The main objective of this two-part state-of-the-art paper called “Recent Advances in the Design, Modeling, and Control of Multiphase Machines” is to present latest contributions in the multiphase machines' field. The first part of this paper focuses on the recent progress in the design, modeling, and control, whereas the drive is in healthy operation. This second part presents relevant contributions in two not analyzed fields. The first is in relation with the use of the additional degrees of freedom of multiphase machines and the exploitation of their fault-tolerant capabilities without adding extra hardware. The second one analyzes multiphase generation, particularly in grid-connected wind energy conversion systems and stand-alone applications. Recent progresses are shown and open challenges and future research directions are discussed.

Recent Advances in the Design, Modeling, and Control of Multiphase Machines—Part II

This paper systematically covers the significant developments of the last decade, including surrogate modeling of electrical machines and direct and stochastic search algorithms for both single- and multi-objective design optimization problems. The specific challenges and the dedicated algorithms for electric machine design are discussed, followed by benchmark studies comparing response surface (RS) and differential evolution (DE) algorithms on a permanent-magnet-synchronous-motor design with five independent variables and a strong nonlinear multiobjective Pareto front and on a function with eleven independent variables. The results show that RS and DE are comparable when the optimization employs only a small number of candidate designs and DE performs better when more candidates are considered.

A Review of Recent Developments in Electrical Machine Design Optimization Methods With a Permanent-Magnet Synchronous Motor Benchmark Study

Disruptive innovations in electrical machine design optimization are observed in this paper, motivated by emerging trends. Improvements in mathematics and computer science enable more detailed optimization scenarios that cover evermore aspects of physics. In the past, electrical machine design was equivalent to investigating the electromagnetic performance. Nowadays, thermal, rotor dynamics, power electronics, and control aspects are included. The material and engineering science have introduced new dimensions on the optimization process and impact of manufacturing, and unavoidable tolerances should be considered. Consequently, multifaceted scenarios are analyzed and improvements in numerous fields take effect. This paper is a reference for both academics and practicing engineers regarding recent developments and future trends. It comprises the definition of optimization scenarios regarding geometry specification and goal setting. Moreover, a materials-based perspective and techniques for solving optimization problems are included. Finally, a collection of examples from the literature is presented and two particular scenarios are illustrated in detail.

Modern Electrical Machine Design Optimization: Techniques, Trends, and Best Practices

This paper deals with two types of interior permanent magnet (IPM) motors, S-type and V-type. The V-type is optimized in the rotor shape to obtain better performance than the S-type. In general, average operational torque (AOT) and torque ripple of IPM motors are greater than those of other permanent magnet motors due to reluctance torque. This reluctance torque is generated by permanent magnet arrangement in the rotor of IPM motor and causes noise and vibration. Therefore, this paper presents the optimal V-shape, based on the finite-element method, of permanent magnet in the V-type by robust design, called Taguchi method, to reduce torque ripple and improve the ratio between torque ripple and AOT than S-type.

Optimization for reduction of torque ripple in interior permanent magnet motor by using the Taguchi method

This paper reviews the modern electric propulsion architectures and configurations for railway traction, which are currently in practice. The development and advancement of power electronics and digital controllers led to the standardization of the insulated gate bipolar transistor (IGBT)-based converter fed induction motor drives. This paper summarizes the state-of-the-art technology of IGBT-based rolling stock in terms of both power and control. Control hierarchy of traction system and drive control techniques are explored. Special emphasis has been put on the technologies, which can improve energy efficiency as well as reliability to develop high-speed rails and metro trains in the near future in both urban and suburban areas. Specific attention is given to power electronic transformer technology-based traction drives and on-board energy storage systems. In addition, advances in traction drive technology and wide-bandgap power devices are addressed. Finally, major issues faced in rolling stock including the challenges for further improvement are highlighted.

Comprehensive Topological Overview of Rolling Stock Architectures and Recent Trends in Electric Railway Traction Systems

Optimal design with finite element model is often expensive in terms of computation time. The output space mapping technique allows benefiting both the rapidity of the analytical model and the accuracy of the finite element model. In this paper, a three-level output space-mapping technique is proposed to reduce the computation time. Three models having a different granularity and describing the same device are used jointly within the optimization process. Proposed strategy is applied for solving the optimal design problems of two electromagnetic devices. Results show that three-level output space mapping strategy allows saving a substantial computation time compared to the classical two-level output space-mapping.

Three-Level Output Space Mapping Strategy for Electromagnetic Design Optimization

In this paper, an optimization method, based on fractional experimental design, is proposed and applied to the design of a brushless DC motor. Taguchi's methodology and a limited number of finite element simulations are used to build an approximation of the cost function of an optimization problem. This approximation allows one to quickly locate the global optimum.

Optimization with experimental design: an approach using Taguchi's methodology and finite element simulations

The solution of a design problem of an electrical motor shows how the experimental design method can be combined with the numerical simulation and how this approach is well adapted to the optimization process. Firstly, the screening of significant geometric parameters is presented. Then the Response Surface Methodology is used to build an analytical model that is finally employed as a constraint in an obvious optimization process. As a result, the performance of the motor is increased.

Screening and response surface method applied to the numerical optimization of electromagnetic devices

A practical methodology to optimize electrical devices, based on a combination of numerical simulation and the experimental design method, is illustrated on the shape optimization of a permanent magnet motor. Firstly, significant parameters are identified. Secondly, these parameters are used to improve the performance of the machine.

Shape optimization of a permanent magnet motor using the experimental design method

Efficient methods to optimize electrical machines are derived from the Design of Experiments Method (DOE) and applied to the shape optimization of a permanent magnet motor. Different experimental designs are used to build a simple model and to find the optimal response. A fully user-controlled approach and iterative algorithms are compared.

Frederic Gillon

Papers

Three-Level Output Space Mapping Strategy for Electromagnetic Design Optimization

Optimization with experimental design: an approach using Taguchi's methodology and finite element simulations

Screening and response surface method applied to the numerical optimization of electromagnetic devices

Shape optimization of a permanent magnet motor using the experimental design method

Optimization techniques derived from experimental design method and their application to the design of a brushless direct current motor