Robust uncertainty modelling of energy variations in electric motors for efficient and reliable mechanical structural analysis

Robust uncertainty modelling of energy variations in electric motors for efficient and reliable mechanical structural analysis

The mechanical power and rotational speed of electric motors have significantly uncertainties arising from energy variations such as the magnetic energy, the flux linkage variation of the winding, and the air gap due to the rotor position. The main aim of this work is to address the effect of the uncertain output power and rotational speed of an electric motor on mechanical structural analysis, especially on the torsional analysis, and accordingly to model the statistical characteristics of variations in torque of the motors in consideration of different powers and speeds for further efficient and reliable mechanical structural analysis under uncertainty. To perform these tasks, a case study that is the torsional loading of a shaft by an electric motor and generator, is carried out. The results show that the uncertainty of power and speed in electric motors considerably affects the probability of failure of the shaft in case of exceeding the maximum shear stress, and increasing the speed at a given power does not significantly change the COV value of the torque whereas increasing the power at a given speed can relatively change the COV value of the torque. The obtained average of the COV values (0.0023) of torque with normal distribution is fairly sufficient for indicating the variations in the torque of electric motors. Moreover, the obtained torque uncertainty can be easily and efficiently used in the mechanical structural analysis under both deterministic and stochastic cases.

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