Road Adhesion Coefficient Estimation Based On Distributed Drive Electric Vehicle

In recent years,the energy shortage and environmental pollution caused by traditional automobiles have become more and more obvious,and people gradually pay attention to the impact of the environment.With the advantages of 'environmental protection' and 'energy saving',electric vehicles have become the development trend of automobiles in recent years under the support of national policies.In the environment of poor road adhesion conditions,the driver's inadequate judgment of the road surface can easily lead to vehicle roll or even traffic accidents.In order to reduce these kind of accidents,active safety system of automobiles has become an inevitable trend of development.The road surface adhesion coefficient has an important impact on vehicle driving safety,which can directly be fonund on the information of the contact surface.It is an important factor to be considered in vehicle stability control and active safety control.Four-wheel hub-driven electric vehicle is driven by hub motor.It has the advantages of compact structure,short transmission chain and independent and controllable driving wheel,which makes it an ideal carrier for obtaining road adhesion coefficient,and can effectively improve the performance of active safety control system.Therefore,it is of great practical significance to accurately estimate the road adhesion coefficient on the four-wheel hub-driven electric vehicle.The specific research content of this paper are as follows:1.A adjustable wheel hub motor control system,tire force correction function model and nonlinear vehicle dynamics model in Matlab/Simulink environment were built.The four-wheel drive Carsim/Simulink co-simulated electric vehicle platform was built,through the joint business software Carsim interface setting.2.Based on the unscented Kalman filter theory,the exponential weighted attenuation factor and the noise estimator were designed to optimize and improve the algorithm.The road surface adhesion coefficient observer is designed.In the built four-wheel drive Carsim/Simulink co-simulated electric vehicle platform,different vehicle driving conditions were set up for simulation verification.3.A domestic electric vehicle was retrofit with a hub motor,build related data acquisition system hardware.The road vehicle adhesion coefficient real vehicle experiment was designed.The feasibility of the algorithm is verified by comparing the estimated values of the unscented Kalman filter observer,the adaptive fading unscented Kalman filter observer and the road surface adhesion coefficient under braking conditions.The conclusion shows that the established four-wheel drive Carsim/Simulink co-simulated electric vehicle platform can provide a more accurate estimation model.The adaptive fading unscented Kalman filter observer can estimate the road surface adhesion coefficient in real time and accurately.It has strong robustness and and high estimation accuracy.