Search Results

A new concept electric vehicle (EV) with four-in-wheel motor is developed to make EVs spread widely. Each motor is mounted inside a wheel and can be controlled individually. The batteries and electrical components are placed in the hollow space of frame structure under the seats. Such a compact configuration permits packaging flexibility by eliminating the central drive motor and driveline components, including the transmission, the mechanical differential, the universal joints and the drive shaft. Apart from many mechanical advantages of such a structure, high performances of chassis control systems such as traction control, electronic differential control, direct yaw moment control and regenerative braking control systems are employed due to the rapid response and precise torque control of the motor. Simulation is conducted in ADVISOR and Matlab/Simulink environment.

For a semi-active suspension design, an important subject is to determine the control law which can achieve good performance both in ride and handling performance. Because of its superiority in non-linear control systems and capability of learning on-line, the fuzzy neural networks (FNNs) control scheme is proposed in this paper for a semi-active suspension system with dynamic absorber. The quarter vehicle model is described by a nonlinear system with three DOF subject to irregular excitation from a road surface and FNNs control scheme is employed. The on-line learning of FNNs to optimize fuzzy inference system is presented. Four kinds of methods, including passive suspension respectively with and without dynamic absorber, semi-active suspension respectively using fuzzy control and FNNs control, are investigated by computer simulation and comparison is made.