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...

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Bibliographic Details
Published in:IEEE transactions on vehicular technology 2022-02, Vol.71 (2), p.1267-1279
Main Authors: Lee, Taeheon, Kim, Dong-Hyun, Choi, Seibum B.
Format: Article
Language:English
Subjects:
Algorithms
Automatic transmissions
Clutches
driveline modeling
Dual clutch transmission
eigenstructure assignment
Engines
Estimation
Frequency analysis
Frequency domain analysis
Gears
Load modeling
Mathematical models
Model accuracy
Noise measurement
Observers
Parameter estimation
Propagation losses
recursive least square estimation
robust torque observer
Robustness
Torque
torque estimation
Transmission loss
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Summary: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, we 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 testbench experiments.
ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2021.3132615