Suspension system state estimation using adaptive Kalman filtering based on road classification-Reference-Cited by-同舟云学术

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Suspension system state estimation using adaptive Kalman filtering based on road classification

Published:2016-12-20 Issue:3 Volume:55 Page:371-398
ISSN:0042-3114
Container-title:Vehicle System Dynamics
language:en
Short-container-title:Vehicle System Dynamics

Author:

Wang Zhenfeng¹,Dong Mingming¹,Qin Yechen¹,Du Yongchang²,Zhao Feng³,Gu Liang¹

Affiliation:

1. School of Mechanical Engineering, Beijing Institute of Technology, Beijing, People’s Republic of China

2. State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, People’s Republic of China

3. Beijing Institute of Aerospace Control Devices, Beijing, People’s Republic of China

Funder

National Nature Science Foundation of China

Innovative Talent Support Program for Post-doctorate of China

China Postdoctoral Science Foundation

Publisher

Informa UK Limited

Subject

Mechanical Engineering,Safety, Risk, Reliability and Quality,Automotive Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/00423114.2016.1267374

Reference23 articles.

1. Survey of Advanced Suspension Developments and Related Optimal Control Applications11This paper was not presented at any IFAC meeting. This paper was recommended for publication in revised form by Editor Karl Johan Åström.,22Simple, mostly LQ-based optimal control concepts gave useful insight about performance potentials, bandwidth requirements, and optimal structure of advanced vehicle suspensions. The present paper reviews these optimal control applications and related practical developments.

2. Vibration Control Using Semi-Active Force Generators

3. Design Optimization of Quarter-car Models with Passive and Semi-active Suspensions under Random Road Excitation

4. Semi-active control of vehicle suspension with magneto-rheological dampers

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