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Research Papers

Optimization of Shift Control Trajectories for Step Gear Automatic Transmissions

[+] Author and Article Information
Mirko Čorić

Faculty of Mechanical Engineering
and Naval Architecture,
University of Zagreb,
Ivana Lučića 5,
Zagreb HR-10002, Croatia
e-mail: mirko.coric@fsb.hr

Vanja Ranogajec

Faculty of Mechanical Engineering and
Naval Architecture,
University of Zagreb,
Ivana Lučića 5,
Zagreb HR-10002, Croatia
e-mail: vanja.ranogajec@fsb.hr

Joško Deur

Faculty of Mechanical Engineering
and Naval Architecture,
University of Zagreb,
Ivana Lučića 5,
Zagreb HR-10002, Croatia
e-mail: josko.deur@fsb.hr

Vladimir Ivanović

Ford Research and Innovation Center,
2101 Village Road,
Dearborn, MI 48121
e-mail: vivanovi@ford.com

H. Eric Tseng

Ford Research and Innovation Center,
2101 Village Road,
Dearborn, MI 48121
e-mail: htseng@ford.com

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received March 17, 2016; final manuscript received November 29, 2016; published online March 23, 2017. Assoc. Editor: Jingang Yi.

J. Dyn. Sys., Meas., Control 139(6), 061005 (Mar 23, 2017) (13 pages) Paper No: DS-16-1149; doi: 10.1115/1.4035403 History: Received March 17, 2016; Revised November 29, 2016

New generation of torque converter automatic transmissions (ATs) include a large number of gears for improved fuel economy and performance. Control requirements for such a transmission become more demanding, which calls for the development of new shift control optimization tools. A pseudospectral collocation method is used in the paper to optimize AT clutch and engine control trajectories for comfortable and efficient shifts. Since the optimization method requires a smooth formulation of plant model, the emphasized clutch model nonlinearity around the zero slip speed has been found to be a major difficulty to be resolved through proper modeling of the optimization problem. Therefore, different approaches of describing the friction behavior are considered and assessed, starting from simple static models, through dynamics models, toward torque-source approaches subject to the clutch passivity constraint. Apart from the conventional optimization approach based on minimizing the cost function (including the vehicle jerk and clutch energy loss terms), the so-called feasibility approach based on restricting the cost through an inequality constraint is considered, as well. The proposed optimization method has been verified on a characteristic example of 10-speed AT for both single- and double-transition shifts (DTSs). It has been found out that the clutch passivity constraint-based approach results in numerically most efficient optimizations for a wide range of shift tasks and scenarios.

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References

Figures

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Fig. 1

Illustration of powertrain structure: schematic (a) and bond graph (b)

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Fig. 2

Schematic of AT gearbox [22]

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Fig. 3

Bond graph model of AT gearbox

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Fig. 4

Generalized static friction model (a), and its realization through classical (b) and Karnopp static model (c), and Dahl dynamic model (d)

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Fig. 5

Phases of typical single-transition upshift

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Fig. 6

Comparative optimization results of 1–2 power-on upshift for different clutch modeling approaches (jerk-only criterion; without off-going and extra clutch modulation in inertia phase; pth = 0.5)

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Fig. 7

Optimization results for different 1–2 power-on upshift control scenarios (passivity-based clutch model, pth = 0.5): (a) w/ and w/o off-going clutch modulation in inertia phase (jerk-only case), (b) w/ and w/o extra clutch control (jerk-only case), (c) w/ and w/o engine torque control (jerk-only case), and (d) different tuning of main weighting factor kw (jerk-only, and weak and strong energy constraint cases)

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Fig. 8

All-clutch control optimization results for 1–2 power-on upshift (jerk-only criterion, passivity-based clutch model, feasibility approach, pth = 0.1), including comparison with two-element shift with off-going clutch modulation in inertia phase

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Fig. 11

Bond graph elements and related equations [27]

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Fig. 9

Optimization results for 5–3 power-on single-transition downshift (jerk-only criterion, passivity-based clutch model, pth varying from 0.3 to 1)

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Fig. 10

Optimization results for 8–4 power-on double-transition downshift (jerk-only criterion, passivity-based clutch model, pth varying from 0.3 to 1)

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