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International Journal of Automotive Technology

, Volume 20, Issue 6, pp 1089–1101 | Cite as

Thermal Compensation Control Strategy in Automated Dry Clutch Engagement Dynamics and Launch Manoeuvre

  • Mario PisaturoEmail author
  • Adolfo Senatore
Article
  • 14 Downloads

Abstract

Repeated engagements in dry clutch systems could yield remarkable increase of clutch disk temperature. In dry clutch based transmissions like Automated Manual Transmissions and Dual Clutch Transmissions the overheating leads to poor control of gearshift quality due to unpredictable and fast change of frictional characteristic. Even permanent damage of clutch facings may occur. Under this light, this paper focusing on thermal effects to improve control performances and prevent uncomfortable engagements. To this aim, detailed analyses of dry clutch architecture have been carried out to understand the main phenomena which affect the clutch torque transmissibility. Moreover, a lumped thermal model has been developed to predict both the disk surface and cushion spring temperature in real-time environment. To validate the proposed thermal model, a non-linear least squares method has been used by comparing simulations with finite element results. A control strategy based on model predictive control and thermal compensation effects has been proposed to simulate vehicle launch manoeuvres in flat and up-hill road conditions with low and high initial clutch temperature as well. Finally, the proposed control approach has been compared with classic PI control strategy to prove its effectiveness.

Key Words

Dry-clutch Friction coefficient Temperature Parameter estimation Model predictive control Thermal compensation 

Nomenclature

α0…13

polynomial coefficients

β

clutch state parameter

δf

cushion spring deflection, mm

ø

road grade angle, rad

μ

friction coefficient

ξ

adimensional throwout bearing position

ρair

air density, kg m−3

θb

clutch body temperature, K

θcm

clutch material temperature, K

θfs

cushion spring temperature, K

τc

clutch actuator delay, s

ωc

clutch angular speed, rad s−1

ωe

engine angular speed, rad s−1

ωsl

angular sliding speed, rad s−1

ωw

wheel angular speed, rad s−1

A

vehicle frontal area, m2

ATM

automated manual transmission

be

engine damping coefficients, Nm s rad−1

bg

gearbox damping coefficients, Nm s rad−1

CoF

coeffcient of friction

Cx

air drag coefficient

DCT

dual clutch transmission

EV

electric vehicle

f

rolling resistance coefficient

Ffc

clamping force, N

Fmax

maximum cushion spring reaction, N

FEA

finite element analysis

g

acceleration of gravity, m s−2

HEV

hybrid electric vehicle

Jcost

model predictive control cost function

Jef

equivalent engine inertias, kg m2

Jv

equivalent vehicle inertias, kg m2

m

vehicle mass, kg

mh

control horizon

MPC

model predictive control

n

number of friction surfaces

p

contact pressure, Pa

ph

prediction horizon

PI

proportional-integral

r

grar ratio

Rm

clutch mean radius, m

Rw

vehicle wheel radius, m

TCU

transmission control unit

Te

engine torque, Nm

Tfc

transmitted clutch torque, Nm

Ts

sampling time, s

Tw

equivalent torque load at wheel, Nm

ν

vehicle speed, m s−1

νs

sliding speed, m s−1

χpp

pressure plate position, mm

χto

throwout bearing position, mm

χtokiss

kiss point position, mm

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Copyright information

© KSAE/ 111-02 2019

Authors and Affiliations

  1. 1.Department of Industrial EngineeringUniversity of SalernoFiscianoItaly

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