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


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 



polynomial coefficients


clutch state parameter


cushion spring deflection, mm


road grade angle, rad


friction coefficient


adimensional throwout bearing position


air density, kg m−3


clutch body temperature, K


clutch material temperature, K


cushion spring temperature, K


clutch actuator delay, s


clutch angular speed, rad s−1


engine angular speed, rad s−1


angular sliding speed, rad s−1


wheel angular speed, rad s−1


vehicle frontal area, m2


automated manual transmission


engine damping coefficients, Nm s rad−1


gearbox damping coefficients, Nm s rad−1


coeffcient of friction


air drag coefficient


dual clutch transmission


electric vehicle


rolling resistance coefficient


clamping force, N


maximum cushion spring reaction, N


finite element analysis


acceleration of gravity, m s−2


hybrid electric vehicle


model predictive control cost function


equivalent engine inertias, kg m2


equivalent vehicle inertias, kg m2


vehicle mass, kg


control horizon


model predictive control


number of friction surfaces


contact pressure, Pa


prediction horizon




grar ratio


clutch mean radius, m


vehicle wheel radius, m


transmission control unit


engine torque, Nm


transmitted clutch torque, Nm


sampling time, s


equivalent torque load at wheel, Nm


vehicle speed, m s−1


sliding speed, m s−1


pressure plate position, mm


throwout bearing position, mm


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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