Abstract
A performance analysis of automotive semi-active suspension control algorithms was realized. Three on/off control strategies were tested in a quarter of vehicle model: hybrid Sky Hook-Ground Hook, hybrid Mix-1-Sensor and Frequency Estimation-Based controller. A commercial Magneto-Rheological damper was modeled by using an Artificial Neural Network approach. The automotive semi-active suspension was implemented in a commercial Controller Area Network system; and the control algorithms were implemented in a micro-controller system with comfort and road holding as main goals. Early results show the feasibility of this application.
Original language | English |
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Title of host publication | 19th IFAC World Congress IFAC 2014, Proceedings |
Editors | Edward Boje, Xiaohua Xia |
Pages | 10902-10907 |
Number of pages | 6 |
ISBN (Electronic) | 9783902823625 |
DOIs | |
Publication status | Published - 2014 |
Publication series
Name | IFAC Proceedings Volumes (IFAC-PapersOnline) |
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Volume | 19 |
ISSN (Print) | 1474-6670 |
Bibliographical note
Funding Information:⋆ This work was supported by CONACyT (Bilateral project México-Spain 142183) and Tecnológico de Monterrey (Autotronics Research Chair). Authors thank METALSA for sharing its experimental setup
Publisher Copyright:
© IFAC.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering