Analysis and optimisation of a bearingless induction motor's suspension force and unbalanced magnetic pulling force mathematical model

摘要

Aiming at the problem that the two general mathematical models of suspension force and unbalanced magnetic pulling force (UMPF) are affected by the actual factors of a bearingless induction motor, a non-linear model fitting method is proposed. Firstly, by finite element method (FEM), the coupling influence of the torque winding and suspension winding is taken into account, and the maximum voltage of the latter is obtained. Secondly, considering the motor magnetic saturation and combing the least squares method (LSM), the suspension force is estimated by a binary function. Similarly, considering the magnetic saturation and cogging effect, the UMPF is estimated by a ternary function. Finally, comparing the fitting precision under different orders, the two functions with their smallest errors are obtained, and the two original linear models are optimised, respectively. The theoretical study and experimental results show that the motor based on the optimised non-linear model control system has a better suspension performance.