Self-learning optimization method and system for half-engagement point of wet double clutch

Abstract

The invention discloses a self-learning optimization method and system for a half-engagement point of a wet double clutch. The rotating speed of an engine flywheel is monitored in real time in the accelerator-free upshift working condition, the value of a clutch target current corresponding to the change inflection point moment of the engine flywheel is recorded, then the value of the difference between the clutch target current and the previous self-learning inflection point current is calculated, the obtained difference value is used for correcting the current value, corresponding to the half-engagement joint of the clutch, of an electromagnetic valve of the clutch, further the pressure, corresponding to the half-engagement point, between friction plates of the clutch is changed, and therefore adverse effects of abrasion on low-speed torque control of the clutch are eliminated or weakened.

Description

technical field [0001] The invention relates to a technology in the field of transmission control, in particular to a method and system for self-learning optimization of wet double clutch semi-joint points. Background technique [0002] The half-engagement point of the clutch is the relative position of the friction plate when the clutch first transmits torque, and it will change with the temperature and wear of the clutch friction plate. In the dual-clutch automatic transmission, the clutch will frequently open and engage during the entire life cycle. Due to the speed difference between the master and driven discs of the clutch, the friction plates of the clutch will wear, especially during the engagement process. After the vehicle has been driven for a long distance, the accumulation of wear and tear is considerable. The control algorithm of the wet clutch using the hydraulic actuator as the driving mechanism obtains the target control current by checking the torque-press...

AI Technical Summary

Problems solved by technology

[0003] The present invention aims at the defect that the existing hybrid vehicle cannot perform self-learning according to the self-learning method of the half-joint point of the traditional vehicle, and proposes a wet double-clutch half-joint point self-learning optimization method and system, and realizes the correction by tracking the rotational speed of the engine flywheel The clutch solenoid valve controls the current value corresponding to the clutch half-engagement point, thereby optimizing the low-speed torque control performance when the clutch is not performing well

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