wherein x is a q-dimensional vector, calculating a target function f (x), then changing the value of x according to the value of f (x) and a specifically used intelligent algorithm, recalculating the value of f (x), and entering the next iteration; the parameter x corresponding to the minimum value of f (x) can be automatically found only by defining the value range of x and the target function f (x).
6. The vertex method-based motor topology optimization method according to claim 1, wherein the objective to be optimized is selected according to design requirements, one or more optimization objectives are selected according to specific engineering practical requirements, and the topology optimization problem is modeled as a single-objective or multi-objective optimization problem expressed by the following mathematical expression:
miny＝[f 1 (x)，f 2 (x)，...，f n (x)]
s.t.g i (x)≤0，i＝1，2，...，d；h j (x)＝0，j＝1，2，...，k
where x is a q-dimensional vector, y is a set of objective functions to be minimized, f (x) is each objective function, n is the number of objective functions, g i (x) For the inequality constraint condition of the limiting parameter x, d is the number of inequality constraints, h j (x) To limit the equality constraint for the parameter x, k is the number of equality constraints.
7. The vertex method based motor topology optimization method according to claim 1 or 6, wherein the targets to be optimized include average torque, torque ripple, efficiency and cost; for the purpose of torque ripple, cost minimization, f (x) is itself; for the target of maximizing average torque and efficiency, f (x) is the reciprocal; for the targets of torque and efficiency, which are related to the electromagnetic performance of the motor, the performance of the motor is calculated by using a finite element method; for the target that the cost is only related to the material use condition of the motor, the use condition of the material is directly determined according to the topology of the motor and is directly calculated.
8. The method of claim 6, wherein the optimization objectives obtain the topology of the motor according to the coordinate parameters, calculate an objective function, calculate the electromagnetic performance of the motor by using a finite element method, directly calculate the cost, optimize the coordinate parameter x by using an intelligent optimization algorithm, and determine the final topology of the motor according to the optimized parameters.
9. The vertex method based motor topology optimization method of claim 8, characterized in that the intelligent optimization algorithm uses a simulated annealing algorithm, a genetic algorithm or a particle swarm algorithm.
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