This research provides a unique contribution to the field of in-wheel motor drive electric vehicles (EVs) by addressing the challenges associated with the use of permanent magnet synchronous motors (PMSMs) for traction. These motors, integrated into the unsprung masses, increase the rotational inertia of the wheels, reducing ride smoothness on uneven roads. To mitigate this issue, we present an optimal Kalman filter for a magnetorheological (MR) control suspension system that correlates road inputs between the front and rear wheels. This filter significantly improves the estimation accuracy of state variables by incorporating the vertical motion of the motor, along with potential enhancements from wheelbase preview. To determine the most suitable coil spring types for use with MR dampers, we used the WDW-600 computer-controlled electronic universal testing machine to evaluate three coil spring types: constant pitch (model A), variable pitch (model B), and conical spring (model C). To assess the impact of controlled vibration on dynamic performance, we compared the dynamic characteristics of in-wheel motor drive EVs equipped with passive, uncorrelated, and correlated suspension systems, all of which have controlled inverters integrated into their design. The results indicate that motor vertical acceleration and dynamic tire load are the primary factors influencing the dynamic behavior of EVs. Additionally, the vehicle’s vibration performance metrics are negatively impacted by the in-wheel motor driving system in both passive and uncorrelated suspension systems. However, the MR-controlled suspension system with a conical spring significantly enhances ride comfort and dynamic stability by addressing complex stiffness and evaluating the effects of different coil spring types on the structural response of EVs. This analysis is based on a correlated suspension system scenario.
Gad et al. (Wed,) studied this question.