Silicon carbide (SiC) devices provide significant performance improvements in many aspects, including lower
power dissipation, higher operating temperatures, and faster switching, compared to conventional Si devices. All these
features helped increase the interest in the applications of these devices for electric drive systems. The inclusion of an impedance network to elevate DC voltage would improve performance of an electric-traction system, because the topologies of impedances networks can eliminate the need of a DC-DC converter. However, it is important to know control methods that applicable to this type of topologies to systems that are more efficient. This paper presents the analysis of a control method in a power converter topology using SiC devices with an impedance network to elevate DC voltage for electric traction applications. The proposed analisys includes the implementation of a control method in Current Fed Quasi-Z topology, with 100 kHz switching frequency, and its analysis using the simulation of the control method, the power losses in SiC devices and the stress on passive components in the impedance network. Finally, the obtained results are compared with a conventional Current Fed Quasi-Z topology built with silicon devices at a low switching frequency (2 KHz).
Fernández, E.; Paredes, A.; Sala, V.; Romeral, L. International Conference on Power Engineering, Energy and Electrical Drives p. 464-470 DOI: 10.1109/CPE.2017.7915216 Data de presentació: 2017-04-06 Presentació treball a congrés
this paper presents the comparative analysis of power converters topologies with impedance source. The analysis consist in the comparison between two power converter topologies: the first topology is a current source inverter (CSI) that incorporates SiC devices with Quasi-Z source impedance; the second topology is CSI power converter built using SiC devices that incorporates Trans-Z source impedance. Both power converters operate with a switching frequency of 100 KHz. The use of SiC devices allows the converters to operate at higher frequency and to reduce the power losses. Additionally, it would allow the reduction of volume and weight of the elements of the source impedance. The goal of this article is to present an analysis of power losses, stress, volume and weight of the passive elements of the SiC proposed topologies using simulations and to compare them with conventional Si devices topologies with Quasi-Z and Trans-Z source impedance. The switching frequency in these topologies was set to 20 KHz in order to validate and demonstrate the advantages of SiC devices.
The operation of current source inverters at high frequency allows to reduce the size of the input coil and output filters. These advantages allowed to obtain converters with better performance and to reduce the size and weight of the passives elements, decreasing the manufacturing costs and while keeping the current harmonic distortion low. For these reasons, it is necessary to implement a modulation technique that allows the converter to work at a higher frequency 100 KHz.
This article presents the design and implementation of a Space Vector Modulation (SVM) technique for high switching frequencies for a Current Source Inverter (CSI) topology implemented with SiC devices. The technique is programmed and implemented in a PIC 24FJ256GA406 microcontroller, for the activation and control of SiC devices in each leg of power converter.
Paredes, A.; Sala, V.; Ghorbani, H.; Romeral, L. Annual Conference of the IEEE Industrial Electronics Society p. 3172-3177 DOI: 10.1109/IECON.2016.7793222 Data de presentació: 2017-02-24 Presentació treball a congrés
A novel active gate driver (AGD) for silicon carbide (SiC) MOSFET is studied in this paper. The gate driver (GD) increases the gate resistance value during the voltage plateau area of the gate-source voltage, in both turn-on and turn-off transitions. The proposed AGD is validated in both simulation and experimental environments and in hard-switching conditions. The simulation is evaluated in MATLAB/Simulink with 100 kHz of switching frequency and 600 V of dc-bus, whereas, the experimental part was realised at 100 kHz and 100 V of dc-bus. The results show that the gate driver can reduce the over-voltage and ringing, with low switching losses.
Michalski, T.D.; Lopez, C.; Garcia, A.; Romeral, L. Annual Conference of the IEEE Industrial Electronics Society p. 1-6 DOI: 10.1109/IECON.2016.7793740 Data de presentació: 2016-10-27 Presentació treball a congrés
This paper deals with the realization of a sensorless five phase permanent magnet synchronous motor (PMSM) drive based on extended Kalman filter (EKF). The vector control for five phase AC machine is applied on dq1dq3 rotor reference planes and structure of the observer is extracted on the fixed stator reference frames of the first and third harmonics. The zero sequence component may also be incorporated in the state vector in order to facilitate fault tolerant operation.
Michalski, T.D.; Lopez, C.; Garcia, A.; Romeral, L. Annual Conference of the IEEE Industrial Electronics Society p. 1-6 DOI: 10.1109/IECON.2016.7793256 Data de presentació: 2016-10-26 Presentació treball a congrés
Sala, E.; Zurita, D.; Kampouropoulos, K.; Delgado Prieto, M.; Romeral, L. Annual Conference of the IEEE Industrial Electronics Society p. 4002-4007 DOI: 10.1109/IECON.2016.7793491 Data de presentació: 2016-10-26 Presentació treball a congrés
Buildings often operate under inefficient conditions and configurations due to their complex dynamics, a necessity of in-depth knowledge and intricate analysis tools. The fact is that interest in proposing higher order approaches for tackling efficiency problems in buildings has been steadily increasing during recent years. A wide range of approaches are being demonstrated, from model-predictive control schemes to frameworks for the detection of anomalies in energy consumption. Occupancy-centric methodologies, in particular, present one of the avenues with greatest potential of improvement because of their ability to adapt the behavior of the building to the real necessities of the users. This paper presents a novel occupancy modeling and forecasting methodology with the capability to support downstream demand-side management tools by providing accurate insight regarding the occupancy of spaces in the building. The proposed methodology takes advantage of the availability of presence detectors located on the different spaces of the building to study their dynamics and autonomously map their behavior. The complete methodology is validated experimentally in terms of accuracy and performance using real data from a research building.
Kampouropoulos, K.; Andrade, F.; Sala, E.; Garcia, A.; Romeral, L. Annual Conference of the IEEE Industrial Electronics Society p. 3990-3995 DOI: 10.1109/IECON.2016.7793570 Data de presentació: 2016-10-26 Presentació treball a congrés
Due to the climate change and the decrease in fossil fuel reserves, the industrial and tertiary sectors have been focused on the implementation of advanced energy management systems in order to improve their energy efficiency and reduce their overall emissions. One way to achieve that goal, which is also the focus of this work, is by optimizing the energy use in their operation processes. This paper presents a hybrid optimization method, combined by neuro-fuzzy inference systems and the quadratic programming optimization method, to calculate the short-term demand forecasting of a multi-carrier energy system and to optimize its energy flow. The objective of the optimization is to fulfill the system's energy demands and minimize a set of established optimization criteria. Moreover, the algorithm considers the system's dynamics and inertias in order to guarantee that the obtained results present a feasible and stable operation strategy for the energetic plant. The method has been applied and validated under real conditions in a car manufacturing plant of Spain, in the framework of a FP7 European research project using online production and consumption data.
Sala, E.; Kampouropoulos, K.; Delgado Prieto, M.; Romeral, L. Annual Conference of the IEEE Industrial Electronics Society p. 3978-3983 DOI: 10.1109/IECON.2016.7794112 Data de presentació: 2016-10-26 Presentació treball a congrés
The increasing ubiquity of sensing and metering devices in buildings is a gateway of opportunities for the analysis of their behavior and the detection of anomalies or sub-optimal performance. In particular, the instrumentation of HVAC equipment, necessary for its monitoring and control, may be used in order to supervise its operation at a finer level. The intelligent supervision methodology proposed in this paper allows the accurate overseeing of the power consumption of HVAC equipment by means of establishing the relationship between the power consumed and the operating status of the installation, and its individual machines. The accurate correlation between the instantaneous power and the available control or state signals of the equipment, simultaneously with other support variables, allows detecting malfunctions or deviations from their nominal operation. First, a model of the power demand of the installation is obtained by means of a training function. Afterwards, the model can be applied in real-time over new samples in order to check if the power demand corresponds to the state of operation of the installation. In addition to the accurate tracking of the power demand, the chosen approach allows to monitor the installation with a single power meter, therefore decreasing the cost of implementation. Finally, this methodology has been validated by means of experimental data from a pilot plant where the complete system has been implemented.
This paper proposes a methodology for optimal design of Permanent Magnet assisted Synchronous Reluctance Motor. The magnetic model is explained because the particularities associated to high magnetic saturation regions this motor has, which lead to difficulties in inductance calculation. Hence, the finite element analysis is currently used to design and optimize Permanent Magnet assisted Synchronous Reluctance Motor, from the first. This method requires a high amount of computational time and resources. For this reason, the magnetic model explained in this paper is a good alternative to introduce on optimal design process. The magnetic model proposed is based on reluctance network and takes into account the magnet effects and the possibility of structural ribs on motor design.
Ghorbani, H.; Sala, V.; Paredes, A.; Romeral, L. Annual Conference of the IEEE Industrial Electronics Society p. 3547-3551 DOI: 10.1109/IECON.2016.7793741 Data de presentació: 2016-10-24 Presentació treball a congrés
This paper presents a new active gate control (AGC) approach for improving the switching behavior of insulated gate bipolar transistors (IGBTs). The proposed controller is applied on the gate driver (GD) of IGBT, which is based on Posicast control method. The reduction of stress in transient conditions without harmful effect on the efficiency is the main objective of this research that is accomplished by a simple feed-forward controller.
The effectiveness of the proposed gate drive controller is verified by both MATLAB/Simulink and PSIM softwares. Moreover, the new GD is implemented in the experimental setup, an
d the results are reflected in this paper.
Fernández, E.; Paredes, A.; Romeral, L.; Sala, V. International Power Electronics and Motion Control Conference p. 267-272 DOI: 10.1109/EPEPEMC.2016.7752009 Data de presentació: 2016-09-27 Presentació treball a congrés
This article presents the analysis of two topologies
of power converters. Voltage Source Inverter (VSI) and Current
Source Inverter (CSI) proposals for traction system applications,
these topologies are implemented with silicon carbide devices.
The use of SiC semiconductors allow working at high switching
frequency (100KHz), increase the working temperature range
and decreasing power losses during conduction and activation of
The objective is analyze these topologies and select the one that
provides the best performance and behavior at high frequency
to improve it on a electric traction system.
Ghorbani, H.; Sala, V.; Paredes, A.; Romeral, L. European Conference on Power Electronics and Applications p. 1-7 DOI: 10.1109/EPE.2016.7695436 Data de presentació: 2016-09-07 Presentació treball a congrés
This paper proposes a novel insulated gate bipolar transistor (IGBT) gate driver. The new gate driver
(GD) has positive effect on the injected gate current to enhance the IGBT switching mechanism. The
approach is based on the Posicast control method. The simple structure is the most important advantage of
this feedforward controller. The main objective is to improve turn-on switching transients without
harmful effect on the IGBT efficiency. The electromagnetic interface (EMI) reduction has been
discussed as another important benefit of this control method.
Lopez, C.; Michalski, T.D.; Garcia, A.; Romeral, L. International Conference on Electrical Machines p. 2052-2058 DOI: 10.1109/ICELMACH.2016.7732805 Data de presentació: 2016-09-06 Presentació treball a congrés
An optimal design for a rotor of SynRM is proposed on this paper. The inductances of the machine computed in dq-axes allow determining machine performance and the motor behavior. High magnetic saturation on this kind of motor increases the difficulty of inductance calculation. Hence, the finite element analysis is currently used to design and optimize SynRM, from the first instance. This method usually requires a high amount of computational time and resources. For this reason, the reluctance network here proposed is a good alternative to consider for designing these motors, because it is a fast and good method to obtain the inductances of the SynRM. Therefore, an optimal design avoiding FEA is proposed on this paper using the reluctance network to calculate the dq-axes motor inductances.
Lopez, C.; Michalski, T.D.; Garcia, A.; Romeral, L. International Conference on Electrical Machines p. 1915-1921 DOI: 10.1109/ICELMACH.2016.7732785 Data de presentació: 2016-09-05 Presentació treball a congrés
A novel motor design methodology and optimization is proposed, which is applied to a SRM. It greatly reduces the finite element analysis use. A multi physics study is realized in order to couple the thermal, magnetic and electric motor analysis. Then, the information obtained with this study allows creating different behaviors maps in order to evaluate the motor in all operating area. With the joule and iron losses, the thermal network obtains a temperature map for each current and angular speed. Then, the electric model uses the parameters obtained on reluctances network and the phase resistance variation obtained on thermal lumped parameter. Finally, the optimal motor obtained is validated on FEA. To sum up, the motor design is obtained using multi physics analysis taking into account different operating points, i.e. it is a range operation optimization. In addition, reducing FEA computation time is achieved with the methodology proposed.
Sala, E.; Kampouropoulos, K.; Delgado Prieto, M.; Romeral, L. IEEE International Conference on Emerging Technologies and Factory Automation p. 1-6 DOI: 10.1109/ETFA.2016.7733568 Data de presentació: 2016-09 Presentació treball a congrés
This paper presents a load disaggregation method for the monitoring and supervision of the load profiles
of individual equipment in an HVAC installation. The method takes advantage of the wealth of sensor and actuation
information found in Building Energy Management Systems in order to find correlations between the state of operation
of each machine and the power demand of the installation. This enables to model the individual power of the
equipment on account of their state, and in combination with other support variables that influence their load demand,
such as weather conditions. The resulting array of equipment models can be evaluated in real-time to infer the
expected power consumption of each machine. Then, allowing the tracking of their individual power consumption while
at the same time significantly lowering the cost of the acquisition and monitoring infrastructure, because a single power
meter can be used to accurately monitor several machines when following this approach. The presented method has
been validated by means of experimental data from a pilot plant where the complete system has been implemented.
Giacometto, Francisco javier; Capelli, F.; Sala, E.; Riba, J.; Romeral, L. Annual Conference of the IEEE Industrial Electronics Society p. 003957-003962 DOI: 10.1109/IECON.2015.7392717 Data de presentació: 2015-11-11 Presentació treball a congrés
A wide study regarding the suitability of data-driven modelling applied to the prediction of thermal convection responses on substation connectors is presented in this paper. The study starts with the compilation of a database with thermal profiles obtained from a finite element method simulation (FEM). Afterwards, we applied partitioning methods in order to increase the number of data sets used for modelling and later evaluate the stability of the learning algorithms. After the modeling process, the accuracy of the model per each data set is measured and the statistics about the errors are analyzed. Normality test are applied to measure the error variance. They bring us information about the error distribution and the stability of the learning algorithms. The study finish when it probes that any data-driven model is computationally less time expensive than any FEM simulation running on this study. Experimental work also confirms that the accuracy of the data-driven models: cascade feed forward neural network and feed forward neural network, can replace the FEM simulations; providing a high accuracy and a low error variance while speeding up the simulation time.
Giacometto, Francisco javier; Kampouropoulos, K.; Romeral, L. Annual Conference of the IEEE Industrial Electronics Society p. 5087-5094 DOI: 10.1109/IECON.2015.7392898 Data de presentació: 2015-11-09 Presentació treball a congrés
Currently, the Cartesian Genetic Programming
approaches applied to regression problems tackle the evolutive strategy from a static point of view. They are confident on the evolving capacity of the genetic algorithm, with less attention being paid over alternative methods to enhance the generalization error of the trained models or the convergence time of the algorithm. On this article, we propose a novel efficient strategy to train models using Cartesian Genetic Programming at a faster rate than its basic implementation. This proposal achieves greater generalization and enhances the error convergence. Finally, the complete methodology is tested using
the Australian electricity market as a case study.
Currently, the Cartesian Genetic Programming
approaches applied to regression problems tackle the evolutive
strategy from a static point of view. They are confident on the
evolving capacity of the genetic algorithm, with less attention
being paid over alternative methods to enhance the
generalization error of the trained models or the convergence
time of the algorithm. On this article, we propose a novel efficient
strategy to train models using Cartesian Genetic Programming at
a faster rate than its basic implementation. This proposal
achieves greater generalization and enhances the error
convergence. Finally, the complete methodology is tested using
the Australian electricity market as a case study.
This paper presents a design tool for Induction
Machines, Permanent Magnet Synchronous Machines,
Externally Excited Synchronous Machines and
Switched Reluctance Machines. This software, based
on Modelica language, is able to provide full
dimensioning (cross and axial section measures) and
operation characteristics according to mechanical and
electrical requirements set as inputs. The tool is able to
perform error handling, which informs a designer about
unfeasible designs and gives clues about the possible
errors. Both aspects of the tool GUI and scripts provide
help files and code explanation in order to re-use the
tool and improve library’s functionalities.
Lopez, C.; Sala, E.; Garcia, A.; Romeral, L. IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives p. 1-7 DOI: 10.1109/DEMPED.2015.7303712 Data de presentació: 2015-08-28 Presentació treball a congrés
Synchronous Reluctance Motors have always been an alternative to more mainstream machines such as the Permanent Magnet Synchronous Motor, but until recently they have not found their right place in industrial applications. This progressing adoption begins with the replacement of the current solutions, but this presents the design challenge of finding a surrogate which conforms to the specifications for a given application. In order to overcome this challenge, an evolutionary design methodology for SynRM is presented. The proposed approach uses a set of design constraints to maximize the mechanical power of the motor taking into account the specified rated speed. Since the calculation of the torque of the motor is critical, an iterative method for the evaluation of iron losses has been introduced. Finally, the proposed approach is validated by means of FEM simulation and the calculation of the efficiency map of the results.
Sala, E.; Zurita, D.; Kampouropoulos, K.; Delgado Prieto, M.; Romeral, L. IEEE International Conference on Industrial Technology p. 1299-1304 DOI: 10.1109/ICIT.2015.7125277 Data de presentació: 2015-05-17 Presentació treball a congrés
Sinusoidally fed permanent magnet synchronous motors (PMSM) fulfill the special features required for traction
motors to be applied in electric vehicles (EV). Among them, axial flux permanent magnet (AFPM) synchronous motors are
especially suited for in-wheel applications. Electric motors used
in such applications must meet two main requirements, i.e. high power density and fault tolerance. This paper deals with the
optimal design of an AFPM for in-wheel applications used to drive an electrical scooter. The single-objective optimization
process carried out in this paper is based on designing the AFPM to obtain an optimized power density while ensuring appropriate fault tolerance requirements. For this purpose a set of analytical
equations are applied to obtain the geometrical, electric and mechanical parameters of the optimized AFPM and several design restrictions are applied to ensure fault tolerance capability. The optimization process is based on a genetic
algorithm and two more constrained nonlinear optimization algorithms in which the objective function is the power density.
Comparisons with available data found in the technical bibliography show the appropriateness of the approach
developed in this work.
Kampouropoulos, K.; Sala, E.; Andrade, F.; Romeral, L. Annual Conference of the IEEE Industrial Electronics Society p. 202- DOI: 10.1109/IECON.2014.7048503 Data de presentació: 2014-11 Presentació treball a congrés
This paper presents an energy optimization methodology applied on industrial plants with multiple energy carriers. The methodology combines an adaptive neuro-fuzzy inference system to calculate the short-term load forecasting of a plant, and the sequential quadratic programming algorithm to optimize its energy flow. Furthermore, the mathematical models of the plant's equipment are considered into the optimization process, in order to calculate the dynamic system response and the equipment's inertias. The final algorithm optimizes the operation of the plant in order to satisfy the energy demand, minimizing several optimization criteria. The methodology has been tested and evaluated in an automotive factory plant using real production and consumption data.
Sala, E.; Kampouropoulos, K.; Giacometto, Francisco javier; Romeral, L. Annual Conference of the IEEE Industrial Electronics Society p. 288-294 DOI: 10.1109/IECON.2014.7048513 Data de presentació: 2014-11 Presentació treball a congrés
A model of power demand represents the foundation of any intelligent Energy Management System, and its accuracy is the key factor determining the performance of such system. In order to improve the accuracy of the modeling process, a multi-model approach based on a Hierarchical Clustering of similar load behaviors is presented. The clustering algorithm joins similar data subsets in groups that are modelled separately using Adaptive Neuro-Fuzzy Inference Systems. Thus, each of the obtained models addresses only the characterization of one behavior, which provides better accuracy than classical approaches based on a single model, in addition to being easier and faster to train. During the training process of the models, an input selection technique based on Genetic Algorithms is proposed to search and select the best combination of inputs. The use of search algorithms allows to reduce the complexity of this task while maintaining the system performance, which represents a significant time saving of expert staff. The proposed approach is validated by means of experimental data from an automotive manufacturing plant. In addition to improving the forecasting accuracy, this methodology automates the segmentation of the load profiles into models and the selection of their inputs, as well as improving parallelization to effectively reduce the computation time.
Andrade, F.; Kampouropoulos, K.; Romeral, L.; Vasquez , J.C.; Guerrero, J. Annual Conference of the IEEE Industrial Electronics Society p. 1840-1846 DOI: 10.1109/IECON.2014.7048752 Data de presentació: 2014-10-30 Presentació treball a congrés
This document analyses the large-signal stability for an inverter-based generator such as photovoltaic and wind power sources. The objective of this study is to determine the stability region taking into account the electrical and control signal of the generator. The generator uses the concept of the electrostatic machine for the model of the generator. Finally, the applied procedure to find the Lyapunov's function is the Popov method, which not only permits to generate a valid function but also to determine the stability region of the system.
Moreno-Eguilaz, J.M.; Garcia, A.; Riba, J.; Ortega, J.A.; Romeral, L.; Hernandez, E. Congrés Internacional de Docència Universitària i Innovació Data de presentació: 2014-07-02 Presentació treball a congrés
Se describe una experiencia docente pionera basada en el clásico concepto“learning-by-doing”, en la que diseño e ingeniería se unen para obtener un producto de mercado. En concreto, se describen los retos planteados así como las dificultades encontradas por el equipo ETSEIB-ELISAVA, procedentes de la Universidad Politécnica de Cataluña y de la Universidad Pompeu Fabra, respectivamente, que consiguió el premio al diseño en la primera edición de la competición Barcelona Smart Moto Challenge.
In this paper the effect of the magnets shape on the AFPMM performance under a demagnetization fault has been analyzed by means of 3D-FEM simulations. Demagnetization
faults in permanent magnet synchronous motors (PMSMs) may generate specific fault harmonic frequencies in the stator currents, output torque and the zero-sequence voltage component (ZSVC) spectra the ones can affect motor behavior, and so these parameters have been studied and compared, for each magnet
configuration in each condition. These analyses are carried out to find out the more suitable geometry for an operation under
healthy and faulty condition.
This paper deals with model predictive control of five phase permanent magnet motors. Using motor model, the stator
currents are estimated for the following modulation period, and the required voltages are applied to minimize the current errors.
A comparison between the proposed algorithm and conventional cascade PI configuration is conducted.
This study is dealt with fault tolerant control of five phase permanent magnet (PM) machines. The main objectives are to increase the output power while eliminating the generated torque ripples. As a new aspect, the effect of available neutral
connection is evaluated on the output power and torque ripples.
This paper deals with the effects of inter-turn short circuit faults in five-phase permanent magnet synchronous motors (PMSMs). For this purpose a finiteelements model (FEM) of a faulty machine with 1, 2 and 4 inter-turns in short circuit is analyzed. From the results of this
model the effects of these fault severities in the stator currents and zero-sequence voltage components (ZSVC) harmonics is
analyzed and the possibility of developing a fault diagnosis scheme based on the changes in their spectral content is exposed. Moreover, the effect of the fault severity on the total power losses in the machine is presented. Inter-turn faults generate large circulating currents which may lead to
catastrophic failures. Therefore it is very important to know the increase in power losses in the machine due to the occurrence of such faults for applying corrective actions at the precise time once the fault has been diagnosed.
Salehi Arashloo, R.; Romeral, L.; Salehifar, M. IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives p. 650-657 Data de presentació: 2013-08-29 Presentació treball a congrés
Detection of broken rotor bars has been an
important but difficult work in fault diagnosis area of induction motors. The characteristic frequency components of faulted rotor are very close to the
power frequency component but by far less in
amplitude, which brings about great difficulty for accurate detection.
In the present study, a new method is proposed in order to remove the main frequency component, resulting in more efficient detection of the rotor
fault characteristics in the frequency spectrum of stator currents. The method is based on Park’s transformation in combination with discrete wavelet decomposition to eliminate the effect of
main frequency and zoom on the energy of
objective fault related frequency components. In addition, the method efficiency is evaluated using Simulations in Matlab.
Zurita, D.; Delgado Prieto, M.; Ortega, J.A.; Romeral, L. IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives Data de presentació: 2013-08-28 Presentació treball a congrés
The development of intelligent and autonomous monitoring systems applied to rotating machinery, represents the evolution towards the automatic industrial plants supervision. In this regard, an acoustic emission based intelligent sensor is presented in this work. The proposed sensor records regularly the acoustic emission signal generated by gearboxes. A time domain statistical analysis is applied in order to characterize the acquired data. Afterwards, a neural network based algorithm is applied to detect gear fault patterns. Finally, the diagnosis result is sent through a wireless transceiver to the central control unit. Moreover, in order to reach a real autonomous operation, the sensor power is approached by different energy harvesting solutions.
Salehifar, M.; Moreno-Eguilaz, J.M.; Sala, V.; Salehi Arashloo, R.; Romeral, L. IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives p. 614-621 Data de presentació: 2013-08-28 Presentació treball a congrés
A new open switch fault detection method based on normalized current analysis is proposed for application in multiphase fault tolerant PMSM drives. Performance
characteristics of proposed method are single diagnostic variable, ability to detect open phase fault without using
auxiliary variable, ability to detect multiple switch fault, simple diagnostic variable, generality, and robustness in case of high unbalanced current waveforms. Theory of diagnostic method with special multiphase drive application is developed; simulation results using Matlab/Simulink and experimental waveforms are shown to validate effectiveness of the presented fault detection method.
Salehifar, M.; Salehi Arashloo, R.; Moreno-Eguilaz, J.M.; Sala, V.; Romeral, L. IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives p. 3-10 Data de presentació: 2013-08-27 Presentació treball a congrés
In this paper, a new fault detection method based on signal normalization using a simple trigonometric function is presented and applied to a five phase converter for fault
tolerant application under nonsinusoidal unbalanced current waveforms. Generality, simplicity, ability to localize faulty
switch, multiple switch fault detection and robustness are achieved using this approach. Once theory is explained,simulation results with Matlab/Simulink and experimental
waveforms are described to show the effectiveness of the proposed detection method. Experimenal results corroborate
these simulation results.
Salehi Arashloo, R.; Romeral, L.; Salehifar, M. IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives p. 412-419 DOI: 10.1109/DEMPED.2013.6645749 Data de presentació: 2013-08 Presentació treball a congrés
Detection of broken rotor bars has been an important but difficult work in fault diagnosis area of induction motors. The characteristic frequency components of faulted rotor are very close to the power frequency component but by far less in amplitude, which brings about great difficulty for accurate detection. In the present study, a new method is proposed in order to remove the main frequency component, resulting in more efficient detection of the rotor fault characteristics in the frequency spectrum of stator currents. The method is based on Park's transformation in combination with discrete wavelet decomposition to eliminate the effect of main frequency and zoom on the energy of objective fault related frequency components. In addition, the method efficiency is evaluated using Simulations in Matlab.
Kampouropoulos, K.; Cardenas, J.; Giacometto, Francisco javier; Romeral, L. IEEE International Symposium on Industrial Electronics p. 1-6 DOI: 10.1109/ISIE.2013.6563627 Data de presentació: 2013-05-29 Presentació treball a congrés
This document presents an energy forecast methodology using Adaptive Neuro-Fuzzy Inference System (ANFIS) and Genetic Algorithms (GA). The GA has been used for the selection of the training inputs of the ANFIS in order to minimize the training result error. The presented algorithm has been installed and it is being operating in an automotive manufacturing plant. It periodically communicates with the plant to obtain new information and update the database in order to improve its training results. Finally the obtained results of the algorithm are used in order to provide a short-term load forecasting for the different modeled consumption processes.
The axial flux permanent magnet machine (AFPMM)is being increasingly demanded for special applications, particularly for transportation systems and concretely for inwheel applications. In this paper the effect of the magnets shape on the AFPMM performance has been analyzed by means of 3DFEM simulations. To this end the air-gap magnetic flux density, the back electromotive force (back-EMF), the cogging torque and the total torque waveforms of the analyzed AFPMMs with different magnets geometries have been studied and compared.
The harmonic content of all these variables has been also analyzed. These analyses are carried out to find out the more suitable geometry for in-wheel applications and particularly to minimize the torque ripple of the AFPMM.
A new mathematical model of a renewable generator,
with a DC-AC interface, based on the concept of electrostatic
machine is presented. This new model has a direct relationship
between the DC and AC side. Moreover, it can be used for
stability studies, taking into account the dynamics of the DC link
and to find saturations and limits on the control signals.
A new mathematical model of a renewable generator, with a DC-AC interface, based on the concept of electrostatic machine is presented. This new model has a direct relationship between the DC and AC side. Moreover, it can be used for stability studies, taking into account the dynamics of the DC link and to find saturations and limits on the control signals.
Bader, B.; Torres , O.; Ortega, J.A.; Lux, G.; Romeral, L. International Conference on Urban Transport and the Environment p. 397-408 DOI: 10.2495/UT130311 Data de presentació: 2013-05 Presentació treball a congrés
Due to the great weight and high costs of electric energy storage systems (ESS), the number of pure electric vehicles (EV) is increasing only slowly. As a compromise between the autonomous hybrid electric vehicle (HEV) and EV, the plug-in HEV (PHEV) allows, like the EV, the recharging of the battery by the grid but brings also a combustion engine so as not to depend on the limited electric range of the vehicle. Next to the sizing of the vehicle components, the energy management strategy has an important influence on the fuel consumption of the vehicle. To minimize fuel consumption, predictive energy management is necessary, as all stored electric energy should be consumed by the end of the trip. In this way it is possible to minimize fuel consumption by substituting as much fuel as possible by the use of electric energy. In order to reach the global optimal result, a prediction horizon of the optimization for the duration of the entire trip is necessary. However, due to model uncertainties and the limited calculation capacities of the control units in a vehicle the global optimum cannot be achieved. Therefore, measures have to be taken to reduce the computation cost on the one hand and achieve results close the global optimum on the other. One of these measures, next to an adequate optimization algorithm, is the reduction of the prediction horizon. In this study, for a real life cycle including urban and highway parts a variation of the prediction horizon is carried out and the influence on the fuel consumption is simulated. The respective results are calculated using Dynamic Programming to exclude any influence of the chosenCenergy management strategy. The results are compared to the global optimal fuel consumption of the used driving cycle.
Torres , O.; Bader, B.; Romeral, L.; Lux, G.; Ortega, J.A. International Conference on Urban Transport and the Environment p. 409-421 DOI: 10.2495/UT130321 Data de presentació: 2013-05 Presentació treball a congrés
The purpose of this paper is to study the influence of the electric motor (EM) size, final drive ratio (FD) and the battery capacity (BAT) of a parallel plug-in hybrid electric vehicle (PHEV) regarding fuel consumption. The energy efficiency of a certain vehicle drivetrain depends on the size of the components. For this reason and for cost reasons it is necessary to study the optimal dimensions of the components that minimize the fuel consumption for a given driving cycle. In this publication the influence of the size of the electric motor, final drive ratio and also the battery capacity are analysed using the Response Surface Methodology (RSM) of the Design of Experiments (DoE) technique. A parallel PHEV has been parameterized and simulated to obtain the fuel consumption over NEDC driving cycle using Modelica/Dymola. This paper contains an introduction, a brief explanation of the modelled parallel HEV, a description of the all electric range operating strategy based on rules, an explanation of the RSM method, the simulation results, and finally the conclusions of this study.
This paper proposes a predictive real time energy management strategy for plug-in- hybrid electric vehicles (PHEV) based on an adaptation of Dynamic Programming (DP). The computational load of predictive real
time strategies increases with the trip length. Therefore, for online computation by the onboard computer, they strongly depend on an efficient implementation. To reduce computation cost, current approaches for predictive strategies rely on strongly simplified intern vehicle models. The here proposed energy management strategy (EMS) uses a different approach, which is based on the use of precalculated lookup tables for the different operating points of the powertrain. This precalculation make the use of more exact vehicle models possible by using more detailed loss models of the powertrain components. The proposed EMS separates the optimization process, i.e. the calculation of the power distribution to engine and electric motor and gear in two calculation steps. The first step, which is computationally more intensive, has only to be executed once for a certain vehicle configuration. The obtained results are saved in lookup tables to avoid a later recomputation. In the second step, which is done online in the vehicle, a shortest path search algorithm is employed which is based on the predicted vehicle speed and rode slope of the trip. Techniques are integrated which decrease the rounding error caused by the use of lookup tables. The resulting difference of the consumed fuel mass between the lookup table based DP and standard DP is smaller than
0.03% by an approximately 50 times faster calculation. Using the proposed algorithm, even complex intern vehicle models do not affect the online computation cost and can be implemented by real time strategies.
The objective of this paper is to give recommendations for the component sizing of a Parallel Plug-in Hybrid Electric Vehicle (PHEV) studying the influence of the Electric Motor (EM) size, Final Drive ratio (FD), the Battery Capacity (BAT) and the Internal Combustion Engine (ICE). A multiple options for the size of the components are in the market and conflicting on the vehicle efficiency and functionality. Their selection is very important in order to achieve reduced fuel consumption and assure the vehicle performance with the minimum cost. This study explains a proposal methodology to solve this problem, firstly doing a problem model approach, then reducing his complexity doing a parameterization and finally analyzing the optimal variables for the multiple objectives. In this publication the component sizing is analysed using the Response Surface Methodology (RSM) of the Design of Experiments (DoE) technique. The parallel HEV has been parameterized and simulated to obtain the fuel consumption over NEDC driving cycle using Modelica/Dymola . This tool is very useful for modeling and simulating complex integrated systems, for the automotive, aerospace, robotics and other applications. This paper contains an introduction, a brief explanation of the Parallel HEV modeled, a description of the all electric range operating strategy based on a rules, an explanation of the RSM method, the simulation results, and finally the conclusions of this study.
This paper presents the analysis and design of a new high frequency ac-ac converter applied to domestic induction heating. The proposed topology uses only four switches to
control power. Converter operation is same as a conventional class D inverter. Working above the resonant frequency, a sinusoidal input current and a unit power factor are obtained. To bring higher efficiency and power density, application of emerging SiC technology in proposed converter has been
evaluated. The analytical and simulation results have been verified by means of a 380-W induction heating prototype.
In this paper a five phase fault tolerant converter is proposed for permanent magnet (PM) drives. The proposed configuration is an extension of conventional three phase double switch redundant topologies. In contrast to three phase systems,the proposed configuration has more flexibility and reliability regarding simultaneous faults in more than one phase. Different faulty cases are explained. Optimal reconfiguration strategies are derived under several faulty conditions. Design criteria are defined and a comparative loss analysis is conducted on
converter behavior under various conditions. Simulation results are included to validate the theory.
Con el objetivo de que el funcionamiento de una máquina sea el correcto es imperativo
asegurar que existe un buen mantenimiento predictivo. Es conveniente tener un sistema
inteligente y dispositivos capaces de detectar fallos en fases tempranas. Los fallos más
comunes en máquinas industriales son todos aquellos relacionados con los sistemas de
transmisión de potencia. La técnica de emisión acústica (EA) es el último enfoque para
detectar e identificar defectos en rodamientos, cajas de cambio y uniones mecánicas.
La emisión acústica (EA) es el fenómeno de generación de ondas elásticas transitorias
en materiales bajo tensión. Cuando el material está sometido a un cierto nivel de
tensión, una liberación rápida de energía de deformación tiene lugar en forma de
ondas elásticas, las cuales pueden ser detectadas mediante transductores colocados en
la pieza en cuestión.
El objetivo de este trabajo es proporcionar una caracterización de las ondas elásticas
que emanan de grietas localizadas entre el flanco y el valle de un engranaje. Las
señales han sido registradas usando transductores colocados en la superficie del
engranaje (a media distancia entre el eje y los dientes).
El método de los elementos finitos ha sido utilizado para simular las ondas elásticas
emitidas durante el crecimiento de las grietas. El modelo de simulación está basado en
suposiciones elásticas y se ha llevado a cabo mediante Abaqus. Estos resultados han
sido comparados con los resultados experimentales.
In order to have a machine that functions well it is imperative to ensure that there is a
good predictive maintenance. An intelligent system and devices able to detect the fault
in its early stage is then convenient. The most common failures in industrial machines
are those related to the power transmission systems. Acoustic Emission (AE) is the
latest approach in detecting and identifying faults in bearings, gearboxes and
mechanical couplings. Acoustic Emission (AE) is the phenomenon of transient elastic
wave generation in materials under stress. When the material is subjected to stress at a
certain level, a rapid release of strain energy takes place in the form of an elastic wave
which can be detected by transducers placed on it. The objective of this work is to provide a characterization of elastic waves emanating
from cracks located between the flank and the valley of a gear. The signals have been
recorded using transducers attached to the surface of the gear (midway between the
shaft and the teeth).
FE modeling has been used to simulate the elastic waves emitted from fatigue crack
growth. The model is based on linear elasticity assumptions and undertaken using
Abaqus. These results have been compared with the experimental ones.
In the last decade, the Power Amplifier applications have used multilevel diode-clamped-inverter or neutral-point-clamped (DCI-NPC) topologies to present very low distortion at high power. In these applications a lot of research has been done in order to reduce the sources of distortion in the DCI-NPC topologies. One of the most important sources of distortion, and less studied, is the reverse recovery time (trr) of the clamp diodes and MOSFET parasitic diodes. Today, with the emergence of Silicon Carbide (SiC) technologies, these sources of distortion are minimized. This paper presents a comparative study and evaluation of the distortion generated by different combinations of diodes and MOSFETs with Si and SiC technologies in a DCI-NPC multilevel Power Amplifier in order to reduce the distortions generated by the non-idealities of the semiconductor devices.
The DCI-NPC topology has become one of the best options to optimize energy efficiency in the world of high power and high quality amplifiers. This can use an analog PWM modulator that is sensitive to generate distortion or error, mainly for two reasons: Carriers Amplitude Error (CAE) and Carriers Offset Error (COE). Other main error and distortion sources in the system is the Dead-Time (td). This is necessary to guarantee the proper operation of the power amplifier stage so that errors and distortions originated by it are unavoidable. This work proposes a negative COE generation to minimize the distortion effects of td. Simulation and experimental results validates this strategy
The DCI-NPC topology has become one of the best options to optimize energy efficiency in the world of high power and high quality amplifiers. This can use an analog PWM modulator that is sensitive to generate distortion or error, mainly for two reasons: Carriers Amplitude Error (CAE) and Carriers Offset Error (COE). Other main error and distortion sources in the system is the Dead-Time (td). This is necessary to guarantee the proper operation of the power amplifier stage so that errors and distortions originated by it are unavoidable. This work proposes a negative COE generation to minimize the distortion effects of td. Simulation and experimental results validates this strategy.
Sala, V.; Salehi Arashloo, R.; Moreno-Eguilaz, J.M.; Salehifar, M.; Romeral, L. Annual Conference of the IEEE Industrial Electronics Society p. 4941-4948 DOI: 10.1109/IECON.2012.6388988 Data de presentació: 2012-10 Presentació treball a congrés
This paper presents a study and analysis of the distorting effects of clamped diodes in multilevel DCI-NPC topology applied to high power and high quality audio-amplifier. The main distorting sources of error are characterized, which are due to the clamped-diodes non-idealities; and they are evaluated for typical commercial diodes values and working conditions. Through this study the distorting contribution of each non-ideality can be quantified, and the influence of the system operating parameters, such as reactive current angle and modulation index, are highlighted. Finally, it is presented the table of optimal parameters that a commercial diode should have to ensure proper operation of the amplifier under rated power and quality specification
This paper presents a study and analysis of the distorting effects of clamped diodes in multilevel DCI-NPC topology applied to high power and high quality audio-amplifier. The main distorting sources of error are characterized, which are due to the clamped-diodes non-idealities; and they are evaluated for typical commercial diodes values and working conditions. Through this study the distorting contribution of each non-ideality can be quantified, and the influence of the system operating parameters, such as reactive current angle and modulation index, are highlighted. Finally, it is presented the table of optimal parameters that a commercial diode should have to ensure proper operation of the amplifier under rated power and quality specification.
Giacometto, Francisco javier; Cardenas, J.; Kampouropoulos, K.; Romeral, L. Annual Conference of the IEEE Industrial Electronics Society p. 1049-1054 Data de presentació: 2012-10 Presentació treball a congrés
Salehi Arashloo, R.; Salehifar, M.; Romeral, L. Annual Conference of the IEEE Industrial Electronics Society p. 1934-1939 DOI: 10.1109/IECON.2012.6388906 Data de presentació: 2012-10 Presentació treball a congrés
on the effect