A Prediction Method of Vehicle Rollover Index Based on Online Estimation of Center of Gravity Height

Abstract

The invention relates to a vehicle roll-over index prediction method based on gravity center height online estimation. The vehicle roll-over index prediction method comprises: establishing a vehicle roll-over dynamic model according to a dynamic base theory; obtaining a parameter identification model related to gravity center height through an adaptive filtering theory, wherein the parameter identification model only requires the lateral acceleration and the relative roll angle sensor signal as the input; based on the parameter identification model, providing an adaptive rate driven by parameter error information by designing a filtering matrix so as to achieve the online real-time adaptive estimation of the gravity center height; and finally obtaining the roll-over index prediction method based on the gravity center height online estimation according to a horizontal load transfer rate basic formula. The vehicle roll-over index prediction method of the present invention has advantages of high reliability, good real-time performance, less signal measurement demand, low cost, and good universality.

Description

technical field [0001] The invention belongs to the field of vehicle engineering, and in particular relates to online real-time estimation of the center of gravity of a vehicle and a rollover index prediction method based on it. Background technique [0002] Among all traffic accidents, vehicle rollover is an extremely dangerous vicious traffic accident, which often brings serious consequences. The online estimation of the height of the center of gravity is of great significance for the development of an effective rollover index prediction method. The dynamic rollover warning index of the vehicle can be obtained directly through online estimation of the height of the center of gravity. The main problem of the commonly used center of gravity estimation methods at present, such as Kalman filter and least squares method, is that in addition to the lateral acceleration and roll angle signals, high-order signals such as roll angular velocity and roll angular acceleration are als...

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Problems solved by technology

[0003] In order to overcome the shortcomings of poor reliability and poor real-time performance of existing rollover index prediction methods, the present invention provides a method with high reliability, good real-time performance, fewer signals to be measured, lower cost, and better universality. Prediction method of vehicle rollover index based on online estimation of center of gravity height

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