**1. Introduction**

Many researchers have studied magnetic device design optimization and permanent magnet synchronous generator (PMSG) design optimization, which are investigated in many research studies over the last few decades. Efficiency, magnetic flux density distribution, total harmonic distortion (THD), and other performance criteria are commonly used in these studies and are attempted to be improved [1–11]. The most common problems are heat buildup in the rotor, balancing issues, and bearing

issues. Magnetic flux density distribution is a key success criterion that must be maintained within a specific range in order to provide high efficiency and low heating for the electric machine. Many different methods are used for design optimization. It is impossible to perform optimization using real experimental results because there are so many design combinations. In most cases, simulation results are used instead. However, there are limited numbers of studies about high-speed alternator design optimization.

Sadeghierad et al. [12] studied on performance comparisons of alternative designs of high-speed alternators (HSA) for microturbines and considered the design difficulties. Sadeghierad et al. [13] studied on optimizing the design of a high-speed axial flux generator (HSAFG) by the aid of particle swarm optimization (PSO) and genetic algorithm (GA) to maximize the efficiency. They discussed the effect of the lambda, which is the ratio of inner diameter to outer diameter. Ismagilov et al. [14] tested a new topology of the stator magnetic core made of amorphous alloy for a 5 kW 60,000 rpm high-speed permanent magnet electric machine with a tooth-coil winding with six slots and two and four poles. Guo et al. [15] presented a method for determining the back electromotive force (EMF) utilizing air gap static flux density distribution and calculating the coil average inductance at the midline of the quadraturedirect axis. They used gradient descent-based optimization to minimize the volume of high-speed generator for micro turbojet engine. The summary for the state of the art is given in **Table 1**.

As can be seen from the literature review, the studies about design optimization of high-speed generator by using optimization methods are very limited. Also the results those presented to show the performance comparisons of the meta-heuristic optimization methods are very poor.

The motivation of this study is to perform design optimization of 18-Poled 8000 rpm 7 kVA high-speed PMSG. This problem is important because of the high rotor speed and high frequency of the stator flux variation; the design of a high-speed machine differs significantly from the design of a conventional machine with low speed and low frequency. The first motivation of this study is to contribute to the knowledge that has emerged based on the limited number of studies on this subject in the literature, with a new study on topology optimization of high-speed PMSGs.

The second motivation is to show the performance of the different class of optimization techniques on the design problem of high-speed alternators to the related researchers. Deterministic or stochastic algorithms can be used for optimization. Due to their high processing demands, deterministic approaches are ineffective for handling multimodal and nonlinear complex issues. The nature is a major source of inspiration for meta-heuristic algorithms, which are stochastic approaches utilized for



*Design Optimization of 18-Poled High-Speed Permanent Magnet Synchronous Generator DOI: http://dx.doi.org/10.5772/intechopen.106987*

optimization. There are four different types of meta-heuristics: (*i*) evolutionary, (*ii*) swarm, (*iii*) physical and chemical, and (*iv*) human. Various well-known optimization methods, such as response surface methodology (RSM) (gradient-based methods), GA (evolutionary-based algorithms), PSO (swarm-based optimization algorithms), and modified social group optimization algorithm (MSGO) (human-based optimization algorithms), are used for this purpose.

The selected design parameters (magnet thickness (MH), offset, embrace (EMB)) and the responses (efficiency (%), rated torque (N.m), air-gap flux density (Tesla), armature current density (A/mm<sup>2</sup> ), armature thermal load (A<sup>2</sup> /mm<sup>3</sup> )) are not previously used together for high-speed alternator design optimization problem. So this is the novelty aspect of this research.

This research was carried out in a real industrial plant, and by focusing on a small number of parameters, we hoped to have a smaller impact on the layout and operation of a serial production line (Such as redesigning assembly parts that may have an impact on standard production, cooling design, body design, and so on.). As a result, the parameters (magnet thickness (MH), offset, embrace (EMB)) that have the least impact on the outer dimensions of the alternator are chosen as the design parameters (factors). The following section goes over the materials and methods.
