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In this paper recent control developments for an electromechanical valve actuator will be presented. The model-based control methodology utilizes position feedback, a nonlinear observer that provides virtual sensing of the armature velocity and current, and cycle-to-cycle learning. The controller is based on a nonlinear state-space description of the actuator that is derived based on physical principles and parameter identification. A bench-top experimental setup and a rapid control prototyping system are used to quantify the actuator performance. Experiments are conducted to measure valve release timing, transition times, and contact velocities for open- and closed-loop control schemes. Simulation results are presented for a feed-forward cycle-to-cycle learning controller.

Turbocharger compressors are susceptible to surge – the instability phenomena that impose limitations on the operation of turbocharged engines because of undesired noise, engine torque capability constraints, and hardware strain. Turbocharged engines are typically equipped with a binary compressor recirculation valve (CRV) whose primary function is to prevent compressor surge. Calibration of the associated control strategy requires in-vehicle tests and usually employs subjective criteria. This work aims to reduce the calibration effort for the strategy by developing a test procedure and data processing algorithms. An automated calibration for CRV control is developed that will generate a baseline calibration that avoids surge events. The effort to obtain the baseline calibration, which can be further fine-tuned, is thereby significantly reduced.