A high-performance computing procedure for the evaluation of 3D coils inductance

Abstract

Purpose – Inductances of complex coils, in the presence of linear materials only, can be computed by discretizing coils into simpler elements, whose magnetic behavior is analytically expressible, and suitably combining elementary contributions. Reliable results require high numbers of elements. In such cases, advantages can be taken from Graphic Processor Unit (GPU) capabilities of dealing efficiently with high numbers of repeated simple computational tasks. The purpose of this paper is to set up a fast and prompt numerical procedure to cope with the above described task. Design/methodology/approach – The coils are first decomposed into current segments, taking into account accuracy, relative position and shape of coils to determine the number of segments. An analytical formula is then used to compute elementary contributions using GPUs to speed up the process, and finally superposition is used to recover the result. Findings – The main advantages of the proposed approach are first demonstrated using simple examples, with analytical solutions, to validate the method accuracy and promptness, then more complex cases are taken to demonstrate its generality. Research limitations/implications – The method is intrinsically limited by the linearity assumption, excluding the presence of magnetic materials. The adopted formulas require in addition that coils must lie in free space. Practical implications – The proposed method can help in the design of complex coils or coils systems, where the performance depends on total magnetic energy or magnetic forces among coils. Originality/value – The paper presents an original implementation in GPU-based computational environment of a procedure to compute inductances, based on the superposition of a high number of current segments. The procedure includes an original method to self-adaptively define number and position of current segments used in the coils discretization.