Vehicle State Estimation Based On The Iterative Extended Kalman Filteringauxiliary Particle Filtering Algorithm

How to actualize the vehicle active safety control is the key to ensure the safety of the vehicle,Vehicle Stability Control System,Anti Rollover Control System and Obstacle Avoidance Control System is the important guarantee to the vehicle active safety control.The sideslip angle is an important parameter to weight the vehicle dynamic state,the accurate estimation is the prerequisite for the system excellent work.However,it is difficult to measure sideslip angle directly in practical application for the cost is very high,therefore,considering the economy and accuracy factor,it's usually estimated by soft measurement method.By using some physical quantity that easily observed based on estimator to estimate the sideslip angle is one of the methods in common.But due to the limitation of the linear model,this method can only be applied to vehicle linear area,It don't suitable for the vehicle stability control system which work during trigger condition,obviously can't meet the requirements.In order to solve the problem that the liner sideslip angle estimation model can't suit the working condition of the vehicle satisfy control system,the main content is as follows:1.Building up a 7 DOF vehicle model which contain horizontal,vertical,yaw and four wheel speed to describe the vehicle state,preparing for the state observer.2.In this paper,an iterative extended kalman auxiliary particle filter algorithm is proposed to estimate the sideslip angle of the vehicle.This algorithm solves the problem that the extended kalman filter is not accurate in nonlinear condition and the particle degradation during standard particle filter process.building the observer,which setting sideslip angle as measurement,using the iterative extended kalman filter to update particles to get close to the real state,and through the auxiliary particle filter algorithm to resample which combine the latest observation,combining these two algorithms proposed iterative extended kalman filtering-auxiliary particle filtering algorithm to observe vehicle sideslip angle,improve the observation results and accuracy.3.The vehicle simulation software CarSim and Matlab/Simulink were used to simulate and compare.4.In order to verify the performance of the algorithm,a sideslip angle test system was developed which based on double antenna GPS and the application of carrier phase.Carry out double lane change and slalom test in high and low adhesion road in different speed using the experimental vehicle and collect experimental data.Data processing module using the Gauss projection coordinate transformation to obtain the angle between the longitudinal axis of the vehicle and the vehicle velocity vector to obtain the actual sideslip angle.And the results were compared to estimation result of the algorithm and the traditional standard particle filter.