Dynamic Characteristics and Stability Analysis of Two-Dimensional (2D) Electro-Hydraulic Proportional Directional Valve

A 2D electrohydraulic proportional directional valve is proposed, which integrates both direct and pilot operation of the valve. In this valve, the output magnetic force of the proportional solenoid is converted to rotate the spool through a thrust-torsion coupling and thus the pressure in the valve sensitive chamber is varied. The varied pressure exerted on the areas of the spool end produces a hydrostatic force to move the spool linearly, which will rotate the spool reversely. Theoretical analysis is carried to the proposed valve and the effects of the key geometric parameters on the dynamic characteristics of the 2D valve and stability are investigated. Experiments are also designed to access to the characteristics of the valve working under direct and pilot operation. The 2D electrohydraulic valve can work properly for both direct operation and pilot operation. The hysteresis and frequency response are measured and the results are within the acceptable range in practical engineering application required of the directional proportional valve.

The Effects of Turbulence Length Scale on the Performance of Piezoelectric Harvesters

Turbulent flows carry mechanical energy distributed over a range of temporal and spatial scales and their interaction with a thin immersed piezoelectric beam results in a strain field which generates electrical charge. This energy harvesting method can be used for developing self-powered electronic devices such as flow sensors. In the present experimental work, various energy harvesters were placed in a turbulent boundary layer or inside a decaying flow field of homogeneous and isotropic turbulence. The role of large instantaneous turbulent structures in this rather complex fluid-structure interaction is discussed in interpreting the electrical output results. The forces acting on the vibrating beams have been measured dynamically and a theory has been developed which incorporates the effects of mean local velocity, turbulence intensity, the relative size of the beam’s length to the integral length scale of turbulence, the structural properties of the beam and the electrical properties of the active piezoelectric layer to provide reasonable estimates of the mean electrical power output. Experiments have been carried out in which these fluidic harvesters are immersed first in inhomogeneous turbulence like that encountered in boundary layers developing over solid walls and homogeneous and isotopic turbulence for which a simplified analytical description exists. It was found that there is a non-linear effect of turbulence length scales on the power output of the fluidic harvesters.

Juggler System: Hybrid Model and Implementation

Several juggling systems have been developed in order to control the dynamics of a bouncing element. This system is useful to show the behavior of elements due to impacts, as well as to have control of the trajectory followed by them based on physical principles. In this article, the description of the physical implementation of a juggler system is presented, including its movement control to achieve a specific objective. A hybrid model to analyze and predict the behavior of both the platform and the ball is studied and implemented. Finally, a multi-agent implementation is proposed to synchronize its movements and show how a group of oscillating systems are able to reach a common work point.

A Detection and Warning System for Unintended Acceleration

This paper presents a data-driven method to detect vehicle problems related to unintended acceleration (UA). A diagnostic system is formulated by analyzing several specific vehicle events such as acceleration peaks and generating corresponding mathematical models. The diagnostic algorithm was implemented in the Simulink/dSpace environment for validation. Major factors that affect vehicles’ acceleration (e.g., changes of road grades and gear shifting) were included in the simulation. UA errors were added randomly when human drivers drove virtual cars. The simulation results show that the algorithm succeeds in detecting abnormal acceleration.

ROM of Superharmonic Resonance of Second Order of Electrostatically Actuated MEMS Resonators

This paper deals with the voltage-amplitude response (or voltage response) of superharmonic resonance of second order of MEMS resonator sensors under electrostatic actuation. The system consists of a MEMS flexible cantilever above a parallel ground plate. The AC frequency of actuation is near one fourth the natural frequency. The voltage response of the superharmonic resonance of second order of the structure is investigated using the Reduced Order Model (ROM) method. Effects of voltage and damping voltage response are reported.

Characterization of Damping and Beating Effects Within the Aggregate Power Demand of Heterogeneous Thermostatically Controlled Loads

This paper presents an analysis of the damping and beating effects within the aggregate power demand of heterogeneous thermostatically controlled loads (TCLs). Demand response using TCLs is an appealing method to enable higher levels of penetration of intermittent renewable resources into the electric grid. Previous literature covers the benefits of TCL population heterogeneity for control purposes, but the focus is solely on the damping observed in these systems. This work is, to the best of the authors’ knowledge, the first to characterize the combined damping and beating response of power demand versus the level of TCL population parameter heterogeneity. The forced aggregate dynamics of TCLs have been shown to be bilinear when set point temperature adjustment is used as a control input. This motivates the paper’s use of free response dynamics, which are linear, to characterize both the damping and beating phenomena. A stochastic parameter distribution is applied to the homogeneous power demand solution, furnishing an analytic expression for aggregate power demand. The resulting analysis shows that increasing parameter heterogeneity increases damping and shortens the beat period.

Distributed Flow Sensing Using Bayesian Estimation for a Flexible Fish Robot

Flexibility plays an important role in fish behaviors by enabling high maneuverability for predator avoidance and swimming in turbulence. In this paper, we present a novel, flexible fish robot equipped with distributed pressure sensors for flow sensing. The body of the robot is made of a soft, hyperelastic material that provides flexibility. The fish robot features a Joukowski-foil shape conducive to modeling the fluid analytically. A quasisteady potential-flow model is adopted for real-time flow estimation, whereas a discrete-time vortex-shedding flow model is used for higher-fidelity simulation. The dynamics for the flexible fish robot are presented, and a reduced model for one-dimensional swimming is derived. A recursive Bayesian filter assimilates pressure measurements for estimating the flow speed, angle of attack, and foil camber. Simulation and experimental results are presented to show the effectiveness of the flow estimation algorithm.

Thermal Management and Voltage Stabilization in Air-Forced Open-Cathode Fuel Cells

Temperature control is undoubtedly one of the important challenges in open-cathode fuel cell systems. Due to cost considerations, it is traditionally achieved by constant-speed operation of the fans. In this paper, a state feedback temperature controller, combined with a Kalman filter to mitigate the noisy temperature measurements is designed and implemented. The controller-filter set facilitates robust thermal management with respect to model uncertainties and measurement noise. The proposed temperature control not only manages to track the fuel cell temperature reference, it can also be used to stabilize the output voltage. Voltage regulation is of great importance for open-cathode fuel cells as it guarantees a predictable and fixed fuel cell output voltage for given current values in spite of internal and external disturbances. The controllers were implemented experimentally and the results show promising performances in regulating the reference temperature and voltage despite model uncertainties and disturbances.

Modeling of Flexible Structures by Means of Least Square Support Vector Machine

This paper investigates modeling of flexible structures by means of the least squares support vector machine (LS-SVM) algorithm. Modeling is the first step to obtain a suitable model-based controller for any given system. Accurate modeling of a flexible structure based on experimental data using LS-SVM algorithm requires less knowledge about the physical system. Least squares support vector machine algorithm can achieve global and unique solution when compared with other soft computing algorithms. Also, LS-SVM algorithm requires less training time. In this paper, the successful use of support vector machine algorithm to model the flexible cantilever is demonstrated. The acquired model is able to provide accurate prediction of the system output under different operating conditions. Experimental results demonstrate the efficiency and high precision of the proposed approach.

Design Optimization of Solenoid Actuated Butterfly Valves Dynamically Coupled in Series

In this effort, we present novel nonlinear modeling of two solenoid actuated butterfly valves operating in series and then develop an optimal configuration in the presence of highly coupled nonlinear dynamics. The valves are used in the so-called “Smart Systems” to be employed in a wide range of applications including bioengineering, medicine, and engineering fields. Typically, tens of the actuated valves are instantaneously operating to regulate the amount of flow and also to avoid probable catastrophic disasters which have been observed in the practice. We focus on minimizing the amount of energy used in the system as one of the most critical design criteria to yield an efficient operation. We optimize the actuation subsystems interacting with the highly nonlinear flow loads in order to minimize a lumped amount of energy consumed. The contribution of this work is to include coupled nonlinearities of electromechanical valve systems to optimize the actuation units. Stochastic, heuristic, and gradient based algorithms are utilized in seeking the optimal design of two sets. The results indicate that substantial amount of energy can be saved by an intelligent design that helps select parameters carefully but also uses flow torques to augment the closing efforts.