Modeling of Inductances Considering Bar Harmonics and Temperature to Accurately Predict Output Torque of an Induction Motor

Equivalent circuit parameters of an induction motor are highly susceptible to various undesired factors. These phenomena primarily include effects of higher order time and space harmonics, temperature, magnetic saturation, and skin-effect. Traditional approaches model these equivalent circuit parameters via temperature, iron saturation, and slotting effects. However, the impacts of harmonic fields generated by the spatial magnetomotive force components as well as that of skin effect in motor inductances are not considered. The proposed work therefore presents an improved inductance estimation considering the impact of total harmonic distortion in the magnetomotive force with a power function-based formulation. Since the induction motor performance is sensitive to its rotor circuit parameters, another realistic variation taken up in this work includes the impact of iron saturation, and skin effect altogether on rotor leakage inductance and rotor bar resistance. Additionally, the effects of non-linearity, such as temperature variations, are incorporated into the magnetizing inductance, while the permeance of rotor tooth-bridge segments is considered in the rotor leakage inductance and bar resistance. The effectiveness of the proposed model is demonstrated with simulation and experimental results of a 13 kW three-phase induction motor prototype for a wide range of operations. This method significantly improves the modelling of inductances, enhancing the accuracy of the electromagnetic torque predictions over a wide range of operating speeds. Achieving net-zero carbon emissions is crucial for transportation electrification, which necessitates the use of high-speed traction motors in electric vehicles that require a reliable design. Therefore, an improved method is proposed that effectively captures the non-linear effects in predicting the parameters and performance including the output torque of the machine.