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Bramerdorfer G.,Johannes Kepler University | Bramerdorfer G.,ACCM Austrian Center of Competence in Mechatronics | Zavoianu A.-C.,ACCM Austrian Center of Competence in Mechatronics | Zavoianu A.-C.,Fuzzy Logic Laboratory Linz Hagenberg | And 5 more authors.
Proceedings - 2015 IEEE International Electric Machines and Drives Conference, IEMDC 2015 | Year: 2015

This article deals with accelerating typical optimization scenarios for electrical machine designs. Besides the advantage of a reduced computation time, this leads to a reduction in computational power and thus to a lower power consumption when running the optimization. If high power density is required, usually highly-utilized electrical machines which feature nonlinear characteristics are applied. As a consequence, typically optimization scenarios are considered where the evaluation of a potential design requires computationally expensive nonlinear finite element (FE) simulations. It is obvious that improving the speed of optimization runs takes top priority and various measures can be considered. This article is about (i) basic easily achievable measures, (ii) techniques for an efficient exploration of the design space, and (iii) advanced strategies to reduce the simulation time, e.g., (a) sophisticated emerging techniques for modeling machine characteristics by paring the number of required FE simulations down to the minimum and (b) nonlinear modeling of the targets of the optimization scenario as functions of the design parameters to further reduce the number of FE evaluations. By way of illustration, the analysis of a typical optimization task is given and achievable speed improvements as well as still present bottlenecks are discussed. © 2015 IEEE.


Zavoianu A.-C.,Johannes Kepler University | Zavoianu A.-C.,ACCM Austrian Center of Competence in Mechatronics | Bramerdorfer G.,Johannes Kepler University | Bramerdorfer G.,ACCM Austrian Center of Competence in Mechatronics | And 7 more authors.
Engineering Applications of Artificial Intelligence | Year: 2013

Performance optimization of electrical drives implies a lot of degrees of freedom in the variation of design parameters, which in turn makes the process overly complex and sometimes impossible to handle for classical analytical optimization approaches. This, and the fact that multiple non-independent design parameter have to be optimized synchronously, makes a soft computing approach based on multi-objective evolutionary algorithms (MOEAs) a feasible alternative. In this paper, we describe the application of the well known Non-dominated Sorting Genetic Algorithm II (NSGA-II) in order to obtain high-quality Pareto-optimal solutions for three optimization scenarios. The nature of these scenarios requires the usage of fitness evaluation functions that rely on very time-intensive finite element (FE) simulations. The key and novel aspect of our optimization procedure is the on-the-fly automated creation of highly accurate and stable surrogate fitness functions based on artificial neural networks (ANNs). We employ these surrogate fitness functions in the middle and end parts of the NSGA-II run (→hybridization) in order to significantly reduce the very high computational effort required by the optimization process. The results show that by using this hybrid optimization procedure, the computation time of a single optimization run can be reduced by 46-72% while achieving Pareto-optimal solution sets with similar, or even slightly better, quality as those obtained when conducting NSGA-II runs that use FE simulations over the whole run-time of the optimization process. © 2013 Elsevier Ltd. All rights reserved.


Poltschak F.,Johannes Kepler University | Amrhein W.,Johannes Kepler University | Amrhein W.,ACCM Austrian Center of Competence in Mechatronics
SPEEDAM 2010 - International Symposium on Power Electronics, Electrical Drives, Automation and Motion | Year: 2010

Permanent magnet synchronous machines (PMSM) are getting increasingly more used in the area of fractional hp drives. Additionally the specifications often include the demand to control the motor sensorless. Many position sensorless control strategies that still work at low speed or standstill are based on the analysis of the inductance difference in the rotor oriented d- and q-coordinate system. While the influence of the rotor geometry on the inductance has been discussed a lot, the main objective of this paper is to investigate the influence of the winding system on the inductances and the inductance ratio between the d- and q-direction. This serves as a measure for the suitability of the motor for sensorless control. An analytical formula is presented to estimate the flux linkage between the phases as well as the inductance ratio. Both characteristics are verified with FE-analyses and sample measurements. © 2010 IEEE.


Poltschak F.,Johannes Kepler University | Amrhein W.,Johannes Kepler University | Amrhein W.,ACCM Austrian Center of Competence in Mechatronics
SPEEDAM 2010 - International Symposium on Power Electronics, Electrical Drives, Automation and Motion | Year: 2010

Sensorless control schemes that operate well even at low speeds or at standstill are mainly based on the evaluation of the machine saliences. Hence a sufficient inductance ratio independent of the rotor angle is essential for permanent magnet synchronous machine (PMSM) drives. This paper analyzes the origin of the angle dependence of the inductance ratio and shows that saturation has an important influence. In many cases saturation deteriorates the inductance ratio, but it can be shown that saturation can also be used to improve it. This is especially important for non-salient machines to make them suitable for sensorless control. The paper concludes with design guidelines to improve the inductance ratio for non-salient machines. © 2010 IEEE.


Bramerdorfer G.,Johannes Kepler University | Bramerdorfer G.,ACCM Austrian Center of Competence in Mechatronics | Jungmayr G.,Johannes Kepler University | Jungmayr G.,ACCM Austrian Center of Competence in Mechatronics | And 8 more authors.
SPEEDAM 2010 - International Symposium on Power Electronics, Electrical Drives, Automation and Motion | Year: 2010

Today magnetically levitated rotors are mainly used in applications where wearless operation and high life cycle are of importance (e.g. in the pharmaceutical, biomedical, chemical and semiconductor industry). The bearingless slice motor features a very compact design because three degrees of freedom (one translational and two rotatory) are passively stabilized by reluctance forces. Therefore, only two translational degrees of freedom remain to be actively controlled. This paper introduces a new bearingless segment motor (a subtype of the bearingless slice motor) featuring a Halbach magnet ring mounted on the rotor. Thus, no back iron is needed on the rotor and therefore the overall weight of the permanent magnet excited disc-shaped rotor is reduced to a minimum. The bearing forces which can be created by one optimized stator segment are calculated analytically. These results allow conclusions for the total force locus. A prototype is built and measurements verify the results of the analytic considerations. © 2010 IEEE.


Zavoianu A.-C.,Johannes Kepler University | Zavoianu A.-C.,ACCM Austrian Center of Competence in Mechatronics | Lughofer E.,Johannes Kepler University | Koppelstatter W.,ACCM Austrian Center of Competence in Mechatronics | And 7 more authors.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2013

This paper is focused on a comparative analysis of the performance of two master-slave parallelization methods, the basic generational scheme and the steady-state asynchronous scheme. Both can be used to improve the convergence speed of multi-objective evolutionary algorithms (MOEAs) that rely on time-intensive fitness evaluation functions. The importance of this work stems from the fact that a correct choice for one or the other parallelization method can lead to considerable speed improvements with regards to the overall duration of the optimization. Our main aim is to provide practitioners of MOEAs with a simple but effective method of deciding which master-slave parallelization option is better when dealing with a time-constrained optimization process. © 2013 Springer-Verlag.


Bramerdorfer G.,Johannes Kepler University | Bramerdorfer G.,ACCM Austrian Center of Competence in Mechatronics | Amrhein W.,Johannes Kepler University | Amrhein W.,ACCM Austrian Center of Competence in Mechatronics | And 2 more authors.
IECON Proceedings (Industrial Electronics Conference) | Year: 2013

Brushless permanent magnet machines (BPMMs) gained more importance due to the high power density ensured by permanent magnets with high energy densities. Therefore, a more compact design can be achieved compared to other types of electrical machines. © 2013 IEEE.


Bramerdorfer G.,Johannes Kepler University | Bramerdorfer G.,ACCM Austrian Center of Competence in Mechatronics | Silber S.,Johannes Kepler University | Silber S.,ACCM Austrian Center of Competence in Mechatronics | And 4 more authors.
Proceedings of the 2013 IEEE International Electric Machines and Drives Conference, IEMDC 2013 | Year: 2013

Due to the increasing significance of energy saving, multiple regulations have been introduced by countries or international organizations regarding the efficiency of electric drives, e.g. the IEC1 60034-30 [1]. In the past, many companies replaced induction machines (IMs) by permanet magnet excited synchronous machines (PMSMs). This lead to a considerable increase of the efficiency, but due to the fluctuating price of the permanent magnets, especially of Neodymium-Iron-Boron(NdFeB)-magnets, the cost of PMSMs is hardly predictable. Therefore, many manufacturers are investigating in synchronous reluctance machines (SyncRM) now. © 2013 IEEE.


Zavoianu A.-C.,Johannes Kepler University | Zavoianu A.-C.,ACCM Austrian Center of Competence in Mechatronics | Bramerdorfer G.,Johannes Kepler University | Bramerdorfer G.,ACCM Austrian Center of Competence in Mechatronics | And 7 more authors.
Advances in Intelligent Systems and Computing | Year: 2013

In this paper, we are applying a hybrid soft computing approach for optimizing the performance of electrical drives where many degrees of freedom are allowed in the variation of design parameters. The hybrid nature of our approach originates from the application of multi-objective evolutionary algorithms (MOEAs) to solve the complex optimization problems combined with the integration of non-linear mappings between design and target parameters. These mappings are based on artificial neural networks (ANNs) and they are used for the fitness evaluation of individuals (design parameter vectors). The mappings substitute very time-intensive finite element simulations during a large part of the optimization run. Empirical results show that this approach finally reduces the computation time for single runs from a few days to several hours while achieving Pareto fronts with a similar high quality. © 2013 Springer-Verlag.


Zavoianu A.-C.,Johannes Kepler University | Zavoianu A.-C.,ACCM Austrian Center of Competence in Mechatronics | Lughofer E.,Johannes Kepler University | Amrhein W.,Johannes Kepler University | And 3 more authors.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2013

We propose a 2-population cooperative coevolutionary optimization method that can efficiently solve multi-objective optimization problems as it successfully combines positive traits from classic multi-objective evolutionary algorithms and from newer optimization approaches that explore the concept of differential evolution. A key part of the algorithm lies in the proposed dual fitness sharing mechanism that is able to smoothly transfer information between the two coevolved populations without negatively impacting the independent evolutionary process behavior that characterizes each population. © 2013 Springer-Verlag Berlin Heidelberg.

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