Variable Valve Timing (VVT) systems are used on internal combustion engines so that they can meet stringent emission requirements, reduce fuel consumption, and increase output. Also, VVT plays a critical role in order for the engine to smoothly transit between spark ignition (SI) and homogeneous charge compression ignition (HCCI) combustion modes. In order to achieve these performance benefits and SI/HCCI transition, it is required that the VVT system be controlled accurately using a model based controller. This work studies hydraulic and electric VVT system modeling and controller design. The VVT system consists of electric, mechanical, and fluid dynamics components. Without knowledge of every component, obtaining physical-based models is not feasible. In this research, the VVT system models were obtained using system identification method. Limited by the sample rate of the crank-based camshaft position sensor, a function of engine speed, the actuator control sample rate is different from that of cam position sensor. Multi-rate system identification is a necessity for this application. On the other hand, it is also difficult to maintain the desired actuator operational condition with an open-loop control. Therefore, system identification in a closed-loop is required. In this study, Pseudo Random Binary Sequence (PRBS) q-Markov Cover identification is used to obtain the closed-loop model. The open-loop system model is calculated based on information of the closed-loop controller and identified closed-loop system model. Both open and closed-loop identifications are performed in a Hardware-In-the-Loop (HIL) simulation environment with a given reference model as a validation process. A hydraulic VVT actuator system test bench and an engine dynamometer (dyno) are used to conduct the proposed multi-rate system identification using PRBS as excitation signals. Output covariance constraint (OCC) controllers were designed based upon the identified models. Performance of the designed OCC controller was compared with those of the baseline proportional integral (PI) controller. Results show that the OCC controller uses less control effort and has less overshoot than those of PI ones. An electric VVT (EVVT) system with planetary gear system and local speed controller was modeled based on system dynamics. Simulation results of the EVVT system model provided a controller framework for the bench test. The EVVT system test bench was modified from the hydraulic VVT bench. Multi-rate closed-loop system identification was conducted on the EVVT system bench and a model based OCC controller was designed. The bench test results show that the OCC controller has a lower phase delay and lower overshoot than a tuned proportional controller, while having the same or faster response time. It is also observed that engine oil viscosity has a profound impact on the EVVT response time. The maximum response speed is saturated at a slow level if the viscosity is too high. From the bench and dyno tests, it is concluded that multi-rate closed-loop identification is a very effective way to retrieve controller design orientated VVT models. It is possible to use an OCC controller to achieve lower energy consumption, lower overshoot, and better tracking compared to PI and proportional controllers on both hydraulic and electric VVT systems.
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