Improved Mathematical Modeling of Six Phase Induction Machines Based on Fractional Calculus

Multiphase induction machine modelling represents a crucial research topic for both machine control and performance evaluation purposes. Generally, multiphase induction machines are preferably modelled using the vector space decomposition technique with some assumptions to simplify the mathematical model. However, different sources of non-linearities, including low order harmonics mapped to secondary subspaces, cross-coupling saturation and iron losses result in a notable deviation from the experimentally measured waveforms. Furthermore, considering full symmetry amongst motors phases seems to be a rather idealistic assumption. Fractional order modelling has recently emerged as a promising mathematical technique to model highly nonlinear electrical and mechanical systems. This paper proposes an improved vector space decomposition (VSD)-based fractional order model of an asymmetrical six-phase induction machine under both healthy and open phase fault conditions with different neutral arrangements. The appropriate differentiation orders have been obtained by optimizing the error function between simulated and experimental waveforms. The results are compared with the conventional integral order-based model. Experimental validation has been carried out using a 1.5Hp prototype induction machine.

Automated summary

Studying multiphase induction machine modelling is crucial for machine control and performance evaluation. This research proposes an improved vector space decomposition (VSD)-based fractional order model for an asymmetrical six-phase induction machine under different fault conditions, optimizing differentiation orders through error function and comparing with conventional models.