Abstract: To investigate the impact of unbalanced electromagnetic forces(UEMFs) resulting from air gap eccentricity in in-wheel motors(IWMs) on vehicle vertical vibration and motor performance, this study proposes a novel calculation method for UEMFs based on a GA-BP neural network, developed in accordance with data-driven modeling theory. Taking into account the coupling between vehicle mechanical vibration and motor vibration, a comprehensive electromechanical coupling model for IWM-driven electric vehicles(EVs) that incorporates both road roughness and UEMFs is established. On this basis, the excitation characteristics and influencing factors of UEMFs is studied, a comparative analysis between the vertical vibration responses of vehicle suspension systems with and without UEMF excitation is conducted, the influence patterns of motor UEMFs on both vehicle dynamic performance and motor performance across various driving conditions is revealed, and correctness of the proposed model and the validity of analytical results are subsequently verified through bench tests. The results show that the UEMFs significantly deteriorates the vehicle ride comfort under acceleration/deceleration conditions, and the larger the acceleration/deceleration, the more obvious the deterioration. However, it has almost no effect on the vehicle dynamics under uniform speed conditions. The research findings establish a solid theoretical foundation for both the analysis and suppression of negative vibration effects of IWM-driven EVs.

Key words: IWM-driven EVs, unbalanced electromagnetic force, electromechanical coupling model, negative vibration effects, bench test