Search

In this paper, a multiobjective design optimization method combining design-of-experiments techniques and differential-evolution algorithms is presented. The method was implemented and utilized in order to provide practical engineering insights for the optimal design of interior and spoke-type permanent-magnet machines. Two combinations with 12 slots and 8 poles and 12 slots and 10 poles, respectively, have been studied in conjunction with rare-earth neodymium-iron-boron (NdFeB) and ferrites. As part of the optimization process, a computationally efficient finite-element electromagnetic analysis was employed for estimating the performance of thousands of candidate designs. Three optimization objectives were concurrently considered for minimum total material cost, power losses, and torque ripple, respectively. Independent variables were considered for both the stator and rotor geometries. A discussion based on a systematic comparison is included, showing, among other things and despite common misconception, that comparable cost versus loss Paretos can be achieved with any of the rotor topologies studied. [ABSTRACT FROM PUBLISHER]

In this paper, a robust parametric model of a brushless permanent magnet machine with fractional-slot concentrated windings, which was developed for automated design optimization is presented. A computationally efficient finite-element analysis method was employed to estimate the dq-axes inductances, the induced voltage and torque ripple waveforms, and losses of the machine. A method for minimum effort calculation of the torque angle corresponding to the maximum torque per ampere load condition was developed. A differential evolution algorithm was implemented for the global design optimization with two concurrent objectives of minimum losses and minimum material cost. An engineering decision process based on the Pareto-optimal front for 3,500 candidate designs is presented together with discussions on the tradeoffs between cost and performance. One optimal design was finally selected, prototyped and successfully tested. [ABSTRACT FROM AUTHOR]

The design optimization methods described in this paper are employing an ultrafast computationally efficient finite element analysis technique. A minimum number of magnetostatic solutions are used for the analysis, which makes possible the study of thousands of candidate motor designs with typical PC-workstation computational resources. A multi-objective differential evolution algorithm that considers a large number of independent stator and rotor geometric variables and performance criteria, such as average and ripple torque, losses, and efficiency, is used. The optimization method is demonstrated on different permanent magnet (PM) ac synchronous motors in the kilowatt and megawatt power ranges. For the low-power PM ac machine study, a nine-slot six-pole topology is considered. For the high-power PM ac machines, four case studies were carried out with the following: fractional-slot embedded surface PM (SPM), fractional-slot interior PM (IPM), integer-slot SPM, and integer-slot IPM, respectively. Four motor topologies are systematically compared based on optimal Pareto sets. The design optimization of IPM motors includes an additional search for an optimum operating torque angle corresponding to the maximum-torque-per-ampere condition. [ABSTRACT FROM AUTHOR]

Computationally efficient finite-element analysis (FEA) (CE-FEA) fully exploits the symmetries of electric and magnetic circuits of sine-wave current-regulated synchronous machines and yields substantial savings of computational efforts. Motor performance is evaluated through Fourier analysis and a minimum number of magnetostatic solutions. The major steady-state performance indices (average torque, ripple and cogging torque, back-electromotive-force waveforms, and core losses) are satisfactorily estimated as compared with the results of detailed time-stepping (transient) FEA. In this paper, the CE-FEA method is presented and applied to a parametric design study for an interior-permanent-magnet machine. Significant reduction of simulation times is achieved (approximately two orders of magnitude), permitting a comprehensive search of large design spaces for optimization purposes. In this case study, the influence of three design variables, namely, stator tooth width, pole arc, and slot opening, on three performance indices, namely, average torque, efficiency, and full-load torque ripple, is examined, and design trends are derived. One hundred candidate designs are simulated in less than 20 minutes on a state-of-the-art workstation. [ABSTRACT FROM PUBLISHER]