A polynomial chaos meta-model for non-linear stochastic magnet variations
Purpose - Due to the production process, arc segment magnets with radial magnetization for surface-mounted permanent-magnet synchronous machines (PMSM) can exhibit a deviation from the intended ideal, radial directed magnetization. In such cases, the resulting air gap field may show spatial variations in angle and absolute value of the flux-density. For this purpose, this paper aims to create and evaluate a stochastic magnet model. Design/methodology/approach - In this paper, a polynomial chaos meta-model approach, extracted from a finite element model, is compared to a direct sampling approach. Both approaches are evaluated using Monte-Carlo simulation for the calculation of the flux-density above one sole magnet surface. Findings - The used approach allows representing the flux-density's variations in terms of the magnet's stochastic input variations, which is not possible with pure Monte-Carlo simulation. Furthermore, the resulting polynomial-chaos meta-model can be used to accelerate the calculation of error probabilities for a given limit state function by a factor of ten. Research limitations/implications - Due to epistemic uncertainty magnet variations are assumed to be purely Gaussian distributed. Originality/value - The comparison of both approaches verifies the assumption that the polynomial chaos meta-model of the magnets will be applicable for a complete machine simulation.
stochastics magnet variations magnetism finite element method monte carlo simulation manufacturing tolerances magnetic flux-density deviations monte carlo methods manufacturing systems