Study On Soft Measurement And Handing Stability Control System For Four In-wheel Motors EV

Gasoline and diesel are the main fuel of the traditional vehicle. The demand of oil products is increasing sharply with the increasing prosperity of the world economy. Oil reserves and production capacity are more and more unable to meet the growing consumer demand. The traditional vehicle is facing the energy crisis. Oil products burns in the internal combustion engine of the traditional vehicle. Exhaust emission system can exhaust a lot of poisonous and harmful gas. The environmental is polluted. The greenhouse effect is increased at the same time. The traditional vehicle is facing the environmental crisis. The researchers have designed and developed various types of electric vehicles to make the vehicles drived by the green energy. In-wheel motor electric vehicle is provided power by the in-wheel motor which can be independently controlled. Some mechanical components of the traditional vehicle arc cancelled, such as engine, clutch, transmission, transmission shaft, differential and the main reducer. Both the power supply and the power transmission are completed by the in-wheel motor. The in-wheel motor vehicle has its own vehicle dynamic characteristics due to the difference of mechanical structure. The precision controllability and quick response of the in-wheel motor can help to control the tire force. Active braking control is adopted in the traditional vehicle handling stability control. The in-wheel motor vehicle adopts the motor vector control or it is combined with hydraulic brake control. The control method and control system structure have difference between the in-wheel motor vehicle and the traditional vehicle. The vehicle state parameters and the road adhesion coefficient have direct influence on the control effect of the handling stability. Rapid acquisition of accurate state parameters and road adhesion coefficient is the prerequisites for handling stability control. Some vehicle state parameters can be directly measured by sensors and other physical devices. Some slate parameters and the road adhesion coefficient can not be directly measured due to the lack of relevant sensing devices or the high cost. Soft measurement technology is needed to measure the parameters and coefficients which can not be measured directly. Based on the above reasons, it is necessary to research on the soft measurement method and the handling stability control system for the in-wheel motor electric vehicle.The soft measurement method and the handling stability control system were researched in this article, which was for the four in-wheels independent drive electric vehicle. The research on soft measurement method was mainly aimed to the application of the improved UKF (Unscented Kalman Filter) algorithm. A combined estimation method was designed for the vehicle state parameters and the road adhesion coefficient. The research on the handling stabilily control system was mainly aimed to the application of the improved dynamic surface sliding mode control method. A stability control system and a handling control system were designed.The scaled correction frame and the minimal skew simplex sampling were combined, which formed the scaled minimal skew simplex sampling strategy for the improved UKF to sample the Sigma points. The virtual noise and the Sage-IIusa time varying noise estimator were introduced to the improved UKF, which was aimed to reduce the model linearization error and enhance the adaptive performance of the estimation algorithm. After equivalent transformation, the lading factor was introduced to the improved UKF, which was aimed to enhance the strong tracking ability of the estimation algorithm. By these improvements, the improved UKF was the improved scaled minimal skew simplex UKF (ISMSS-UKF) algorithm. Based on the ISMSS-UKF algorithm and a three degree of freedom vehicle state space model, a combined estimation method was designed. The combined estimation method included the vehicle state estimation and the vehicle parameter estimation. The vehicle state included speed, acceleration, yaw velocity and sideslip angle. The vehicle parameter was the road adhesion coefficient. Based on MATLAB/Simulink and Carsim joint simulation platform, simulation experiments were made. One simulation experiment was a sinusoidal sleering input running condition with high road adhesion coefficient. The other simulation experiment was a double lane change running condition with low road adhesion coefficient. The experimental results showed that the adaptive performance and the strong tracking ability of the ISMSS-UKF algorithm were enhanced.The handling stability control system was based on the concept of hierarchical design. It included signal processing layer, management layer, direct yaw moment control layer and executive layer. In the direct yaw moment control layer, two control systems were designed based on stability and handling. The direct yaw moment controller and distributor were designed in the control systems. Exponential approach law, dynamic surface sliding mode control and function substitution were combined to improve dynamic sliding mode control method. That was aimed to eliminate the chattering and enhance the anti-interferenee performance. The stability direct yaw moment controller controlled the demand direct yaw moment by the improved dynamic sliding mode control method. The object function of the stability direct yaw moment distributor was the minimum road adhesion consumption. The handling direct yaw moment controller was based on the feedforward and feedback control method. The object function of the handling direct yaw moment distributor was the fastest motor response. Using the elimination method, the object function was solved.A dynamic vehicle model and an AMESim vehicle model were made for the four in-wheel motors electric vehicle.Hardware in the loop test platform was made based on dSPACE, computer, hydraulic braking system and driver system. The simulation experiments and the hardware in the loop tests were made. The experiments and the tests included sinusoidal steering input, double lane change and sine increment running conditions. The results showed that the handling stability control system worked well.