Research On The Algorithm Of The Road Friction Coefficient Estimatiom Based On The Extended Kalman Filter

Vehicle Stability control is a vehicle active safety devices that can adjust the movement of vehicles real-timely passing the vehicle control system. This can ensure that the vehicles travel in accordance with the intention of drivers, and to prevent vehicles instability. Vehicle Stability control is the international hot spots of automobile active safety research.Vehicle Stability Control system need access the state variables of the vehicle movement and parameters of variables real-timely, such as wheel speed, speed, acceleration, lateral angle of body center of mass, tire force and tire-road friction coefficient, yaw rate, and so on. Some of these variables or parameters can be measured by Car sensors directly, while others can't be measured because of the cost or the accuracy of measuring.With the development of the estimation theory, people have become more leaned to estimation algorithm to obtain state variables or parameters of these variables, becoming an effective way to access accurate vehicle information. This method can realize the vehicle stability control finally and improve the active safety.Based on the analysis of research status and development trends of the domestic and international road/tire coefficient, on the basis of estimated state vehicles variables, will research on the coefficient estimation algorithm based on the extended Kalman filter.The main task of this paper is as follows:(1) The theory and algorithms of Kalman filter have been studied in depth, and unbiased Estimation of recursive filtering method using the signal system on the use of state variables and parameters variableshave been summarized. Above this, the application of the extended Kalman filter theory have been researched and the optimal estimation of the state variables and parameters of the movement system of nonlinear have been described, and at the same time, the specific of the process have been showed. This laid the theoretical foundation for the next work to the use of extended Kalman filter for state estimation and parameter estimation.(2) Based on the nonlinear 3-DOF vehicle dynamics model, estimation algorithm of vehicles movement state on the using of vehicle sensor information have been studied and the extended Kalman state observer has been designed. The longitudinal,.lateral acceleration and yaw rate of the state of the vehicle can be estimated online. Vehicle state estimation algorithm in Matlab/imulink has been achieved,.and the vehicle state estimation algorithm has been experimental verificated passing the real vehicle test. The results proved that, the accuracy of the state of the vehicle movement based on the extended Kalman Filter. It establishes a firm basis for the estimation algorithm of road/tire coefficient in the next chapter.(3) Through the magic formula tire, the unitire model and the Dugoff tire model comparison and analysis, Dugoff tire model has been determined to applicate into the research of road/tire coefficient estimation algorithm,and the basic guarantee its accuracy requirements was satisfied by a group of empirical parameters.At the same time, a simulation verification of the tire Characteristics of the Dugoff tire model hae been made using the software CarSim7.0. A four vehicle dynamics model has been constructed, Road/tire coefficient estimation algorithm has been established based on the extended Kalman Filter, and achieved in Matlab/Simulink environment. (4) On the basis of the conclusion of the above study, a preliminary idea to combine vehicle state estimation algorithm and road/tire coefficient estimation algorithm based on the extended Kalman Filter into a complete estimation algorithm,therefore, using of a state vehicle signal to estimate road/tire coefficient, and the estimation algorithm has been achieved in the Matlab/imulink environment.Vehicle speed, yaw rate, road/tire coefficient of state estimation and parameters have been completed using CarSim7.0 in the high-adhesion, low attachment, docking, four off the road situation.The results show that simulation results are in good agreement, this fully explained the accuracy of the road/tire coefficient estimation algorithm based on the extended Kalman Filter.This paper has researched on the state of vehicles and road/tire coefficient estimation algorithm based on the extended Kalman filter theory. The real vehicle testing of the state estimate have been made. The simulation of road/tire coefficient estimation algorithm have been completed,all of the results have been fairly satisfied.It provides a new method for the vehicle state estimates and road/tire coefficient estimation.