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A full drive-by-wire electric vehicle, named Urban Future Electric Vehicle (UFEV) is developed, where the four wheels' traction and braking torques, four wheels' steering angles, and four active suspensions (in the future) are controlled independently. It is an ideal platform to realize the optimal vehicle dynamics, the marginal-stability and the energy-efficient control, it is also a platform for studying the advanced chassis control methods and their applications. A centralized control system of hierarchical structure for UFEV is proposed, which consist of Sensor Layer, Identification and Estimation Layer, Objective Control Layer, Forces and Motion Distribution Layer, Executive Layer. In the Identification and Estimation Layer, identification model is established by utilizing neural network algorithms to identify the driver characteristics. Vehicle state estimation and road identification of UFEV based on EKF and Fuzzy Logic Control methods is also conducted in this layer.

Four-wheel independent control electric vehicle is a new type of x-by-wire EV with four wheels independent steering and four wheels independent drive/brake systems. In order to take full advantage of the vehicle's performance potential, this paper presents a novel integrated chassis control strategy. In the paper, the strategy is designed by the hierarchical control structure and divided into integrated control layer and allocation layer. By this method, the control logical can be modularized and simplified. In the integrated control layer, Model Prediction Control (MPC) is adopted to design the integrated control unit, which belongs to be a kind of local optimization algorithm with feedback correction features. Using this method could avoid the system performance degradation caused by the control model mismatch. The control allocation layer is to optimally distribute the vehicle control forces to the steering/driving/brake actuators on each wheel.

As a new form of electric vehicle, Four-wheel-independent electric vehicle with X-By-Wire (XBW) inherits all the advantages of in-wheel motor drive electric vehicles. The vehicle steering system is liberated from traditional mechanical steering mechanism and forms an advanced vehicle with all- wheel independent driving, braking and steering. Compared with conventional vehicles, it has more controllable degrees of freedom. The design of the integrated vehicle dynamics control systems helps to achieve the steering, driving and braking coordinated control and improves the vehicle's handling stability. In order to solve the problem of lacking of vehicle state information in the integrated control, some methods are used to estimate the vehicle state of four-wheel-independent electric vehicles with XBW. In order to improve the estimation accuracy, unscented Kalman filter (UKF) is used to estimate the vehicle state variables in this paper.