An Efficient Design Optimization Framework for Nonlinear Switched Reluctance Machines

Abstract

The tubular linear SR machines were successfully tested in medical applications as artificial heart pump actuators [12].However, analysis and design of SR machines is a complex task compounded by their non-linear behavior. Despite some effort [13] the analysis and design calculations have not yet been developed into intuitive analytical tools comparable to the methods available for the more established types of machines, such as induction or permanent magnet. The main difficulty with the analysis and design of SR machines is the magnetic nonlinearity caused by the heavily saturated iron parts of the machine circuit. The non-saturating SR machines, as used in some niche applications, are not considered here.Given the wide variety of topological arrangements of SR machines, which is expected to grow in the future as the demand for the new applications increases [14], it is vital to establish computationally efficient analysis and design methods. The aim is to make the design task more systematic which in turn will open new application areas for the versatile SR electric machine technology.Reduced order computational methods, the most notable example being the magnetic equivalent circuit (MEC) approach, have been successfully employed in the past to various types of electric machines [15]. The main advantage of the MEC based models is that they are relatively accurate given their computational efficiency. The finite element analysis (FEA) is very useful for accurate analysis of the established electric machine technologies, but it does not offer the cause-and-effect insight when novel and unfamiliar machine topologies are being considered [16]. Therefore, bearing in mind the advantages of the MEC based analysis methods, the design cycle is proposed as illustrated in Fig. 1.The starting point (red rim) in Fig. 1 is where a novel topology SR machine is identified and considered for a certain application because it meets some particular requirements imposed by the application, for example: cost, volume and mass, mechanical, etc. Next, the improved flux tube based method [17], [18], which we propose in this paper, is employed to construct the electromagnetic model of the machine and is subsequently used in conjunction with a design search and optimization algorithm, e.g. the genetic algorithm (GA) [19]. Once a set of near optimal solutions

Rapid multi‐objective design optimisation of switched reluctance motors exploiting magnetic flux tubes

“…Assuming less than ideal parallel speedup of only 1.8 times, rather than 2.0, the average FEM solution time was approximately 252s -thus achieving at least six times the speedup with the flux tube based method compared to the FEM based solution. The speedup result is consistent with the previously undertaken flux tubes based GA optimization [15]. Further advantage of using flux tubes based optimization is that the requirement for extensive computing software and hardware is minimal as the method can be implemented with any modern computer scripting language such as Octave [22].…”

“…where π denotes an error introduced due to the uncertainties in the magnetization data of the magnetically nonlinear material [15], which can be in the region of ±10% as typically found in laboratory measurements and λ denotes an average error for the flux tube lengths, as in (5).…”

“…This paper proposes to improve the efficiency of analysis and design optimization of the radial flux SR machine by adapting the improved reduced order computational method of flux tubes. The flux tube methodwhich has already been successfully applied to translating SR machines as reported in [14] and [15] -complements and enhances the hierarchical design paradigm of Fig. 1 by reducing the need for hard choice between solution time and accuracy early on in the design process, while still allowing to arrive at a near-optimal design.…”

Average Rated Torque Calculations for Switched Reluctance Machines Based on Vector Analysis

“…Therefore, for each required torque value at the fixed constant speed, an exhaustive search for the combination of the three control parameters will have to be performed, that is, the turn-on, the commutation, and the phase current magnitude. This type of search is effective only with the help of computer-based design routines; for example, see [8,10]. Figure 13 also shows the torque obtained from Eq.…”

Modified grey wolf method for optimization of PM motors

“…The final solution of the optimization process should fulfil imposed requirements regarding functional parameters of designed object. The optimality criteria are usually of economic type or are related to natural environment protection [1]. Very often the optimization task consists in limitation of the energy consumption and improvement of the device efficiency.…”