Techno‐economic design optimisation of an interior permanent‐magnet synchronous motor by the multi‐objective approach

Abstract

In engineering terms, it is always desirable to maximise the efficiency of the motor and to look the problem in economic viewpoint, minimisation of the weight and cost of the motor is required. As these two aspects are like two sides of a coin, it is usually aimed to acquire the best efficiency per weight and cost. As a result, the performance improvement of permanent-magnet synchronous motor (PMSM) has two sides: technical and economic. This study proposes a new approach for design optimisation of an interior PMSM (IPMSM) taking into account both technical performances and economic considerations. The selected rotor configuration is a good candidate for general purpose industrial applications. A multiobjective optimisation technique based on a new and efficient magnetic equivalent circuit of the motor is applied to obtain optimal motor parameters. A Pareto front composed of possible optimal solutions is provided. The best optimal solution is then selected using a k-means clustering algorithm. To verify the efficacy of the design optimisation, the performance characteristics of the optimal PMSM are compared by both the finite element simulations and the experiments. In the test setup, an 8-pole, 200-Watt, four-phase IPMSM with an optimised structure is prototyped where the results give agreeable accuracy.

Multi-Objective Optimal Design of Permanent Magnet Synchronous Motor for Electric Vehicle Based on Deep Learning

“…The optimal design for a PMSM can be created by combining design methods such as analytical models [1,2], magnetic equivalent circuit (MEC) models [3,4], and finite element analysis (FEA) [5][6][7][8] with an optimal design algorithm. Although these design methods have their advantages, the FEA optimization method combined with the optimal design algorithm has the highest accuracy [5].…”

Multi‐objective optimisation design and performance comparison of permanent magnet synchronous motor for EVs based on FEA

“…Nowadays, there is a lot of research on multi-objective design optimisation of motor. In general, there are three methods for multi-objective design optimisation of motor: linear analytical model [6][7][8][9], magnetic equivalent circuits (MEC) model [10][11][12][13][14], and finite element analysis (FEA) model [15][16][17][18][19][20][21], all of them can be combined with modern optimisation algorithms such as non-dominated sorting GA-II, artificial bee colony algorithm, modified particle swarm optimisation (MPSO) etc [22][23][24][25][26][27][28].…”

Optimal Design of PMSM Based on Automated Finite Element Analysis and Metamodeling

“…Optimal design is a method of finding the values of design variables to obtain an optimal solution within a range of constraints. The optimal design for PMSMs is created by combining design methods such as the analytical model, magnetic equivalent circuits (MEC) model, and finite element analysis (FEA) with optimal design algorithms [1][2][3][4][5][6][7][8]. First of all, there are studies on optimal design using the analytical model [1,2].…”

“…The stator current was optimized considering magnetic saturation using an analytical expression. The following are studies on optimization using the MEC model [3,4]. In [3] it was reported that the MEC optimization method combined with an optimization algorithm can optimize the volume and energy loss of a PMSM.…”

“…In [3] it was reported that the MEC optimization method combined with an optimization algorithm can optimize the volume and energy loss of a PMSM. A novel MEC model of a PMSM to obtain the maximum efficiency, minimum weight, and price was developed [4]. K-means clustering algorithm was utilized to obtain the best solution out of the eight clusters.…”