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This paper introduces the characteristics of the 4 wheel independent driving/4 wheel independent steering (4WID/4WIS) electric vehicle (EV). Models of Subsystems and the vehicle are constructed based on Matlab/simulink. The vehicle model allows the inputs of different drive torques and steer angles of four wheels. The dynamic characteristics of drive motors and steer motors are considered, and also it can reflect the vehicle longitudinal dynamics change due to the increase of the mass and inertia of the four wheels. Besides, drive mode selection function that is unique to this type vehicle is involved. Simulations and analyses of crab, oblique driving and zero radius turning which are the special conditions of 4WID/4WIS EV are conducted. The results show that the model can reflect the dynamic response characteristics. The model can be used to the simulation analyses of handling, stability, energy saving and control strategies verification of 4WID/4WIS EVs.

The EPS motor will be over-heated if large current lasts for a long time, which will decline the performance of EPS motor and even lead to irreparable damage. So the over-temperature protection control should be conducted in order to protect the components of EPS system, especially the durability of EPS motor. In this paper, the motor temperature was estimated according to the environmental temperature and the current of motor armature, and then the EPS assist current was limited based on the estimated temperature of motor to ensure that the EPS motor had a good working condition. So the over-temperature protection control for motor can be realized without increasing the EPS system components. Finally the control strategy for over-temperature protection was conducted in a vehicle with EPS system and its performance was verified.

A fault tolerant control (FTC) approach based on reconfigurable control allocation for four-wheel independently driven and steered (4WID/4WIS) electric vehicles against driving motor failures is proposed in order to improve vehicle safety, performance and maneuverability after the driving motor failures. The proposed fault tolerant control method consists of the following three parts: 1) a fault detection and diagnosis (FDD) module that monitors vehicle driving condition, detects and diagnoses actuator failures; 2) a motion controller that computes the generalized forces/moments to track the desired vehicle motion using model predictive control method; 3) a reconfigurable control allocator that optimally distributes the generalized forces/moments to four wheels aiming at minimizing the total tire usage. The FTC approach is based on the reconfigurable control allocation which reallocates the generalized forces/moments among healthy actuators once the actuator failures is detected.

With rapid development of the automobile industry and the growing maturity of the automotive electronic technologies, the distributed-traction electric vehicle with four-wheel-distributed steering/braking/traction systems is regarded as an important development direction. With its unique chassis structure, it is the ideal benchmark platform used to evaluate active safety systems. The distributed-traction electric vehicle with four-wheel-distributed steering system is essentially full drive-by-wire vehicle. With its flexible chassis layout and high control degrees-of-freedom, the full drive-by-wire electric vehicle acted as a kind of redundant system is an ideal platform for the research of integrated control. In this treatise, the longitudinal dynamics of the electric vehicle as well as its lateral and yaw motions are controlled simultaneously.

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.

On-center handling has drawn lots of attention from consumers and car manufactures for its extraordinarily large effect on vehicle security at high speed. So far, there are a large number of objective evaluation indices for on-center handling, but it is not clear which ones are the key points on evaluation indices. In this paper, the authors propose a simplified on-center handling objective evaluation index system. Firstly, a basic on-center handling objective evaluation index system is summarized based on the ones of ISO, GM, MIRA, TRC and Hyundai, and then dynamics analysis on each index is conducted so as to primarily eliminate the redundant indices. Secondly, the repetitive indices are cut out again by the correlation analysis among indices in objective tests for eight types of vehicles. Thirdly, the importance factor of each subjective evaluation index is gained on the basis of subjective evaluation tests for eight types of vehicles by the weighed principal component analysis.

Omni-directional electric vehicle built by our research group is an advanced electric vehicle whose four wheels can drive, steer and brake independently. The vehicle chassis system is composed of four in-wheel motors, four independent steer motors and electromagnetic brake system, and its control system is divided into logical control layer and underlying execution layer. The information exchange between these two layers is implemented by CAN bus. In this paper, the traction control logic for Omni-directional electric vehicle is developed. The study mainly involves two aspects: the vehicle states estimation and the traction control logic design. The vehicle states, including vehicle longitudinal velocity, lateral speed, side slip angle and yaw rate, etc, are estimated based on Extended Kalman Estimation and multiple degrees of freedom vehicle model.