Modeling, design, testing and control of a two-stage actuation mechanism using piezoelectric actuators for automotive applications

High bandwidth actuation systems capable of simultaneously producing relatively large forces and displacements are required for use in automobiles and other industrial applications. Conventional hydraulic actuation mechanisms used in automotive brakes and clutches are complex, inefficient and have poor control robustness. For instance, the hydraulic clutch actuation mechanism used in automatic transmissions requires pumping hardware that derives power from the engine. Along with inefficient torque converters these systems lead to reduced fuel economy, controllability issues and other disadvantages. Therefore, using advanced technologies to develop and implement novel devices, as replacements for the conventional hydraulic actuation mechanisms will improve the vehicle fuel economy significantly. This thesis presents the concept, design, development, modeling, testing and control of a novel two-stage hybrid actuation mechanism by combining classical actuators like DC motors and advanced smart material actuators like piezoelectric stack actuators. This two-stage mechanism takes advantage of the unique stiffness (force-stroke) characteristic of a typical clutch or a brake engagement process. This two-stage mechanism is modeled and designed by splitting the system into two operating regimes, namely the stroke phase and the force phase. Importance is placed on modeling the nonlinearities like the hysteresis property of piezoelectric actuators and techniques to overcome it using appropriate analysis and control methodologies. Also a technique to estimate force based on the charge stored in the piezoactuator is discussed, which leads to the elimination of the mechanical force sensor. A simple laboratory prototype experimental setup is built to demonstrate the system functioning and to test the different control strategies. A major part of this research includes the development of robust control methodologies using advanced concepts like Internal Model Control (IMC), Model Predictive Control (MPC) and a new strategy called Model Predictive Sliding Mode Control (MPSMC). The different control strategies are used to guide the two-stage actuation system to track time-varying reference force inputs. The IMC concept is used to develop a robust controller based on the uncertainty-bound on the system model. MPC is used to produce a sub-optimal controller that uses a receding-horizon window for future prediction of system behavior. The new concept MPSMC is developed to overcome the limitations of the conventional discrete-time sliding mode control. In this method, the system is forced to reach the sliding mode in a smooth sub-optimal trajectory. This optimization is carried out using MPC. Experimental results are highlighted in each case comparing the effectiveness of the different methods.