Design parameters.
Abstract
This chapter proposes a novel topology optimization method for the material distribution of electrical machines using the genetic algorithm (GA) combined with the cluster of material and the cleaning procedure. Moreover, the obtained rotor structure was assumed to consist of the simple shape of PMs in order to consider ease of manufacturing. The rotor structure of a permanent magnet (PM) synchronous motor is designed and manufactured. The optimized rotor has 32% more average torque than that of the experimental motor with the same stator. The effectiveness of the proposed method is verified.
Keywords
- topology optimization
- genetic algorithm
- permanent magnet synchronous motor
- finite element method
- manufacturing
1. Introduction
There are several design techniques to optimize electrical machines and electromagnetic devices. However, most of these techniques were restricted to the optimization of a couple of parameters defining the shape. I think that the first step of optimal design should design the topology of these structures by starting from an empty space. Topology optimization allows obtaining an initial conceptual structure starting with minimal information regarding the structure of the object. Topology optimization methods are very promising and, therefore, were proposed about 20 years ago [1, 2]. Since then, several papers have been published in this field. For example, reference [3] proposed a topology optimization using design sensitivity. Reference [4] proposed an ON/OFF sensitivity method and hybridized it with the GA in order to improve convergence characteristics. Reference [5] designed an electromagnetic system by a topology optimization method considering magnetization direction. Reference [6] proposed a topology optimization method coupling with magneto-thermal systems. Reference [7] designed a 3D electromagnetic machine with soft magnetic composite core. Reference [8] proposed a topology optimization method using the GA and ON/OFF sensitivity in conjunction with a blurring technique in order to avoid small structure spots. Reference [9] took into account a mapping function to improve convexity in the topology optimization procedure. Reference [10] applied a topology optimization method to a coupled magnetic structural problem. Reference [11] designed an IPM motor using the ON/OFF method. Reference [12] optimized magnetic actuators by a level-set method. Reference [13] optimized an inductor by the evolutionary algorithm. Reference [14] proposed a 3D topological optimization method based on the multistep utilization of GA. Reference [15] presented a possible solution to the structural optimization problem using a simple heuristic search algorithm.
The author proposed a topology optimization method to optimize the distribution of materials within an electrical machine using the GA [16]. In addition, he proposed a concept for the cluster of materials and a cleaning procedure for the materials and designed the stator of a brushless DC motor based on this method [17]. However, that study considered only two types of materials, air, and iron, and therefore, it is similar to the ON/OFF method. He improved the previous method in order to consider more than two materials namely, air and iron as well as
This chapter summarizes the novel topology optimization method for the material distribution of electrical machines using the GA combined with the cluster of material and the cleaning procedure. Moreover, the obtained rotor structure was assumed to consist of the simple shape of PMs in order to consider ease of manufacturing. The proposed method is applied to the design of the rotor structure of PM synchronous motor. It is an interior permanent magnet synchronous motor (IPMSM) used for air-conditioning. The average torque characteristics of IPMSMs are compared with the commercialized motor.
2. Proposed topology optimization method
In this section, the topology optimization method is briefly explained, which is implemented in this study. GA is an algorithm that imitates the evolution of living things and is suitable for problems with a large sample space. In the proposed method, the design region is split into finite element meshes, and the materials of several elements—for example, a cell—are associated with a gene in the chromosome. For example, if we consider three types of materials—for example, air, iron, and magnet, which are set to 0, 1, and 2, respectively—the chromosome is composed of some genes as shown in Figure 1. Two parents are selected randomly, and some genes are selected to be exchanged by a uniform crossover with a crossover ratio, and then, two new children are generated as shown in Figure 1. The children inherit the good characteristics of parents by repeating the process. We proposed the concept of the cluster with many types of materials. For example, irons 2 and 3 form the same cluster because they are next to each other as shown in Figure 2a, and iron 4 forms another cluster. If the area of cluster is narrow, that is, the number of cells in the same cluster is smaller than or equal to an integer
Figure 3 shows the cross section of a four-pole PM synchronous motor with distributed windings. One-eighth of the rotor is designed for symmetry. This study iterates the GA with the newly increased length of genes. For the first iteration, a coarse topology is designed using a small number of design variables in a 5 × 9 array of cells as shown in Figure 4a. Three magnetized directions of permanent magnet are dealt with as shown in Figure 5. Figure 6 shows the treatment of the cluster of material on the boundary. The
A fine topology then is designed using a large number of design variables for the second iteration in a 20 × 18 array of cells as shown in Figure 4b. For the second iteration, a set of initial individuals in the GA inherit the individual that has the best fitness at the conclusion of the previous iteration. For example, the initial material in cell P0 is generated by a probability of 1/5 from materials in cells P0, P1, P2, P3, and P4 shown in Figure 7. The whole flowchart for the proposed method is shown in Figure 8. The parts highlighted by the thick line are newly added to the conventional GA with the elite selection. The parameter
Figures | Material | ||
---|---|---|---|
Figure 10a | Air, iron, |
1 | 4 |
Figure 10b | Air, iron, |
1 | 4 |
Figure 10c | Air, iron, |
1 for air and iron, 0 for PM | 4 |
Figure 10d | Air, iron, |
0 | 0 |
3. Rotor structure obtained by the topology optimization method
We optimize the topology of the rotor structure by considering two types of PMs;
Figure 10a shows the obtained rotor structure, in which three types of materials—air, iron, and the r-oriented magnet—are taken into account.
The optimized rotor shapes shown in Figure 10b, c appear as
4. Optimization considering ease of manufacturing
The obtained rotor structures are complex and impractical. In order to consider the ease of manufacturing, magnets and air pockets are assumed to be simple shapes, and they are then optimized using conventional techniques. For example, the rotor structures shown in Figure 12a can be assumed to be similar to the ones in Figure 10a, where the magnets are represented by four parameters. The rotor structure shown in Figure 10b, c can be assumed to contain four hexahedron PMs as shown in Figure 12b. In this shape, the rotor structure is represented by six parameters if the thickness of the magnets is uniform and the volume of the magnets is specified. We assume that the shape of each magnet is a hexahedron and the magnet is magnetized in the vertical direction as shown in Figure 12b for the ease of magnetization. Moreover, we assume that a core area is introduced on the surface of the rotor as shown in Figure 12b to insure machine strength against centrifugal force. Therefore, parameter
An example to be optimized is the rotor of an experimental motor. This experimental motor is well known as the D model in IEE Japan for an air-conditioner and has an IPM-type rotor. A full-search method to optimize the rotor shape is used, because we want to verify that there is a good rotor shape similar to those shown in Figure 10b, c. The angle of position
Figure 13 shows the obtained rotor structure, where the “best” rotor structure provides the largest average torque at the second iteration of the full-search method, and the “second” one provides the second-largest average torque at the first iteration. It was found that the “best” rotor structure is
5. Comparison of measured results
We have manufactured the designed rotor shown in Figure 14a. Figure 16 shows the measured electromotive force when the rotor is rotating at a speed of 1500 min−1. The effective value and fundamental component of the electromotive force are 96.3 and 133.8 V, respectively, and those for the experimental motor are 68.2 and 95.6 V, respectively. Therefore, the electromotive force of the designed motor is 1.4 times larger than that of the experimental motor. Figure 17 shows the inductance measured by an LCR meter at 100 Hz. The obtained
where
Figure 18 shows the torque–current characteristics when
6. Conclusions
In this study, we designed the rotor structure of PM synchronous motors. The proposed optimization process combines the topology optimization method and a method that considers the ease of manufacturing. We assumed four hexahedron PMs similar to the rotor shapes obtained by the proposed method for reasons of manufacturing ease. The obtained rotor of the compressor motor for the air-conditioner has 32% more average torque than that of the experimental motor with the same stator. Therefore, the effectiveness of the proposed method is verified.
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