Method for robust estimation of vehicle side slip angle based on longitudinal force observer

Abstract

The invention discloses a method for robust estimation of a vehicle side slip angle based on a longitudinal force observer. The method comprises the following steps of (1), establishing a two-degree-of-freedom vehicle model and an electric drive wheel model; (2), designing the longitudinal force observer; 3), conducting robust estimation on the vehicle side slip angle based on the longitudinal force observer. The new longitudinal force estimation method is proposed on the basis of distributed drive electric vehicles and driving characteristics thereof, and based on the longitudinal force estimation, vehicle model uncertainty caused by parameter perturbation of tire cornering stiffness is considered to design vehicle side slip angle estimation by adopting a robust Kalman filter. The estimation method can fully utilize the advantages of the distributed drive electric vehicles, the longitudinal force estimation cost is effectively reduced, and the method helps to improve the robustness ofside slip angle estimation under unknown disturbance and complicated working conditions.

Description

technical field [0001] The invention belongs to the field of electric vehicle research, and in particular relates to a method for robustly estimating the sideslip angle of the center of mass of a distributed drive electric vehicle based on a longitudinal force observer. Background technique [0002] In recent years, active safety systems including electronic stability system ESP, brake anti-lock brake system ABS, traction control system TCS, and drive anti-skid system ASR have been more and more widely used in vehicles. Good vehicle system closed-loop control requires accurate and reliable vehicle state measurements. However, some vehicle states, including the center of mass side slip angle, are difficult to directly measure with on-board sensors, or considering the high cost of sensors, people are increasingly inclined to It is based on the design of a feasible observer to accurately estimate part of the vehicle state, so as to provide a basis for the vehicle control system...

AI Technical Summary

Problems solved by technology

When the car is actually driving, the vehicle parameters including the tire cornering stiffness change in real time. These model uncertainties caused by parameter perturbation will cause a certain degree of vehicle modeling error, so the model-based vehicle state observer The estimation accuracy is also affected accordingly, so it is necessary to design a robust estimation method for the sideslip angle of the vehicle center of mass

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