Rub-impact is a critical failure mode in high-speed rotor systems that heavily complicates fault diagnosis. While traditionally studied in aero-engines due to its severe risks of blade damage and thermal-induced rotor instability, rub-impact has increasingly emerged as a crucial concern in modern electric vehicle (EV) traction motors characterized by high speeds, slender shafts, and ultra-narrow rotor–stator air gaps. Since rub-impact rarely occurs in isolation, this study establishes a dynamic model of an EV motor rotor system experiencing compound rub-impact and bearing faults based on Jeffcott rotor theory and the lumped-mass method. The influences of key fault parameters on system dynamics are comprehensively investigated through analyses of time histories, phase trajectories, Poincaré sections, frequency spectra, and envelope spectra. The results show that increasing the rub-impact stiffness (from 1.0 × 1010 N/m to 3.0 × 1010 N/m) significantly enhances the non-linear impulsive behavior of the system while reducing the rotor unbalance vibration amplitude by 20.0%. Under compound fault conditions with a local bearing defect width of 3 mm, the disk response is mainly governed by global rub-impact behavior, whereas the bearing-end response is more sensitive to local bearing defects. Under compound fault conditions, although widening the localized bearing defect (from 1 mm to 3 mm) significantly exacerbates the local fault severity at the bearing end, the disk’s phase trajectories, Poincaré maps, and spectra remain virtually uninfluenced. This is attributed to the fact that the relative signature intensity of the bearing fault characteristic frequency fi attenuates by more than 99% during structural transmission, causing the global non-linear dynamics of the rotor disk to be exclusively governed by global rub-impact behavior and completely insensitive to the localized defect propagation. These quantitative findings provide a precise theoretical basis for the diagnosis and identification of compound faults in rotor systems.
Liu et al. (Wed,) studied this question.