  Adverse road conditions can cause vehicle yaw instability and loss of
traction. To compensate for the instability under such conditions, corrective
actions must be taken. In comparison to a mechanical differential, an
electronic differential can independently control the two drive wheels and
provide means of generating more effective corrective actions. As a solution
for traction and stability issues in automobiles, this study has developed a
controller for a vehicle electronic differential consisting of two
program-controlled rear motors. The control algorithm adjusts to changing road
conditions. Traction was controlled using a motor reaction torque
observer-based slip ratio estimation, and yaw stability was achieved by
tracking a reference yaw rate calculated using estimated tyre cornering
stiffnesses. A recursive least squares algorithm was used to estimate cornering
stiffness. The yaw rate of the vehicle, as well as its longitudinal and lateral
accelerations, were measured, and the body slip angle was estimated using an
observer. A fuzzy inference system was used to integrate the independently
developed traction control and yaw control schemes. The fuzzy inference system
modifies the commanded voltage generated by the driver's input to account for
the traction and yaw stability controller outputs. A vehicle simulator was used
to numerically simulate the integrated controller. For the racetrack
simulation, the root-mean-square slip ratio error reduced by 96.14% and the RMS
yaw rate error reduced by 88.17%. For the double lane change test at 40 km/h
and 100 km/h, the RMS yaw rate error reduced by 86.96% and 92.34%,
respectively.
