Research Papers

A Modified Predictive Functional Control With Sliding Mode Observer for Automated Dry Clutch Control of Vehicle

[+] Author and Article Information
Liang Li

The State Key Laboratory of Automotive
Safety and Energy,
Tsinghua University,
Beijing 100084, China;
The Collaborative Innovation
Center of Electric Vehicles,
Beijing 100081, China
e-mail: liangl@mail.tsinghua.edu.cn

Xiangyu Wang

The State Key Laboratory of Automotive Safety
and Energy,
Tsinghua University,
Beijing 100084, China
e-mail: wang-xy15@mails.tsinghua.edu.cn

Xiaosong Hu

The State Key Laboratory of Mechanical
Chongqing University,
Chongqing 400044, China
e-mail: xiaosonghu@berkeley.edu

Zheng Chen

Mechatronics and Intelligent Systems,
Faculty of Engineering,
University of Technology,
Sydney 2070, Australia
e-mail: jeffchenzheng@yahoo.com

Jian Song

The State Key Laboratory of Automotive Safety
and Energy,
Tsinghua University,
Beijing 100084, China
e-mail: daesj@tsinghua.edu.cn

Fahad Muhammad

The State Key Laboratory of Automotive Safety
and Energy,
Tsinghua University,
Beijing 100084, China
e-mail: engineer_fahad@rocketmail.com

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received July 24, 2015; final manuscript received January 20, 2016; published online March 30, 2016. Assoc. Editor: Zongxuan Sun.

J. Dyn. Sys., Meas., Control 138(6), 061005 (Mar 30, 2016) (10 pages) Paper No: DS-15-1341; doi: 10.1115/1.4032830 History: Received July 24, 2015; Revised January 20, 2016

Dry clutch control is a typical nonlinear problem due to the nonlinear characteristics of diaphragm springs. For precise position control of the automated dry clutch, a modified predictive functional control (mPFC) method is proposed. First, a novel mechanical actuator is designed and models of the automated dry clutch system are built based on theoretical analysis and experimental data. Then, in order to compensate for the position error of direct current (DC) motor caused by load torque, modifications are introduced to a regular predictive functional control (PFC), including a sliding mode observer (SMO) to estimate the load torque and a predictive model concerning the load torque. Next, simulations show that the SMO could estimate the load torque accurately and the mPFC performs well with the nonlinear load torque. Finally, experiments are carried out on a test bench and the results are in accordance with the simulations. Due to the little online computing burden and the simple structure of the mPFC, it could be used in other industrial control systems which need fast response.

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Fig. 1

Schematic graph of the automated clutch system

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Fig. 2

Relationship between the throw-out force and the clutch position

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Fig. 3

Free displacement and throw-out displacement of clutch

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Fig. 4

Schematic diagram of the clutch actuator: 1—worm, 2—worm gear, 3—solar gear, 4—planetary gear, 5—planetary carrier, 6—release yoke, 7—clutch throw-out bearing, and 8—gear rings

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Fig. 5

Schematic diagram of the simplified DC motor

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Fig. 6

Clutch position curve in three startup conditions: (a) normal startup condition, (b) ramp startup condition, (c) slow startup condition, and (d) comparison of fitted curves in three conditions

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Fig. 7

Block diagram of the mPFC controller

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Fig. 8

Simulation results of step response using a regular PFC

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Fig. 9

Simulation results of step response using an mPFC

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Fig. 10

Simulation results of normal startup of a vehicle

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Fig. 11

Simulation results of slow and ramp startup of a vehicle

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Fig. 12

Test bench of automated clutch system

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Fig. 13

Experiment results of step response

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Fig. 14

Experiment results of normal startup of a vehicle



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