Improved Winding Function Based Model for Analytical Estimation of Stray Load Loss in Traction Induction Machines

The automotive industry's progressive adoption of electric vehicles (EVs), including small-scale EVs, in response to the traction electrification trend has created a surge in demand for high-performance electric motors. While induction machines (IMs) are viable options for small EVs due to their higher durability and lower cost, it is essential to address their predominant drawback of lower efficiency. Therefore, to ensure optimal performance of traction IMs, it is crucial to account for the typically overlooked yet critically important stray load loss caused by space and time harmonics introduced by pulse-width modulation (PWM) inverters in traction drive systems during their initial design stages. To meet the need for a computationally efficient stray load loss model, this paper introduces an improved winding function based (IWFB) model that provides an analytical estimation of stray load loss in traction IMs. The proposed IWFB stray load loss model integrates considerations of space harmonics, time harmonics, dynamics of rotor magneto-motive force effects, and frequency-dependent magnetic characteristics of core materials to estimate the time variation of flux densities in predetermined core regions, enabling accurate estimation of the stray load loss in the inverter-fed IMs. The proposed IWFB stray load loss model is validated through experimentation using an 11 kW prototype traction IM, demonstrating an accuracy of 95.7% and an average computational time of 18.5 minutes.