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