Vehicle operating state estimation method based on improved extended Kalman filter

Abstract

A vehicle operating state estimation method based on improved extended Kalman filter includes using the improved extended Kalman filter algorithm for properly modeling to acquire operating state information such as longitudinal forward speed, yaw velocity, lateral speed, side slip angle and the like of a vehicle in a higher maneuvering operating state, wherein the information can be used for relevant control of vehicle active safety. The vehicle operating state estimation method based on improved extended Kalman filter has the advantages of high precision, low cost, high instantaneity and the like.

Description

Technical field [0001] The present invention relates to a vehicle operating state estimation method based on an improved extended Kalman filter. Its purpose is to use the improved extended Kalman filter method to properly model the vehicle dynamics process and obtain the vehicle operating status under higher maneuvering conditions. The vehicle operating state, these states can be used for the related control of automobile active safety, which has significant advantages such as high accuracy, low cost, and good real-time performance, and belongs to the field of automobile active safety measurement and control. Background technique [0002] With the development of social economy, the problem of road traffic safety has become increasingly prominent and has become a global problem. Traffic accidents all over the world cause a large number of casualties and property losses every year. Countries around the world are working hard to reduce the occurrence of traffic accidents. In recent...

AI Technical Summary

Problems solved by technology

One is to use low-cost on-board sensors (such as inertial sensors and wheel speed sensors, etc.) to perform simple mathematical calculations on the measured signals to obtain relevant vehicle operating conditions. This method is low in cost, but due to poor accuracy of low-cost sensors And the calculation process is too simple and there are large measurement errors, thus affecting the control effect

The second is to use high-precision sensors to directly measure the running status of the relevant vehicles (such as using a photoelectric five-wheel instrument or a high-precision global navigation satellite system GNSS, especially a high-precision global positioning system GPS, etc.). This method has high precision but is expensive. Expensive and cannot be widely used

However, the model methods that have been proposed so far are mainly based on the kinematics model of the car or the dynamic model that makes more linear assumptions on the vehicle or tires. These models can obtain better estimation results and accuracy when the vehicle is running relatively smoothly. , but under high maneuvering conditions, the estimation accuracy is low because it is difficult to reflect the actual nonlinear dynamic behavior of the vehicle

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