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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.

This paper sets up a simplified dynamic model for simulating the yaw/roll stability of heavy tractor-semitrailer using Matlab/Simulink. A linear quadratic regulator (LQR) based on partial-state feedback controller is used to optimize the roll stability of the vehicle. The control objective for optimizing roll stability is to be reducing the lateral load transfer rate while keeping the suspension angle less than the maximum allowable angle. The simulation result shows that the LQR controller is effective in the active roll stability control of the heavy tractor-semitrailer.

This paper presents a study on steering effort preference of Chinese drivers based on ADSL Driving Simulator. The results of the simulation test demonstrates that Chinese drivers' steering effort preference increases with vehicle speed, which is similar to European and Japanese drivers', but the mean preference effort level itself is lower than that of European and Japanese drivers' and this same steering effort preference increases obviously with lateral acceleration in linear region (lateral acceleration level lower than 0.3g) while not as evidently in nonlinear region (lateral acceleration level higher than 0.3g).

The research of driver behavior characteristics has been a focus of vehicle handling and stability performance. With the driver preview effort, many different driver preview models of direction control have been proposed and the simulations of driver-vehicle-road closed-loop system made. But in the simulation, most of the conventional models have the same precondition that the road was simply described as a pre-given preview course. How to simulate the driver dynamically deciding vehicle preview course based on the real road circumstance is the key to the further research of the driver model. In this paper, a new driver direction control model is established, which is called the Optimal Preview Lateral Acceleration (OPLA) Model and divided into three sub-models: driver’s information identification model, driver’s fuzzy decision model of vehicle preview course and driver’s performance first-order correction model.

A closed-loop comprehensive evaluation and a test method for vehicle handling and stability have been studied by using development driving simulator. Simulator test scheme has been designed and carried out with 14 vehicle configurations, and subjective evaluation has been made for easy handling of vehicle by drivers. A closed-loop comprehensive evaluation index has been put forward considering the factors affecting vehicle handling and stability. The reliability of the index has been validated by driver's subjective evaluation. A driver/vehicle/ road closed-loop system model has been established, and the theoretical predictive evaluation has been carried out with 14 vehicle configurations. Simulation showed that similar result for both theoretical predictive evaluation and subjective evaluation.