The Estimation Of Vehicle Speed Based On Moving Horizon Estimation

With the booming of the private car, the safety of the vehicle has become a hot issue.The safety of the Vehicle depends on its stability.So it is very important to keep the vehicle's stability. Vehicle Stability Control (VSC) is such an active safety device, which lets the vehicle run following the driver's intension to prevent vehicle from losing stability. Now, VSC is an international research focus in the vehicle active safety field. With the development of control techniques and decrease of control system cost, VSC will replace ABS to be the standard device of modern vehicles. The state variables and enviroment parameters about the movement of vehicle are needed for the VSC system. Some of these variables or parameters can be measured directly, such as wheel speed, acceleration, brake pressure and so on. But for some other parameters which are hard to measure and the large cost of the measure device, it is not wise to use device to measure them. These kinds of parameters include vehicle body silp angle, lateral velocity, tire force and so on. With the development of the estimation theory, more and more scholars would like to get these state variables and parameters through estimation.The dissertation pays attention to velocity estimation of vehicle based on the classic manoeuvre. Moving Horizon Estimation (MHE) method is used to estimate the velocity of the vehicle.The research concentrates on the realization of using MHE to estimate the vehicle speed. The details of realizing have been given and severals tests have been used to see the estimation results.In this paper, the following tasks have been done:1.Build vehicle model Accroding to Prof.Guo Konghui's tire theory and the 8-DOF vehicle model provided by vehicle department, set up the 8-DOF vehicle model in MATLAB with Simulink and consider some of its outputs to be the inputs of the estimation part.2.Design the estimation partAccroding to 7-DOF vehicle model and Dugoff tire model, set up the state model with vehicle speed and friction coefficient, and change it to a certain disceate type which is suitable to use for MHE. Put forward the contraints of the vehicle speed and friction coefficent inorder to get more reasonable and accurate results.3.Experiment vadilationBased on nonlinear, discreate state model that has changed before, analyze the MHE method, and to find out how to use it in the estimation of vehicle speed.Write the program and adjust several parameters to get the optimum results, with several classic inputs to do some simulations to test MHE's estimation results. Besides, the friction coefficient and longitude acceleration's estamation value have been acquired. Through the estimation of vehicle speed based on MHE method and the simulation results, the conclusions are as follows:1.MHE is a good method to estiamate the state with constaints, and the research results in this paper prove the MHE's priority to deal with the estimation questions with constraints invovled.2.Although MHE shows the ceratin results for estimating the vehicle speed, there are still some parts which need to be improved. For example, the chosen of the parameters. There are so many parameters which need to be adjust. So the parameters need to be adjust to find the group of optimum ones. Second, the MHE method is a pretty complicate method, so it is more hard to use it to design and application, especially for nonlinear system. Besides, MHE needs to optimize the states every step, this method will take a long time to show the result. So it will take more efforts to make it use in the real system.So if we want to use it in reality, it will depend on the development of the high speed software and hardware.