Pascal Brochet

Multiphysics Modeling of a Permanent Magnet Synchronous Machine by Using Lumped Models

This paper describes the modeling of a permanent magnet synchronous machine (PMSM) by using lumped models (LMs). Designing electrical machines necessarily involves several fields of physics, such as electromagnetics, thermics, mechanics, and acoustics. Magnetic, electrical, electronic, and thermal parts are represented by LMs, whereas vibro-acoustic and mechanical parts are represented by analytical models. The aim of this study is to build a design model of a PMSM for traction applications. Each model is parameterized to optimize the machine. The method of taking into account saturation and movement is described. These fast, LMs make it possible to couple the software used with optimization tools. Simulation results are presented and compared with the finite-element method and the experiments performed.

Multiobjective Optimization of Induction Machines Including Mixed Variables and Noise Minimization

Induction motor design requires making numerous tradeoffs, especially when including electromagnetic noise criterion besides usual criteria like efficiency and cost. Moreover, adding the noise objective significantly increases computational time as it must be evaluated at variable speed in order to take into account resonance effects. In that case, the application of multiobjective optimization algorithms can be hard for their computational cost as for the difficulty to interpret multidimensional results in both design variables and objectives spaces. This paper first describes a fast analytical model of a variable-speed induction machine which calculates both motor performances and sound power level of electromagnetic origin. This model is then coupled to Nondominating Sorting Genetic Algorithm (NSGA-II) in order to perform global constrained optimizations with respect to several objectives (e.g., noise level, efficiency and material cost). As induction machine design involves both continuous and discrete variables, a modified NSGA-II algorithm handling mixed variables is detailed. Finally, some optimization results are presented and analyzed by the aid of several visualization tools.

Three-Level Output Space Mapping Strategy for Electromagnetic Design Optimization

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.

A Parallel Multiobjective Efficient Global Optimization: The Finite Element Method in Optimal Design and Model Development

Conceiving electromagnetic devices using finite element modeling tools is a complex task and also time-costly. The Efficient Global Optimization method, based on the progressive construction of surrogate models, is studied. The method uses Kriging models and allows for multiobjective optimization. An original infill criterion, combining the surrogate models and an estimate of their error is proposed. Moreover, two techniques for the calculi distribution, adapted to the algorithm, are tested on an eight-core machine. An advantage of the method consists in its capability of providing sufficiently accurate models for each objective and constraint function around the obtained Pareto front. The SMES device of the TEAM problem 22 is used as benchmark.

Characterization of the audible magnetic noise emitted by traction motors in railway rolling stock

This paper first presents the analytical models of an ALSTOM simulation software, DIVA, which computes the vibratory and acoustic behavior of a variable-speed induction machine due to Maxwell forces. This radial magnetic pressure in the air-gap makes the stator vibrate in the audible range, creating the so-called magnetic noise characterized by high tonality. On the basis of these analytical models, the main magnetic vibrations due to slotting, pulse-width modulation (PWM) harmonics and their interaction are then analytically characterized. Their number of nodes, velocity and propagation direction are experimentally validated by visualizing the stator deflection shapes. Finally, some experimental validations of the simulation tool are presented. Both analytical results and simulations show that some quieter motors can be designed with motor geometry (especially slot numbers) and PWM strategy.

Design of permanent magnet synchronous machine in order to reduce noise under multi-physic contraints

This paper describes the modeling of a permanent magnet synchronous machine by lumped models. Several fields of physics, such as electromagnetics, thermics, mechanics and acoustics are necessary for designing electrical machines. The aim of this study is to build a design model of a permanent magnet synchronous machine for traction applications which takes into account all these different physical aspects. Magnetic, electrical, electronic and thermal parts are represented by lumped models, whereas vibro-acoustic and mechanical parts are represented by analytical models. Simulation results are presented and compared with the finite element method and experiments. These fast and entirely parameterized, lumped models make it possible to couple the software with optimization tools. Some optimization results are discussed here.

Techno-economic optimization of induction machines: An industrial application

Current economic situation force manufacturers to find the new ways of designing electrical machines. In order to succeed in competitive market, industry has to create new approaches of finding the solutions which will satisfy customers requirements. Task of determining this set of optimal configurations must be done in the least possible time frame. This problem is becoming more complex when the required electrical machine is not in the standard range of configurations and so the price of the solution cannot be determined with high precision. In this article we propose an example of industrial application which assists in defining the set of optimal configurations of induction machine where the criterions of optimality are the efficiency and total cost of manufacturing.

Multi‐objective optimization of a linear induction motor using 3D FEM

Purpose – The purpose of this paper is to present a low evaluation budget optimization strategy for expensive simulation models, such as 3D finite element models.Design/methodology/approach – A 3D finite element electromagnetic model and a thermal model are developed and coupled in order to simulate the linear induction motor (LIM) to be conceived. Using the 3D finite element coupling model as a simulation model, a multi‐objective optimization with a progressive improvement of a surrogate model is proposed. The proposed surrogate model is progressively improved using an infill set selection strategy which is well‐suited for the parallel evaluation of the 3D finite element coupling model on an eight‐core machine, with a maximum of four models running in parallel.Findings – The proposed strategy allows for a significant gain of optimization time. The 3D Pareto front composed of the finite element model evaluation results is obtained, which provides the designer with a set of optimal trade‐off solutions for ...

Comparison between efficient global optimization and output space mapping technique

The optimization of electromagnetic devices by direct use of finite element models is computationally expensive. This paper presents two effective surrogate-assisted optimization algorithms: Output Space Mapping and Efficient Global Optimization which are employed with regard to a minimum number of finite element model evaluations. A parallel between the two algorithms is made through a single phase safety isolating transformer optimization problem using 3D finite element models.

Optimal design of a linear induction motor for subway system

Optimal design by means of finite element models is complex and time consuming. The Efficient Global Optimization (EGO) based on the progressive construction of a Kriging model used to drive the optimization problem allows for an affordable optimization time. In this paper, a linear induction motor (LIM) with double primaries for the subway system is designed, based on the validated 2D finite element model at reduced scale and the tramways needs. The optimal design problem of LIM is formulated using the rated point design approach and achieved using the EGO algorithm.