Actuator Position Control of Dual Clutch Transmission systems using Model Predictive Control techniques

The economic performance of a vehicle fuel as well as the driving comfort are currently attracting the attention of automotive industries for commercial success. In this regard, the Automated Manual Transmission (AMT) systems equipped with the Dry Dual Clutch Transmission (DCT) technology represents the best compromise between the Manual Transmission (MT) low fuel consumption and the Automated Transmission (AT) clutch actuation efficiency. In such a modern powertrain system, the accuracy of the clutch actuator control system is of paramount importance in relation to the driving behaviour. With reference to this, the following thesis proposes a position control strategy for the even gear actuator (K2 - Actuator) of a DDCT system. The aim of the project, developed in collaboration with Centro Ricerche Fiat (CRF), is to design a controller to track different position trajectories guaranteeing smoothness during the gear shifting process with a continue torque transmission. Since an a priory model of the considered K2 - Actuator is not available, the system identification methodology is exploited to built a mathematical model that suitably represents the dynamic relationship between the involved variables. Linear and non-linear model structures are proposed to identify the plant dynamics and an adaptive approach is considered to handle the system variations with respect to the working region. Different control architectures are adopted following the Optimal Control theoretical procedures. A Model Predictive Controller (MPC) is designed to deal with multiple control objectives explicitly accounting physical constraints on the involved variables. Then, a Linear Quadratic Regulator (LQR) control technique is introduced to enhance computational aspects. Thus, a possible numerical implementation is proposed. For both of the adopted control strategies, an adaptive approach and a real time adjustment of the controller design parameters is developed to maintain the same level of control system performances despite the plant model dynamics are quickly changing on the basis of the working region. Finally, the absence of a real position sensor in the described DDCT system is considered by exploiting different Virtual Sensor based Control architectures. Several simulations in the MATLAB/SIMULINK environment and a fine tuning procedure are carried out to test the effectiveness of the proposed control strategies until satisfactory control performances are achieved.