This research provides a unique contribution to the field of in-wheel motor drive
(IWMD) 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 wheels’ rotational inertia,
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 motor’s vertical motion, 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 (model C). To assess the impact of
controlled vibration on dynamic performance, we compared the dynamic
characteristics of IWMD 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.
