ISBN 978-3-8439-5532-4

978-3-8439-5532-4, Reihe Fahrzeugtechnik

Xiongshi Wang
Online Estimation of Vehicle Inertial Parameters with IMU Using Vibration Response Data

192 Seiten, Dissertation Technische Universität Berlin (2024), Softcover, A4

Zusammenfassung / Abstract

Advanced stability control systems and safety requirements in automatic vehicles have made active safety dynamics control highly dependent on precise vehicle states and parameters. Vehicle inertial parameters such as vehicle mass, center of gravity (CoG), and moment of inertia (MoI) are crucial for optimal performance. However, measuring them directly in a standard car is difficult due to technical and economic reasons. Therefore, it is essential to identify these parameters to improve the performance of advanced driver assistance systems. This study focuses on accurately estimating vehicle inertial parameters.

To achieve the objective, this study proposes an integrated estimation structure that simultaneously estimates the vehicle inertial parameters with an inertial measurement unit (IMU), regardless of changes in passenger numbers or seating arrangement. The integrated estimation structure has three main components: the mass estimator, the CoG estimator, and the MoI estimator. The estimator blocks which are developed in Carmaker, considering the combination of model-based and data-driven methods with machine learning algorithms.

To validate the performance of the developed estimators, the 4-poster test rig is utilized and seven kinds of vehicle loading scenarios are designed. Results confirm the accuracy and effectiveness of the proposed estimators, the experimental results demonstrate the good performance of the integrated vehicle inertia parameters estimation system with IMU based on road condition uncertainties.

This study is an important part of vehicle parameters estimation, which provides data support for active safety control, drivetrain control, and autonomous driving.