An Accurate Full Car Ride Model Using Model Reducing Techniques

Author:

Kim Chul1,Ro Paul I.2

Affiliation:

1. General Motors Co.

2. Department of Mechanical Engineering, North Carolina State University, Raleigh, NC 27695

Abstract

In this study, an approach to obtain an accurate yet simple model for full-vehicle ride analysis is proposed. The approach involves linearization of a full car MBD (multibody dynamics) model to obtain a large-order vehicle model. The states of the model are divided into two groups depending on their effects on the ride quality and handling performance. Singular perturbation method is then applied to reduce the model size. Comparing the responses of the proposed model and the original MBD model shows an accurate matching between the two systems. A set of identified parameters that makes the well-known seven degree-of-freedom model very close to the full car MBD model is obtained. Finally, the benefits of the approach are illustrated through design of an active suspension system. The identified model exhibits improved performance over the nominal models in the sense that the accurate model leads to the appropriate selection of control gains. This study also provides an analytical method to investigate the effects of model complexity on model accuracy for vehicle suspension systems.

Publisher

ASME International

Subject

Computer Graphics and Computer-Aided Design,Computer Science Applications,Mechanical Engineering,Mechanics of Materials

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1. Analyzing Urban Transportation Services using RideShare Data Insights;2024 IEEE 9th International Conference for Convergence in Technology (I2CT);2024-04-05

2. Improved Performance of Active Suspension System Using COA Optimized FLC for Full Car With Driver Model;Advances in Computer and Electrical Engineering;2024-03-15

3. Response Characteristic Analysis of a 10 DOF Full Car Model;Lecture Notes in Mechanical Engineering;2024

4. Performance Analysis of Linear and Rotary Energy Harvesting Shock Absorber Systems;2023 IEEE Vehicle Power and Propulsion Conference (VPPC);2023-10-24

5. A Novel Parameter Estimation Scheme for Vehicle Suspension Systems Based on Response and Test Track Prioritization;Applied Sciences;2023-09-14

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