2 research outputs found

    Nonlinear System Modeling, Optimal Cam Design, and Advanced System Control for an Electromechanical Engine Valve Drive

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    A cam-based shear force-actuated electromechanical valve drive system offering variable valve timing in internal combustion engines was previously proposed and demonstrated. To transform this concept into a competitive commercial product, several major challenges need to addressed, including the reduction of power consumption, transition time, and size. As shown in this paper, by using nonlinear system modeling, optimizing cam design, and exploring different control strategies, the power consumption has been reduced from 140 to 49 W (65%), the transition time has been decreased from 3.3 to 2.7 ms (18%), and the actuator torque requirement has been cut from 1.33 to 0.30 N·m (77%).Sheila and Emanuel Landsman Foundatio

    Rauch-Tung-Striebel Smoother for Position Estimation of Short-Stroke Reluctance Actuators

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    This article presents a novel state estimator for short-stroke reluctance actuators, intended for soft-landing control applications in which the position cannot be measured in real time. One of the most important contributions regards the system modeling for the estimator. The discrete state of the hybrid system is treated as an input. Moreover, the model is simplified to facilitate the identification of parameters and the implementation of the estimator. Thus, auxiliary variables are added to the state vector in order to indirectly account for modeling errors. Another important contribution is the state estimation approach. It is based on the Rauch–Tung–Striebel fixed-interval smoother, which allows refining past data from later observations. Numerous simulations are performed to analyze and compare the proposal and several alternatives. In addition, experimental testing is presented to evaluate and validate the estimator. As the simulated and experimental analyses demonstrate, the combined effect of the novel additions results in significantly smaller estimation errors of position and velocity
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