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This paper proposes a torque tracking algorithm via steer by wire to achieve the target steering feel and proposed a modified friction model to obtain return-ability. A three dimensional reference steering wheel torque map is designed using the measurement data of the steering characteristics of the target vehicle at a transition test and a weave test. In order to track the reference steering wheel torque, a sliding mode control is used in the tracking algorithm. In addition, to achieve return-ability, the modified friction model for steer by wire is used instead of the friction model defined in the reference steering wheel torque map. The modified friction model is composed of various models according to the angular velocity. The angular velocity and the angular acceleration used in the control algorithm are estimated using a kalman filter.

This paper describes an optimal torque vectoring strategy for 4WD electric vehicles (EV) in order to improve vehicle maneuverability, lateral stability and at the same time prevent vehicle rollover. The 4WD EV is driven using an in-line motor at a front driving shaft and in-wheel motors at rear wheels. Many previous studies have been conducted to determine a desired traction force and a yaw moment input for human driver's intention or vehicle stability control. The driving control algorithm consists of three parts: a supervisory controller that determines the control mode, admissible control region, and desired dynamics, such as the desired speed and yaw rate, an upper-level controller that computes the traction force input and yaw moment input to track the desired dynamics and an optimal torque vectoring algorithm that determines actuator commands, such as the front in-line motor, rear in-wheel motors and independent brake modules.