System dynamic modelling and adaptive optimal control for automatic clutch engagement of vehicles

Abstract

A non-linear multi-rigid-body system dynamic modelling is developed for the automated clutch system in power transmission during clutch engagements, especially at sharp vehicle start-up, sudden engine flame-out, low driving speed and clutch plate overwearing. In order to guarantee an ideal dynamic performance of the clutch engagement, an adaptive optimal controller is designed by considering throttle angle, engine speed, gear ratio, vehicle acceleration and road condition. A non-linear model reference adaptive controller is utilized to prevent the engine from flame-out or fly-off effectively and the minimum value principle is also introduced to achieve an optimal dynamic performance of the non-linear system compromised in friction plate wear and vehicle drive quality. The optimal trajectory of the clutch engagement can be described in the form of explicit and analytical expressions and characterized by a deterministic and accurate control strategy instead of indeterministic and soft control techniques which need thousands of experiments. For validation of the controller, test work is carried out for the automated clutch engagements in a commercial car with a traditional mechanical transmission, a hydraulic actuator, a group of sensors and a portable computer system. It is shown through experiments that dynamic behaviours of the clutch engagement operated by the adaptive optimal control are more effective and efficient than those by a fuzzy PID control.

Feasibility investigation on novel concept of clutched train system to substitute for vehicular friction clutch

“…where engine output torque Me as the driving torque in the clutched train system is function in literature by Zhang et al (2002); referring to Inalpolat & Kahraman's study (2008), transmission error excitation e Sj,Pji (j=1,2) and e Rj,Pji (j=1,2) are defined in Fourier series form based on evaluation of overall effective mesh stiffness fluctuations; relative gear mesh displacements are defined as δ Sj,Pji =r Sj ·(θ Sj -θ A )+r Pj ·(θ Pji,A -θ A ), δ Rj,Pji =r Rj ·(θ Rj -θ A )-r Pj ·(θ Pji,A -θ A ) and δ R1,G =r R1 ·θ R1 ; relative displacement θ Pji,A of planet P ji (j=1,2) to arm is defined as θ Pji,A =θ Pji -θ A ; total inertia J A ' of the arm with (n1+n2) planets is defined as J A '=J A +n1·J P1 +n2·J P2 +n1·m P1 ·(r S1 +r P1 )+n2·m P2 ·(r S2 +r P2 ) where J A is moment of inertia of the arm; m P is mass of a planet; and n1 and n2 are number of planets of PGS-I and PGS-II, respectively. Similarly, equations of motion for PGS-II are described as: ( 2 2 2 2 , 2 2 , 2 2 2 , 2 2 2 2 2 , 2 2 , 2 2 2 , 2 2 ( , 2 2 , 2 2 1 2 , 2 2 2 , 2 , 2 2 , 2 2 1 2 , 2 2 2 , 2 2 …”

“…where relative gear mesh displacements are defined as δ R2,P =r R2 ·θ R2 +r P ·θ P and δ M,G =r M ·θ M ; ∆p is the pressure drop between the reversible motor-pump inlet and outlet ports; D v is the displacement of reversible motor-pump; ƞ m is the mechanical efficiency of reversible motor-pump; and function of vehicle resistant torque M r refers to literature by Zhang et al (2002).…”

“…It implies that most of control methods used in friction clutch might be transplanted into clutched train system. (Zhang et al, 2002;Chen et al, 2011) Slipping…”

“…The selected feedback gain k ij (i=2; j=1, 2) are set to 0.7 and -0.7, respectively, in accordance with Lyapunov stability theory. As for CRC, the friction work, which was taken into account for preventing overwear of friction plates (Zhang et al, 2002), is removed from the evaluation of optimal trajectory on the proposed substitution engagement. With regard to FC, the rate of engagement depends on the amplitude and the change in engine working load, and the ratio of the angular velocity difference between the driving and the driven shaft to the angular velocity of the driving shaft (Tanaka and Wada, 1995;Liu and He, 2009).…”

“…Previous research paper by Zhang et al (2002) described the application of Adaptive Optimal Control to compromise in friction plate wear and driving comfort, while other research papers from Tanaka and Wada (1995) and Liu and He (2009) showed that Fuzzy Control provides skillful operation for friction clutch engagement. These controllers improve the driving comfort during the slipping phase.…”