Driveline Modeling With Transmission Loss and Robust Torque Observer Design for Dual Clutch Transmission
This paper presents a design of driveline torque observer with dual clutch transmission (DCT). A goal of this study is to improve estimation performance of the observer. To increase the observer’s performance, it is important to make an accurate driveline model and a robust observer. First, to increase the accuracy of the model, the authors propose lumped driveline efficiency which is a parameter that expresses driveline transmission loss. In addition, a recursive least square estimation (RLSE) algorithm is proposed to estimate the parameter using driving data. Then, the model is updated using the estimated parameter value. Second, a reduced order observer is proposed to estimate transmitted torques of driveline in both driving and gear shifting process. Moreover, the observer, which is robust against measurement noise and disturbance, is designed through frequency domain analysis. For frequency domain analysis, an eigenstructure assignment method is applied to tune observer gains. Performance of the proposed RLSE algorithm and the observer are verified through simulation and test-bench experiments.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/00189545
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Supplemental Notes:
- Copyright © 2022, IEEE.
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Authors:
- Lee, Taeheon
- Kim, Dong-Hyun
- Choi, Seibum B
- Publication Date: 2022-2
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: pp 1267-1279
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Serial:
- IEEE Transactions on Vehicular Technology
- Volume: 71
- Issue Number: 2
- Publisher: Institute of Electrical and Electronics Engineers (IEEE)
- ISSN: 0018-9545
- Serial URL: http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=25
Subject/Index Terms
- TRT Terms: Clutches; Engines; Frequency domain analysis; Mathematical models; Torque; Transmissions
- Subject Areas: Highways; Vehicles and Equipment;
Filing Info
- Accession Number: 01837088
- Record Type: Publication
- Files: TRIS
- Created Date: Feb 25 2022 8:58AM