Vehicle parameter on-line estimation method based on unscented Kalman filtering

Abstract

The invention discloses a method for estimating vehicle parameters such as complete vehicle mass and centre-of-gravity position on line by using an unscented Kalman filtering technique during the driving process of a vehicle. A hardware part of the method mainly comprises a vehicle-mounted sensor for a vehicle longitudinal speed, a vehicle longitudinal accelerated speed, a wheel angular speed, a wheel angular accelerated speed, a vehicle vertical accelerated speed and the like, a microcontroller and the like; a software part mainly refers to an unscented Kalman filtering algorithm for implementing estimation on the complete vehicle mass and the centre-of-gravity position. By applying the method, the on-line estimation on the vehicle parameters such as the complete vehicle mass and the centre-of-gravity position can be realized by collecting vehicle dynamic states and establishing an unscented Kalman filter according to a characteristic that the complete vehicle mass and the centre-of-gravity position are greatly influenced by the load change of the vehicles such as a heavy truck and a light automobile.

Description

technical field [0001] The invention relates to an online estimation method of vehicle parameters such as vehicle mass and center of gravity position by using unscented Kalman filter technology during vehicle running, and belongs to the field of vehicle auxiliary driving. Background technique [0002] For heavy-duty trucks and lightweight vehicles, changes in their loading capacity will have a significant impact on the quality of the vehicle, and will also lead to significant changes in the position of the center of gravity of the vehicle. However, the existing vehicle active safety systems such as anti-lock brake control and body electronic stability control generally obtain the vehicle mass and the center of gravity position of the vehicle in a static state in advance through static measurement, and assume that these two types of parameters are in the vehicle. It is approximately constant during the driving process to establish a linear vehicle dynamics model and realize t...

AI Technical Summary

Problems solved by technology

These patents use special methods to estimate the mass of the vehicle or the position of the center of gravity online, but none of them can estimate the mass of the vehicle and the position of the center of gravity at the same time

At the same time, none of these patented methods uses a model-based online estimation method, and the accuracy of the obtained vehicle parameters such as vehicle mass and center of gravity position is not high

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