P.J. Costa Branco

Abstract: Portable fuel cells are receiving great attention today mainly because their energy density is higher than any portable battery solution. Among other types, portable polymer electrolyte membrane (PEM) fuel cells are an established technology where research on increasing their efficiency is leading product development and manufacturing. The objective of this work was to study and evaluate the redesign of a commercial portable fuel cell, improving its efficiency. A three-dimensional model of the original PEM fuel cell with parallel plus a transversal flow channel design was developed using Comsol Multiphysics, including the effects of liquid water formation and electric current production. Using this model, the effects of different channel geometries and respective cathode flow rates on the cell�s performance, including the local transport characteristics, were studied. Laboratory tests with various fuel cell stacks using the new channels structure were effectuated for an evaluation of the fuel cell�s performance, showing improvements in its efficiency of up to 26.4%. (C) 2009 Elsevier Ltd. All rights reserved.

Abstract: In this paper an analytical and experimental evaluation of a magnetorheological damper is described. Based on modelling the friction force effects between the MR fluid and the device walls, a continuum electromechanical model describing the damper behaviour is formulated. A magnetorheological device was fabricated to validate the model being tested under static and steady-state load conditions and applied magnetic field values. The friction coefficient and the magnetic permeability of the MR fluid are estimated experimentally, and the effectiveness of the proposed model is verified. (C) 2009 Elsevier B.V. All rights reserved.

Abstract: Ionic polymer-metal composites (IPMCs) need ionic hydration to operate. Being water the most used solvent, it happens that during the IPMC air operational life it will eventually dry. With the objective of producing an air-operable IPMC actuator, a new encapsulation process using a dielectric gel is proposed in this paper. We describe the encapsulation procedure and a set of experiments that were performed to verify the evolution of electrical and mechanical IPMC characteristics after I day. I week, and after 20 days of encapsulation. The results show that the encapsulated IPMC remained hydrated and its performance maintained, indicating the potentiality of the dielectric gel as an IPMC encapsulant material. (c) 2007 Elsevier B.V. All rights reserved.

Abstract: Biomedical engineering applications of ionic polymer-metal composites such as motion devices for endoscopy, pumps, valves, catheter navigation mechanisms and spinal pressure sensors make it important to properly model IPMCs for engineering design. In particular, IPMC continuum models and their electric equivalent circuit representation are critical to a more efficient design of IPMC devices. In this paper, we propose a new continuum electromechanical model to understand and predict the electrical/mechanical behavior of the IPMC. An IPMC lumped-parameter circuit is derived from its continuum model to predict the relationship between its voltage and current signals. Although based on previous works of Shahinpoor and Nemat-Nasser, our model was derived on a macroscopic level, the water effects were assumed negligible when compared with the electrical effects of mobile ions for the IPMC motion, the model parameters were clearly identified in their physical meaning, and an equivalent-circuit IPMC model was determined from the established continuum electromechanical model. Experiments are done with two IPMC pieces having different dimensions, which were previously immersed in a sodium solution. The IPMCs are current driven, the transverse displacement and voltage signals being measured for different current values, avoiding the water electrolysis phenomenon. Simulations using the analytic models derived are compared with the experimental results and they are found to predict the electrical and mechanical relations very accurately.

Abstract: We report on a theoretical and experimental study of the use of a traveling magnetic field generated by a linear induction motor to propel a conducting fluid in a closed channel. We initially developed an analytical model to predict the distribution of density currents, forces, and fluid speed. To verify the validity of our assumptions for the analytical model, we developed a finite-element model and compared its results to those ones obtained from the analytical model. We built a prototype of the fluid transportation system, using mercury as the conducting fluid. Here, we present the prototype�s experimental characteristics with various alternating current values and compare them with the analytical model�s results.

Abstract: This paper describes the procedure for modeling an 8/6 switched reluctance machine (SRM) step-by-step. First, the geometry and mechanical parameters of the machine are established, when a finite-element modeling (FEM) approach is initially developed to obtain the flux linkage/current/rotor position relationship so that the proper and mutual inductances and also its torque and field distribution characteristics can then be computed. Afterward, a series of experimental tests are performed to obtain the magnetic characteristics of the machine, comparing, correcting, and discussing the results with those of FEM analysis.

Abstract: This paper presents an analytical, numerical and experimental study of an asymmetric piezoelectric actuator/sensor cantilever beam. The structure consists in a three-layered laminate with a piezoceramic acting as actuator, an elastic material layer and a second piezoceramic layer that can operate as a sensor or actuator. The coupled expansion-bending motion of the system is analytically resolved, where the governing electromechanical expansion and bending motion equations are obtained. Explicitly analytic solutions for longitudinal and transverse displacements, and also the mechanical/electrical frequency response of the structure are calculated. A finite element model (FEM) is developed and used to evaluate the accuracy of the analytic model. Experimental results are used to verify the frequency response of the structure, and validate the theoretical and FEM models.

Abstract: The immune system is a cognitive system of complexity comparable to the brain and its computational algorithms suggest new solutions to engineering problems or new ways of looking at these problems. Using immunological principles, a two(or three-) module algorithm is developed which is capable of launching a specific response to an anomalous situation for diagnostic purposes. Experimental results concerning fault detection in an induction motor are presented as an example illustrating how the immune-based system operates, discussing its capabilities, drawbacks, and future developments.

Abstract: A new offline current modulation using a neuro-fuzzy compensation scheme for torque-ripple reduction in switched reluctance motors is presented. The main advantage of the proposed technique is that the torque signal is unnecessary. The compensating signal is learned prior to normal operation in a self-commissioning run, capturing the necessary current shape to reduce the torque ripple. Simulation results verify first the effects of speed and then load changes on the compensator performance. Implementation of the proposed technique in a laboratory prototype shows the feasibility and accuracy of the respective offline scheme.

Abstract: A Matlab/Simulink environment to simulate a 6/4-switched reluctance motor is described. From its linear model to the nonlinear model, its dynamics is described and discussed in detail. All simulations are completely documented by their block diagrams and corresponding special Matlab functions and parameters quickly develop its model to the reader. Based on the developed model, simulation studies are performed and compared with measured motor phase currents either for hysteresis and voltage control strategies, and the steady-state motor operation to validate the model.

Abstract: Drive systems today determine the productivity and quality of industrial processes. However, they exhibit considerable complexities related with their behavior as large uncertainties at a structure and parameter levels, multidimensionality, and strong mutual interactions, With these multiplying complexities, the usual models are becoming not accurate enough. It is necessary to complement them with other information-processing techniques that allow a better recognition of their behavior. The aim of this paper is to analyze common features, and the potential, but also the drawbacks that fuzzy logic and formal language theories show when used for recognition of patterns in experimental drives. Two prototype systems are used: an electrohydraulic drive and an induction motor drive, We underline the similarities and various aspects of both recognition methodologies, despite their use on different systems. A set of experimental learning situations with critical effects on their performance are presented and discussed.

Abstract: Fuzzy relational identification builds a relational model describing a system�s behaviour by a nonlinear mapping between its variables. In this paper, we propose a new fuzzy relational algorithm based on the simplified max-min relational equation. The algorithm presents an adaptation method applied to the gravity-centre of each fuzzy set based on the error integral value between the measured and predicted system�s output, and uses the concept of time-variant universe of discourse. The identification algorithm also includes a method to attenuate the noise influence in the extracted system�s relational model using a fuzzy filtering mechanism. The algorithm is applied to a one-step forward prediction of a simulated and experimental motor drive system. The identified model has its input-output variables (stator-reference current and motor speed signal) treated as fuzzy sets, whereas the relations existing between them are described by means of a matrix R defining the relational model extracted by the algorithm. The results show the good potentialities of the algorithm in predicting the behaviour of the system and in attenuating through the fuzzy filtering method possible noise distortions in the relational model. (C) 2000 Elsevier Science B.V. All rights reserved.

Abstract: In Part I of this paper, fuzzy modeling showed its potential to describe the behavior of the electro-hydraulic system. To verify the possibilities of its application for the system�s learning control, two inverse-model compensation schemes were implemented. This paper describes and discusses the experimental results obtained, showing the feasibility and effectiveness of the learning controllers in:generalizing their previously acquired knowledge to possible new trajectories, their ability to learn new rules and update their fuzzy models while functioning, and how they compensate changes in the system�s dynamics caused by the variation of the parameters and/or environment perturbations on it.

Abstract: Drive systems are usually modeled using a mathematical characterization of their physical phenomena. However, the difficulty in establishing a relevant model representation, in particular for electro-hydraulic systems, makes important the search for other modeling mechanisms that allow the combination of previously compiled system�s knowledge with acquired experimental information. This paper, divided into two parts, describes the potential and possible drawbacks of integrating fuzzy learning mechanisms into a drive system that includes an electro-hydraulic actuator, First, experimental verification of actuator�s fuzzy modeling is presented in Part I of the paper, where the variable selection problem and the performance of the learning algorithm are discussed. In Part II, extensive experimental results employing the extracted fuzzy model and associated learning algorithm are presented, The feasibility and effectiveness of integrating fuzzy learning mechanisms into the actuator�s control is also discussed.

Abstract: Electromechanical systems are usually modelled using energy conversion theory. However, this representation is not accurate enough. The reasons are the presence of non-linear relations between the variables, changes in system parameters, and the difficulty encountered sometimes in taking into account, in a simple and precise way, physical phenomena like, friction, viscosity, and saturation. So, it is useful to automatically extract the relations that represent the system behaviour. We investigate in this paper three fuzzy learning algorithms which represent the development of our study and are used for automatic modelling of electromechanical systems. We begin with a very simple algorithm. Some problems are pointed as containing the requisites to be a good model; next, two methods which are composed of a fuzzy-cluster-based algorithm and a fuzzy-supervised-learning algorithm are employed. We explore their learning capabilities in situations like modelling in a direct and inverse way, the amount of information necessary to build a good model, and the problem of selecting the information relevant to the learning process. The algorithms are analysed in an experimental system in our laboratory. We close with a simple control application for the relationship between fuzzy modelling and electromechanical systems designing a feedforward learning controller for the experimental system. (C) 1998 Elsevier Science B.V. All rights reserved.

Abstract: Electrical drives are usually modeled using circuit theory, with currents or linking fluxes chosen as state variables for its electrical part and rotor speed or position chosen for its mechanical part. Often, its internal structure contains nonlinear relations difficult to model as dead-time, hysteresis, and saturation effects. On the contrary, if the available model is accurate enough, its parameter values are generally difficult to obtain and/or be estimated in real time. Therefore, this paper investigates the use of fuzzy logic for automatic modeling electrical drive systems. An experimental system composed by a DC motor supplied from a DC-DC converter is used. We underline the unsupervised learning characteristics of the fuzzy algorithm, its memory and generalization capabilities, Some learning situations with critical effects in model performance are presented and discussed, pointing out some results and conclusions concerning the fuzzy modeling process in practice.

Abstract: A self-adaptive scheme is described for automatically tracking the temperature and saturation-dependent rotor time constant T-r in indirect vector control. This method is based on a monitoring signal injected into the process. A cross-correlation function between the monitoring signal and the speed error indicates the T-r changes in direction (increase or decrease) and magnitude. The proposed identification algorithm presents unique characteristics: it does not use current or voltage sensors; it is not motor-parameter dependent; the amplitude of the monitoring signal can be reduced but with an increase on the speed-error sensibility to control interference in drive�s performance and it works either on steady-and dynamic transient-state. it will need some load to operate but this condition is satisfied in all practical cases. Tests were conducted with a 1.2 kW four-quadrant AC drive. The adaptive indirect vector-control was implemented in a microcomputer with the motor supplied by a voltage-source inverter with current control using IGBT Experimental and simulated results using this adaptive digital scheme for different loads and values of model T-r(representing a detuned operation) are presented showing good performances.

Abstract: The electrical motion drives are more and more used in various industrial processes. The choice of the motor drive is based on power, speed, precision, and cost requirements. There are many different types of motors for motion drives application. AC and DC motors feature brushed or brushless designs are suitable for a variety of industrial applications. Speed, torque and position control are the most used motion control systems. There are many papers about switched reluctance motor speed control and torque control but few about position control. This paper pretends to contribute for the potentiality of the switched reluctance motor in position application. In the first part it is presented the theoretical concepts for motor shaft position. The second part presents a prototype implementation and experimental results when intermediate position between two poles position alignment are reached.

Abstract: In power systems, superconducting fault current limiters (SFCL) emerge as an alternative to limit the prospective short circuit currents to lower levels. The purpose of this paper is to study the influence of using superconducting devices on the transient stability of the synchronic operation and power quality. Different SFCL design and local of installation are also analyzed. Simulation studies are performed using one-machine connected to an infinite bus by two parallel lines.

Abstract: This work implements an electronic converter to supply an electric vehicle powered by two distinct power supplies, a battery and supercapacitors. A solution for the implementation of the electronic converter in the electric vehicle (in this case a bicycle) is developed. The control system of the electronic converter is built regarding the vehicle�s optimal functioning and to increase its autonomy. Based on the implemented system, experimental results are shown and the advantages and disadvantages of this solution are analyzed.

Abstract: The Switched Reluctance Machine (SRM) was, during the last decade, target of the attention of researchers. Some studies stand out the application potentialities of the machine another�s developed the machine design for better performance in terms of efficiency, good torque and speed behavior. Others denote the possibility of good machine functioning without the position sensor and there are still others presenting a way to reduce the noise produced in dynamic regimen. However, there are very few works about the analysis of the machine behavior regarding its shaft position. This work presents sonic results in this thematic, studying and analyzing its geometry and torque values necessary to develop when a shaft position is intended. Some methodologies are presented in order to he applied to obtain a shaft position. One of them is based on experimental results taking into account the two phases that are necessary to excite simultaneously in order to produce the immobilization of the motor shaft in one determined position.

Abstract: In this paper, a traction system useful for an autonomous Electric Vehicle of individual use is described. The developed system is constituted in a first approach by two different power sources: one is constituted by batteries or by fuel cells, and the other by supercapacitors. This paper describes a technical solution joining and accomplishing the usage of two energy storage systems in the same traction system. In the developed system, the supercapacitors run as element that store energy temporarily and that can be used to retrieve energy. Starting from the functional characteristics of typical electrical vehicles and characterization of a typical routing profile, the energy consumption is obtained. In order to characterize and design the system, this is described in detail, namely the supercapacitors models, the battery, the power converters and the implemented strategy of control. According to the obtained results, a control strategy that allows an effective management of the stored energy in the system regarding the vehicle�s optimal functioning and increasing its autonomy is also presented and discussed. Based on experimental and simulation results, the advantages and disadvantages of the proposed solution are presented.

Abstract: The Switched Reluctance Machine (SW was, during this last decade, the target of various researchers� attention. Several authors have published mainly research results analysing torque ripple reduction, speed control, noise reduction, magnetic characteristics, and the SR machine operation without position sensor. However, very few works have studied the SR machine in terms of its shaft position. This paper presents this thematic. The static torque, experimentally obtained, is analysed followed by the determination of which phases must be excited in order to immobilize the shaft Finite Element Method (FFM) is used to calculate the current values, function of the various shaft positions. Experimental tests were done in order to validate the theoretical assumptions and FEM results. Finally, the results are discussed.

Abstract: In this paper, the controller�s tuning and performance of a speed controller prototype for switched reluctance motor is presented using significant experimental tests. The system uses an on-line learning mechanism to acquire and modify, if needed, the �good� fuzzy control rules. Experimental essays are analyzed and discussed in order to reveal some advantages of having a learning speed controller for the SR machine, and also the drawbacks that the use of using these controllers can introduce to the drive system and possible ways to overcome them.

Abstract: The mostly used neuro-fuzzy motor speed control systems are time consuming and have an high computation effort when the speed reference changes gradually and the system has to learn the new operating point most of the time. In this cases a degradation of the system performance is evident has is demonstrated by experimental results in this paper. To surpass these effects, a decision and adaptation algorithm of the learning rate applied to the neuro-fuzzy control�s approach is proposed. The adaptive learning rate algorithm with the controller is tested and compared in the speed control system for an 8/6 switched reluctance motor by experimental tests. The proposed solution is explained, tested and the experimental tests are presented and discussed.

Abstract: This work presents the development of a position sensor elimination technique of a switched reluctance machine. Details of the Neuro-fuzzy system training and the system operation are presented. A speed range online training confirms the good performance of the presented technique. In this work the proposed model of the position sensor elimination is verified experimentally. Real cases are presented and prove the trustworthiness of the model.

Abstract: This article has the objective to present a brief revision of the techniques more generally used in the position sensor elimination in a Switched Reluctance Motor. For each speed level, different techniques are indicated for a good system operation. A new technique of position sensor elimination is presented, based in intelligent techniques with neural nets and fuzzy logic. It uses only phase voltages and the reference current signals to obtain the speed/position estimation. Experimental and simulation results are presented showing its good performance.

Abstract: This paper describes the systematic procedure for designing a MOSFET power converter for an 8/6-switched reluctance machine. Starting from establishing its topology and subsystems, a Matlab simulation approach is initially developed to design its driving circuits, test different converter operating modes, and phase current controllers. Experimental tests are performed to verify the converter functionality and performance, comparing, correcting and discussing the results obtained with simulation analysis.

Abstract: This paper describes the step-by-step procedure for modeling an 8/6 switched reluctance machine. Starting from establishing the geometry of the machine, a finite element modeling approach is initially developed to compute the flux linkage/current/rotor position relationship extracting proper and mutual inductances, also its torque and field distribution characteristics. Experimental tests are performed to obtain the magnetic characteristics of the machine, comparing, correcting, and discussing the results obtained with those of FEM analysis.

Abstract: This paper initially discusses the learning methodologies as an underlay approach that advances several applications in power electronics and drive systems. Two applications of learning techniques based on fuzzy logic and neural networks are presented as examples of intelligent electrical drives. Initially, an adaptive learning speed control of a PMSM drive is designed, simulated and implemented. A second example deals with neuro-fuzzy control of a SR drive to reduce pulsating torque. Those techniques are corroborated by both simulation and experimental results, achieving good performance results and fast dynamic response.

Abstract: Each day that passes, the electrical drives operation conditions become more demanding. The use of switched reluctance motors (SRM) has magnified sufficiently with the intelligent control strategies improvement for torque ripple minimization. Another important subject is the sensors elimination, allowing that the price of the equipment is reduced. In this work, two new automatic on-line control schemes to minimize the torque ripple in SRM are presented. The first scheme is using the sensor torque, to read the information about this signal, and the second is implemented without sensor. Also, the neuro-fuzzy algorithm is presented and simulated results for two speed references are show.

Abstract: This paper describes two approaches for fault detection: an immune-based mechanism and a formal language algorithm. The first one is based on the feature of immune systems in distinguish any foreign cell from the body�s own cell. The formal language approach assumes the system as a linguistic source capable of generating a certain language, characterised by a grammar. Each algorithm has particular characteristics, which are analysed in the paper, namely in what cases they can be used with advantage. To test their practicality, both approaches were applied on the problem of fault detection in an induction motor.

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