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.
