Four Wheel Independent Drive Electric Vehicle Lateral Stability Control Strategy

In this paper,a kind of lateral stability control strategy is put forward about the four wheel independent drive electric vehicle.The design of control system adopts hierarchical structure.Unlike the previous control strategy,this paper introduces a method which is the combination of sliding mode control and optimal allocation algorithm.According to the driver’s operation commands(steering angle and speed),the steady state responses of the sideslip angle and yaw rate are obtained.Based on this,the reference model is built.Upper controller adopts the sliding mode control principle to obtain the desired yawing moment demand.Lower controller is designed to satisfy the desired yawing moment demand by optimal allocation of the tire longitudinal forces.Firstly,the optimization goal is built to minimize the actuator cost.Secondly,the weighted least-square method is used to design the tire longitudinal forces optimization distribution strategy under the constraint conditions of actuator and the friction oval.Beyond that,when the optimal allocation algorithm is not applied,a method of axial load ratio distribution is adopted.Finally,Car Sim associated with Simulink simulation experiments are designed under the conditions of different velocities and different pavements.The simulation results show that the control strategy designed in this paper has a good following effect comparing with the reference model and the sideslip angle is controlled within a small rang at the same time.Beyond that,based on the optimal distribution mode,the electromagnetic torque phase of each wheel can follow the trend of the vertical force of the tire,which shows the effectiveness of the optimal distribution algorithm.

Multi-objective Optimization of Differential Steering System of Electric Vehicle with Motorized Wheels

A differential steering system is presented for electric vehicle with motorized wheels and a dynamic model of three-freedom car is built.Based on these models,the quantitative expressions of the road feel,sensitivity,and operation stability of the steering are derived.Then,according to the features of multi-constrained optimization of multi-objective function,a multi-island genetic algorithm(MIGA)is designed.Taking the road feel and the sensitivity of the steering as optimization objectives and the operation stability of the steering as a constraint,the system parameters are optimized.The simulation results show that the system optimized with MIGA can improve the steering road feel,and guarantee the operation stability and steering sensibility.

IN SlTU TRUING/DRESSING OF DIAMOND WHEEL FOR PRECISION GRINDING

An application for achieving on-machine truing/dressing and monitoring of diamond wheel is dealt with in dry grinding. A dry electrical discharge （ED） assisted truing and dressing method is adopted in preparation of diamond grinding wheels. Effective and precise truing/dressing of a diamond wheel is carried out on a CNC curve grinding machine by utilizing an ED assisted diamond dresser. The dressed wheel is monitored online by a CCD vision system. It detects the topography changes of a wheel surface. The wear condition is evaluated by analyzing the edge deviation of a wheel image. The benefits of the proposed methods are confirmed by the grinding experiments. The designed truing/dressing device has high material removal rate, low dresser wear, and hence guarantees a desired wheel surface. Real-time monitoring of the wheel profile facilitates determining the optimum dressing amount, dressing interval, and the compensation error.