Showing papers presented at "International Symposium on Industrial Electronics in 2014"

Arabic sign language recognition using the leap motion controller

Abstract: Sign language is important for facilitating communication between hearing impaired and the rest of society. Two approaches have traditionally been used in the literature: image-based and sensor-based systems. Sensor-based systems require the user to wear electronic gloves while performing the signs. The glove includes a number of sensors detecting different hand and finger articulations. Image-based systems use camera(s) to acquire a sequence of images of the hand. Each of the two approaches has its own disadvantages. The sensor-based method is not natural as the user must wear a cumbersome instrument while the imagebased system requires specific background and environmental conditions to achieve high accuracy. In this paper, we propose a new approach for Arabic Sign Language Recognition (ArSLR) which involves the use of the recently introduced Leap Motion Controller (LMC). This device detects and tracks the hand and fingers to provide position and motion information. We propose to use the LMC as a backbone of the ArSLR system. In addition to data acquisition, the system includes a preprocessing stage, a feature extraction stage, and a classification stage. We compare the performance of Multilayer Perceptron (MLP) neural networks with the Nave Bayes classifier. Using the proposed system on the Arabic sign alphabets gives 98% classification accuracy with the Nave Bayes classifier and more than 99% using the MLP.

Mixed cells modular multilevel converter

Abstract: This paper uses a scaled down version of the mixed cells modular multilevel converter (MMC) to discuss its modulation and capacitor voltage balancing method, and investigates its AC and DC fault ride-through capability. It has been found that the mixed MMC is resilient to both AC and DC network faults, which are necessary for next generations of highly meshed multi-terminal HVDC grids. The power losses comparison conducted in this paper has shown that the mixed cells MMC and three-level cells MMC achieve DC fault reverse blocking capability at reduced on-state losses than full-bridge MMC and alternative arm MMC.

Comprehensive steady state analysis of bidirectional dual active bridge DC/DC converter using triple phase shift control

Abstract: Several papers have been published recently on TPS control of dual active bridge (DAB) converter, however, no complete study of the converter operation behaviour exists, that takes into account all switching modes in both charging and discharging (bidirectional) power transfer. In this paper, six switching modes and their complements with opposite power transfer direction are defined with their operational constraints. Exact expressions for power transferred are derived with no fundamental frequency assumptions and range of power transfer for each mode is also defined to characterize mode limitations. Detailed constraints for zero voltage switching (ZVS) are also obtained. A new definition for converter reactive power consumption is introduced. This is based on calculation of inductor apparent power which avoids fundamental frequency approximations as well as the vague negative (back flowing) power definitions in recent papers. All known DAB phase shift modulation techniques including conventional, dual and extended phase shift, represent special cases from triple phase shift, therefore the presented analysis provides a generalised theory for all phase shift based modulation techniques.

RUL prediction based on a new similarity-instance based approach

Abstract: Prognostics is a major activity of Condition-Based Maintenance (CBM) in many industrial domains where safety, reliability and cost reduction are of high importance. The main objective of prognostics is to provide an estimation of the Remaining Useful Life (RUL) of a degrading component/ system, i.e. to predict the time after which a component/system will no longer be able to meet its operating requirements. This RUL prediction is a challenging task that requires special attention when modeling the prognostics approach. In this paper, we proposes a RUL prediction approach based on Instance Based Learning (IBL) with an emphasis on the retrieval step of the latter. The method is divided into two steps: an offline and an online step. The purpose of the offline phase is to learn a model that represents the degradation behavior of a critical component using a history of run-to-failure data. This modeling step enables us to construct a library of health indicators (HI's) from run-to-failure data which are then used online to estimate the RUL of components at an early stage of life, by comparing their HI's to the ones of the library built in the offline phase. Our approach makes use of a new similarity measure between HIs. The proposed approach was tested on real turbofan data set and showed good performance compared to other existing approaches.

Grid inertial response with Lithium-ion battery energy storage systems

Abstract: The increased grid-penetration levels of energy produced by renewable sources, which have almost no inertia, might have a negative impact on the reliable and stable operation of the power system Various solutions for mitigating the aforementioned problem were proposed in the literature The aim of this paper is to evaluate the technical viability of utilizing energy storage systems based on Lithium-ion batteries for providing inertial response in grids with high penetration levels of wind power In order to perform this evaluation, the 12-bus system grid model was used; the inertia of the grid was varied by decreasing the number of conventional power plants in the studied grid model while in the same time increasing the load and the wind power penetration levels Moreover, in order to perform a realistic investigation, a dynamic model of the Lithium-ion battery was considered and parameterized All the studies were performed in real time on a laboratory setup composed of RTDS and dSPACE platforms

Comparative study of Series-Series and Series-Parallel compensation topologies for electric vehicle charging

Abstract: Loosely coupled inductive power transfer (IPT) systems have recently gained enormous attention for electric vehicle (EV) battery charging. For EV battery charging, a constant-current source is required. Numerous published papers suggest that the secondary of loosely coupled IPT systems, if series compensated, can act as constant-voltage source; and, if parallel compensated, it can act as constant-current source. In this paper, the authors prove that both series as well as parallel compensated secondary can act as constant-current source as well as a constant-voltage source, depending on the nature of power supply. Hence, either of the topological options can be utilized efficiently for EV charging. The authors intend to present the work for the case where primary is in the form of a long track, such as in a mono-rail or electric traction metro system. Hence, the primary is always considered to be series compensated.

Cascaded multilevel inverter with multicarrier PWM technique and voltage balancing feature

Abstract: Multilevel inverters generate low harmonic waveforms at the output, which makes them suitable for high voltage energy conversion scheme to deliver efficient high power to the loads from renewable energy sources like photovoltaic systems which are penetrating to the electric grid nowadays, significantly. In this paper a single-phase hybrid multilevel inverter based on cascading full bridge and half bridge cells is introduced. Moreover the associated switching technique with multicarrier PWM is designed to generate five-level voltage at the output. As well, the designed switching technique allows the capacitors of the half bridge cell to have balanced voltage despite load changes. Furthermore, this study is extended to more cells using unequal DC sources to produce more voltage levels. Simulations have been performed on two and three cells to demonstrate the efficiency of the presented cascaded inverter with equal and unequal DC sources and switching technique.

Multi-dimension diode photovoltaic (PV) model for different PV cell technologies

Abstract: Different types of photovoltaic (PV) cell technologies have been commercially used for various applications. These cell technologies can be categorized as multi-crystalline, mono-crystalline and thin film. Due to the differences in PV cell technologies, a single PV model is unable to model all the output characteristics. The single and double diode PV models have been widely used for modeling the output characteristic of a PV module. This paper introduces a generalized multi-dimension diode PV model which can be used to select the most suitable dimension for a particular PV cell technology. The results confirm that the single diode PV model is suitable for the multi-crystalline and mono-crystalline PV modules. For the thin film PV module, a multi-dimension diode PV model is required to achieve a low modeling error.

Development of the intelligent charger with battery State-Of-Health estimation using online impedance spectroscopy

Abstract: In this research, a novel intelligent charger with battery diagnosis function is proposed. The diagnosis function is implemented by way of impedance spectroscopy achieved by controlling the charger to create a frequency swept excitation voltage at the battery terminals with no additional hardware. The impedance variation of battery according to the degradation over the life is measured and used for evaluating the State-of-Health (SOH) of the battery. The voltage perturbation and the current response of the battery are measured by the digital lock-in amplifier embedded in the digital signal processor (DSP) in order to calculate the impedance of the battery. The parameters of the equivalent circuit model for the lead-acid battery are extracted by using the complex non-linear least square method and compared to the reference values to estimate the SOH of the battery. The design procedure of the proposed charger is detailed and the feasibility of the system is verified by the experiments.

An advanced energy management of microgrid system based on genetic algorithm

Abstract: Immense growth has happened in the field of microgrid (MG) and the energy management system (EMS) methods in the past decade. It is estimated that there is still a huge potential of growth remaining in the field of EMS in the coming years. The main role of EMS is to autonomously determine hour-by-hour the optimum dispatch of MG and main grid energy to satisfy load demand needs. This paper is focused on developing an advanced EMS model able to determine the optimal operating strategies regarding to energy costs minimization, pollutant emissions reduction, MG system constraints and better utilization of renewable resources of energy such as wind and photovoltaic through daily load demand. The proposed optimization model of EMS is formulated and solved based on genetic algorithm (GA). The efficient performance of the algorithm and its behavior is illustrated and analyzed in detail considering winter load demand profile.

Generalized classification of PV modules by simplified single-diode models

Abstract: This paper proposes a theoretical study supporting the use of simplified single-diode photovoltaic (PV) models to accurately reproduce the behaviour of PV generators. In particular, a newly defined parameter is introduced, which allows to classify PV modules according to the possibility to neglect either the series- or the shunt resistance in the circuit model. On such a basis, equations allowing to identify the nonneglected resistance and the other unknown model parameters, are derived. The resolution of such equations is non-iterative, therefore, the proposed approach is suitable for on-line parameter identification, for example for supporting a maximum power point tracking circuit. The accuracy of the proposed method is assessed by practical cases of PV model parameter extraction.

An intelligent MPPT approach based on neural-network voltage estimator and fuzzy controller, applied to a stand-alone PV system

Abstract: This paper presents an intelligent maximum power point tracking (MPPT) method for a stand-alone photovoltaic (PV) system using artificial neural networks (ANN) modelling and a fuzzy logic controller (FLC). The ANN is trained for various conditions of solar irradiance and temperature to estimate the MPP voltage. This voltage is then used by the FLC as a reference voltage to generate the appropriate control signal for the DC-DC converter. The proposed technique is implemented in Matlab/Simulink and compared with the conventional method of incremental conductance (IncCond). Simulation results show a good performance of the ANN based fuzzy MPPT controller.

Integrated voltage control and line congestion management in Active Distribution Networks by means of smart transformers

Abstract: Within the context of Active Distribution Networks (ADNs), smart transformers represent very powerful devices able to provide fast and efficient control actions with respect to different ADNs ancillary services. This paper discusses the benefits, in terms of ADNs voltage and line flows controls, achieved by interfacing distributed generators with the power grid by means of a smart transformer. Among several benefits, these devices allow for a phase-per-phase control of the generators active and reactive power injections. This peculiarity enables to deploy new control schemes that are analyzed and discussed in the paper with reference to a case study based on a modified IEEE 34 node test distribution feeder.

Power sharing for efficiency optimisation into a multi fuel cell system

Abstract: This paper presents a power splitting algorithm in order to optimize the efficiency of a multi fuel cell system. Versus a single fuel cell, such a system is modular, allows a better efficiency curve and reduces the risk of general failure. The results of the algorithm are easy to implement into a real time controller. This work presents simulation results based on an experimental power vs efficiency curve.

Optimal and secure protocols in the IETF 6TiSCH communication stack

Abstract: In order to cope with large multi-hop resource-constrained and IPv6-compliant Low-power and Lossy Networks (LLNs), based on IEEE802.15.4 radios, novel protocols have been standardized within the IETF. More recently, the IEEE802.15.4e Timeslotted Channel Hopping (TSCH) MAC amendment has been designed to meet the requirements of industrial applications, by reducing idle-listening and improving reliability in the presence of narrow-band interference and multi-path fading. To integrate this new powerful MAC within the framework of IPv6-based LLN protocols, a new IETF working group has been defined, namely “IPv6 over the TSCH mode of IEEE 802.15.4e” (6TiSCH). In a timely way, this paper presents our contribution to the early standardization efforts required to define (i) an optimal distributed scheduling technique able to allocate resources between any couple of neighbors, while seconding the minimal bandwidth requirements and avoiding collisions, and (ii) a scalable framework supporting setting-up and maintenance of secured domains. Supported by the scientific interest to this reasearch topic, we strongly believe that the 6TiSCH stack will be a viable solution for a wide gamut of optimal and secured IoT applications in industrial environments.

A survey on modeling, control, and dc-fault protection of modular multilevel converters for HVDC systems

Abstract: The modular multilevel converter (MMC) is becoming one of the most promising topology in multilevel converter series especially for high-voltage and high-power applications. This valuable features, nominates MMCs to interface high-voltage and high-power renewable energy resources into modern HVDC electric grids for more penetration of renewable energy. This paper investigates recent modelling, control, and dc-fault protection techniques that have been applied to MMCs.

An integrated battery charger for EVs based on a symmetrical six-phase machine

Abstract: A new topology for integrated on-board battery charging is proposed in this paper A symmetrical six-phase machine and inverter, which are used for propulsion, are incorporated into the charging process The configuration achieves power transfer through the machine without developing an average torque in it during the charging mode Additional degrees of freedom of six-phase machines are explained and it is shown how they can be utilized to transfer a part of the excitation from the torque producing plane into the non-flux/torque producing plane of the machine, so that rotation does not take place The advantage is that the motor does not have to be mechanically locked during the charging process The configuration is operated with a unity power factor and the appropriate control scheme is introduced for this purpose Theoretical considerations are validated by simulations for both charging and vehicle-to-grid (V2G) modes of operation

Finite set model predictive current control with reduced and constant common mode voltage for a five-phase voltage source inverter

Abstract: Multiphase drives are now becoming serious competitor to traditional three-phase drives due to reasons of better fault tolerant property and reduced per-phase converter rating that are especially suited to high power drives application. One of the major factor of widespread research on multiphase drive are the availability of high computational power of control platforms such as DSP and FPGAs. With availability of such computationally powerful tool of DSP/FPGA leads to the adoption of model predictive control (MPC) in electric drive. This paper present current control of a five-phase inverter using MPC with the aim of achieving constant common mode voltage. By achieving constant common mode voltage (CMV), bearing current can be greatly reduced. This is achieved by proper selection of space vectors and analysis of drop in voltage gain is presented. Simulation results are supported by experimental approach.

Energy management and control algorithms for integration of energy storage within microgrid

Abstract: This paper discusses energy management and control algorithms of microgrid with energy storage. Specific management framework within microgrid presented here includes: a) help prioritizing the renewable energy sources (RES) to provide power to local loads, b) manage battery to avoid deep-discharging and overcharging, c) maintain dc link voltage at a specified value, and d) regulate ac voltage buses at nominal voltage and frequency. The system analyzed here is adopted from Consortium for Electric Reliability Technology Solutions (CERTS) microgrid test bed. While the generation priority is from RES, the system also has a thermal generation unit to compensate for renewable energy variability and intermittency. Depending on battery state of charge (SOC) and power difference between photovoltaic (PV) and the load, the energy management can work with several modes: charging, discharging, export power, import power, and halt. The system is simulated in PSCAD platform and shows that energy management and control algorithms work as expected.

Comparison of bi-directional voltage-fed and current-fed dual active bridge isolated dc/dc converters low voltage high current applications

Abstract: This paper presents a comparison of two potential soft-switching bi-directional high-frequency transformer isolated voltage-fed and current-fed dual active bridge dc/dc converters for fuel cell vehicle application. The comparison and discussion are conducted over the suitability of these two converters acting as a front-end dc/dc converter for a fuel cell inverter from the perspective of the circulating and peak currents, RMS currents through the devices, components' ratings, size, losses, and efficiency. Software package PSIM 9.0.4 has been utilized to justify the merits of current-fed converter over voltage-fed converter for the given application. Experimental results of current-fed converter have also been provided. Switching losses are reduced significantly owing to zero-current switching (ZCS) of primary switches and zero-voltage switching (ZVS) of secondary switches, which allow high switching frequency operation resulting in a compact and low cost system.

Home energy management with PSO in smart grid

Abstract: In this paper, a real-time optimal appliance usage strategy is proposed based on binary particle swarm algorithm, participated by both energy suppliers and end users. Under the multi end-users and time-of-use electricity prices circumstances, the total electricity bills can be generated with different appliance usage pattern: random, single optimal objective and double optimal objectives, resulting in different load curves. Considering the characteristics of the appliances and living habits, the appliances are classified into three categories. Matlab is used as the simulation tool to perform the experiments to prove that the load shifting, energy saving and energy supply efficiency enhancement can be achieved with multi-objectives with particle swarm optimization.

Selective harmonic elimination modulation technique applied on four-leg NPC

Abstract: In this paper the selective harmonic elimination pulse width modulation (SHE-PWM) technique is proposed to control the three-level four-leg neutral point clamped (NPC) inverter in order to have both advantages of low switching frequency of SHE and neutral point of fourth leg in four wire systems. In this proposed method, the obtained switching angles of inverter phase legs are used to eliminate the non-triplen, 5 th to 23 th harmonics orders from the output voltage. As well, switching angles calculated for the fourth leg are considered to eliminate the triplen harmonics containing 3 th , 9 th , 15 th , 21 th and 27th orders from phase voltage. The efficiency of the proposed modulation technique is verified by simulations of a four leg NPC inverter as an UPS feeding different types of dynamic and unbalanced loads.

Industrial applications of collaborative Wireless Sensor Networks: A survey

Abstract: The objective of this paper is to summarize the recent literature and application examples of the use of Wireless Sensor Networks (WSN) in the industry Main focus in this paper is primarily on the use of collaborative wireless sensor networks for condition and performance monitoring of the industrial machines and plants Current challenges and potential future research issues are outlined for design of WSN-based industrial monitoring systems in order to provide guidelines to researchers and application developers

Neural Networks based approach for inverse kinematic modeling of a Compact Bionic Handling Assistant trunk

Abstract: A common approach to resolve the problem of inverse kinematics of manipulators is based on the Jacobian matrix. However, depending on the complexity of the system to model the elements of the Jacobian matrices may not be calculated. To overcome intrinsic problems related to Jacobian matrix based methods, a new inverse kinematic modeling approach capable to approximate the inverse kinematics of a class of hyper-redundant continuum robots, namely Compact Bionic Handling Assistant (CBHA) is proposed in the present work. The proposed approach makes use of Multilayer Perceptron (MLP) and Radial Basis Function (RBF) Neural Networks as approximation methods. A validation using a rigid 6 DOF industrial manipulator demonstrates the effectiveness and efficiency of the proposed approach.

Indoor WiFi energy harvester with multiple antenna for low-power wireless applications

Abstract: This research proposed a WiFi energy harvester for low-power wireless applications. The proposed system harvests energy using three antennas to cover three ISM (Industrial, Scientific, and Medical) channels with central frequencies at 2.412 GHz, 2.439 GHz, and 2.462 GHz. For each channel, a co-planar waveguide antenna is designed to harvest energy from indoor WiFi transmitters. FR4 substrate with relative permittivity of 4.3 and loss tangent of 0.025 is used to form the antennas. The output from each harvester antenna is then connected to a seven-stage multiplier circuit. The multiplier circuit is to rectify and boost the harvested energy to a higher voltage level and then stored temporarily in a super capacitor. A dc-dc boost-charger circuit with battery management is used to increase the output voltage level to 2 V. An experiment with the proposed system has been conducted using transmitted energy from available WiFi transmitters. The power density at the harvesting antenna front is between -80 dBm and -50 dBm. The proposed harvester system takes about 6 to 7 hours to charge up the first stage super capacitor up to the minimal threshold voltage (0.45V). This minimal threshold will start the boost-charger circuit charging the secondary storage device. This research demonstrates that the proposed system can supply energy for low-power wireless sensors that operate with an input power less than 1 mW.

Single-phase grid-tied photovoltaic system with boost converter and active filtering

Abstract: This paper deals with a single-phase grid-tied photovoltaic system, which can operate, simultaneously, as shunt active power filter and injecting active power into the grid. The photovoltaic system is composed of DC/DC step-up (boost) converter and full-bridge DC-AC converter, performing both reactive power compensation and harmonic current suppression generated by nonlinear loads. The photovoltaic system is implemented utilizing an equivalent electric model, and its maximum power point is tracked by means of P&O algorithm, which is used to control the DC-DC step-up converter. The algorithm adopted to obtain the current reference of the DC-AC converter is based on the synchronous reference frame (SRF) method. Furthermore, an anti-islanding technique is implemented, in order to guarantee the safe operation of photovoltaic system. Simulation results are present to validate the proposed control strategy, and to verify the system feasibility.

Modeling, design and fault analysis of bidirectional DC-DC converter for hybrid electric vehicles

Abstract: This paper presents modeling, design and analysis of a bidirectional half-bridge DC/DC converter suitable for power electronic interface between the main energy storage system and the electric traction drive in hybrid electric vehicles. A hybrid energy storage system composed of a battery unit and an ultracapacitor pack is considered. A parallel dc-linked multi-input converter with a half-bridge bidirectional DC/DC cell topology is chosen to link the battery/ultracapacitor storage unit with the dc-link. The paper focuses on modeling the proposed converter for both dynamic and steady state analysis. Averaging and linearization techniques are applied to obtain the averaged state space models and small signal models of the converter in both boost and buck operation modes. A criterion for sizing the converter passive components based on the imposed design specifications and constraints is illustrated. Simulation results of the buck-boost converter during normal functioning and under faulty conditions are presented. In particular, short-circuit faults and open-circuit faults of diodes and transistors are analyzed.

Loss analysis of non-isolated bidirectional DC/DC converters for hybrid energy storage system in EVs

Abstract: The selection of a bidirectional non-isolated dc-dc converter interfacing the battery and ultracapacitor (UC) in electric vehicles (EVs) is of critical importance for the overall system efficiency. Generally, efficiency comparison of converters is conducted based on given fixed input and output parameters. Such a comparison may not provide fair results for EV applications since energy source voltages and traction power vary dynamically depending on the driving conditions. This paper provides a comprehensive efficiency comparison of three-level, two-level and interleaved bidirectional buck/boost converters through developed loss models considering the dynamic variables in a drive cycle. The results of the analyses show that three-level converter exhibits higher overall efficiency. A 1kW prototype has been designed and developed to serve as a proof of concept.

Automatic landing control of Unmanned Aerial Vehicles on moving platforms

Abstract: This paper studies the landing control problem for Unmanned Aerial Vehicles (UAVs) on an oscillating platform such as a ship deck in a rough sea. A full nonlinear mathematical model is first introduced for the UAV in an inertial frame. A Fourier transform based method is then employed for a realistic characterization of the sea motion and the ship dynamics. Finally, a landing control algorithm is developed based on the dynamics of the UAV relative to the ship. The effectiveness of the control algorithm is illustrated through a simulation example.

A novel SVPWM scheme for Vienna rectifier without current distortion at current zero-crossing point

Abstract: Vienna rectifier is one of the most popular topologies for three-phase PFC converter. DC voltage, grid current double loop controller and three-level SVPWM are normally used to control the Vienna rectifier. Accurately detecting the current zero-crossing point is required to achieve the correct SVPWM signals since the output level of Vienna rectifier is also decided by the direction of the phase current. The error of the duty ratio is decided by the error time of the current zero-crossing point detecting and the duty ratio before and after the current zero-crossing point. It can be concluded that the impact of current zero-crossing will be eliminated if the switches near current zero-crossing point are kept “on”. To achieve this goal, a novel SVPWM scheme is proposed by using the certain state combinations of short vectors in each sector. In this method, the calculation of duty ratio will not be affected by the direction of phase current near the zero-crossing point, and therefore the distortion of current caused by current zero-crossing detection error will be eliminated. Simulations and experiments are conducted to verify the presented method.