Piergiorgio Alotto

Stochastic algorithms in electromagnetic optimization

This paper gives an overview of some stochastic optimization strategies, namely, evolution strategies, genetic algorithms, and simulated annealing, and how these methods can be applied to problems in electrical engineering. Since these methods usually require a careful tuning of the parameters which control the behavior of the strategies (strategy parameters), significant features of the algorithms implemented by the authors are presented. An analytical comparison among them is performed. Finally, results are discussed on three optimization problems.

Multiobjective optimization in magnetostatics: a proposal for benchmark problems

A proposal for benchmark problems to test electromagnetic optimization methods, relevant to multiobjective optimization of a solenoidal superconducting magnetic energy storage with active and passive shielding is presented. The system has been optimized by means of different optimization procedures based on the global search algorithm, evolution strategies, simulated annealing and the conjugate gradient method, all coupled to integral or finite element codes. A comparison of results is performed and the features of the problem as a test of optimization procedures are discussed.

Gaussian artificial bee colony algorithm approach applied to Loney's solenoid benchmark problem

Optimization metaheuristics, such as Particle Swarm Optimization, Ant Colony Optimization and bacterial foraging strategies have become very popular in the optimization community and have been successfully applied to electromagnetic device design. The Artificial Bee Colony (ABC) algorithm is a rather new bio-inspired swarm intelligence approach which is competitive with other population-based algorithms and has the advantage of using fewer control parameters. In this work, a standard and an improved version of the ABC algorithm using Gaussian distribution are applied to Loneys solenoid problem, showing the suitability of these methods for electromagnetic optimization.

Optimization of Interior PM Motors With Machaon Rotor Flux Barriers

Interior permanent magnet (IPM) motors are normally designed with two or more flux barriers per pole. The form of such flux barriers has a direct impact on the torque developed by the IPM motor, with regards to both its average value and ripple. The Machaon structure includes flux barriers of different shape, aimed at reducing the torque ripple. Their shape depends on the number of poles, number of slots, winding arrangements, and PM volume used in the rotor. An optimization technique is adopted in order to determine the best shape of the flux barriers with the objective of achieving a smooth torque with a high average value.

A multiquadrics-based algorithm for the acceleration of simulated annealing optimization procedures

A procedure to significantly reduce the computational cost of the simulated annealing optimization algorithm coupled with analysis methods is proposed for EM devices. The chosen approach relies on the application of the simulated annealing method to an analytical approximation of the true objective function, expressed in the form of a multiquadric expansion. The algorithm is fully described, its potential advantages are pointed out and some test cases showing the effectiveness of the implemented strategy are reported and discussed. As an example the superconducting magnet energy storage device is mentioned.

SMES Optimization Benchmark Extended: Introducing Pareto Optimal Solutions Into TEAM22

In 1996, a superconducting magnetic energy storage arrangement was selected to become a benchmark problem for testing different optimization algorithms, both deterministic and stochastic ones. Since the forward problem can be solved semianalytically by Biot-Savarts law, this benchmark became quite popular. Nevertheless, the demands on optimization software have increased dramatically since then. To give an example, methods looking for Pareto-optimal points rather than for a single solution only have been introduced by several groups. In this paper, a proposal for an extended version of the benchmark problem will be made and some results will be presented.

A Modified Imperialist Competitive Algorithm for Optimization in Electromagnetics

Recently, a new kind of socio-politically motivated global search metaheuristic called imperialist competitive algorithm (ICA) was proposed. ICA is based on a form of imperialistic competition in which the populations are represented by countries divided among imperialists and colonies. In this paper, a modified ICA (MICA) approach based on concepts of attraction and repulsion between the colony and its imperialist is introduced during the search for better solutions. A brushless direct current wheel motor benchmark problem is used to investigate the performance of the classical ICA and the proposed MICA and results are shown to be competitive with those of other well-established optimization methods.

A Multiobjective Gaussian Particle Swarm Approach Applied to Electromagnetic Optimization

The development of optimization techniques for multiobjective problems in electromagnetics has been flourishing in the last decade. This paper proposes an improved multiobjective particle swarm optimization approach and applies it to the multiobjective version of TEAM workshop problem 22. Simulation results show that this improved version of the algorithm finds a better Pareto-optimal front with respect to more classical PSO methods while maintaining a better spread of nondominated solutions along the front. Furthermore, the proposed algorithm is compared with the widely used Nondominated Sorting Genetic Algorithm-II (NSGA-II) method highlighting a strongly different behaviour of these strategies.

Discontinuous finite element methods for the simulation of rotating electrical machines

The capability of discontinuous finite element methods of handling non‐matching grids is exploited in the simulation of rotating electrical machines. During time stepping, the relative movement of two meshes, consistent with two different regions of the electrical device (rotor and stator), results in the generation of so‐called hanging nodes on the slip surface. A discretisation of the problem in the air‐gap region between rotor and stator, which relies entirely on finite element methods, is presented here. A discontinuous Galerkin method is applied in a small region containing the slip surface, and a conforming method is used in the remaining part.

Multiphysics Problems via the Cell Method: The Role of Tonti Diagrams

A common structure of several physical laws emerges naturally from the Tonti diagrams of different physical theories so that topological operators can be built only once and used to assemble the stiffness matrices and the coupling terms of the various problems. This process is known in algebraic topology as coboundary process and is presented as the theoretical background for solving multiphysics problems. The main contribution of this paper is to show that the discrete setting provided by Tonti diagrams not only allows to define discrete counterparts of the differential operators and constituive matrices, but that the same matrices can be used to set up the coupling terms in multiphysics problem formulations. The proposed method is compared with a commercial code on an electro-thermo-mechanical benchmark.