Miracle-dz/UniFAR-FTUs huggingface dataset:
Design and Modeling of an Equalizer for Fuel Cell Energy Management Systems

During the lifespan of a polymer electrolyte membrane fuel cell (PEMFC) system, some heterogeneities between the cells constituting the stack can appear. The voltage of one particular cell in a stack may decrease because of specific aging or local malfunctioning such as drying. As a result, more heat is generated in this cell leading to an increase in its temperature and, thus, an additional voltage loss. This snowball effect can result in the failure of the cell. Therefore, the lifetime of a PEMFC stack can be increased by applying energy management to its cells. Note that the output voltage of a cell is lower than a stack. Hence, a high conversion ratio converter is necessary to implement such energy management. An efficient way to increase the output voltage is to connect the output capacitors of the converters such as the boosts in series. Ensuring the converters’ controllability is a key point to implement energy management. In this paper, an equalizer system is proposed to ensure the controllability of the boost converters. The balancing speed and the low number of switches are the main advantages of this system. The validity of the proposed system is verified through simulation and experiments.
Polymer mechanics and tribology

Purpose The purpose of this paper is to review the advances in mechanics and tribology of polymers and polymer-based materials. It is focused on the understanding of the correlation of contact mechanics and the tribological behavior of polymers and polymer composites by taking account of surface forces and adhesion in the contact. Design/methodology/approach Mechanical behavior of polymers is considered a viscoelasticity. Tribological performance is estimated while considering the parts of deformation and adhesion in friction arising in the contact. Surface energy, roughness, load and temperature effects on the tribological behavior of polymers are evaluated. Polymer composites produced by reinforcing and by the addition of functional additives are considered as materials for various applications in tribology. Particular attention is given to polymer-based nanocomposites. Findings A review of studies in tribology has shown that polymer-based materials can be most successfully used as self-lubricating components of sliding bearings. The use of the fillers provides changes in the tribological performance of neat polymers and widens their areas of application in the industry. Thin polymer films were found to be prospective lubricants for memory storage devices, micro-electro-mechanical systems and precision mechanisms. Further progress in polymer tribology should be achieved on solving the problems of contact mechanics, surface physics and tribochemistry by taking account of the scale factor. Originality/value The review is based on the experience of the authors in polymer mechanics and tribology, their research data and on data of many other literature sources published in this area. It can be useful for specialists in polymer research and industrial engineers working in tribology and industrial lubrication.
Improved power flow control strategy of the hybrid AC/DC microgrid based on VSM

The hybrid AC/DC microgrid with different types of distributed generations (DGs) and load demands is considered to be the preferred microgrid mode in the future. For hybrid AC/DC microgrid, autonomous and bidirectional power flow between AC and DC subgrids with superior dynamic performance is the fundamental objective to realise proportional power sharing and robust operation. In this study, an improved active power control strategy of the bidirectional AC/DC main converter (BMC) based on virtual synchronisation machine (VSM) for inertia improvement of the AC bus frequency and DC bus voltage of the hybrid microgrid is proposed. The VSM control is derived through the virtual inertia equation and the virtual capacitance equation, which can manage the AC frequency and DC voltage simultaneously. Then, the small signal and large signal characteristics analysis of the BMC are conducted to analyse the VSM control feature with different control parameters. On the basis of the small signal analysis, a proportional power sharing principle to select the control parameters is given to make DGs share the power commensurate with their power ratings. Finally, simulation cases are carried out to show the validity and efficiency of the proposed control strategy.
A novel dual-mode wideband band pass filter

─ A novel Wideband (WB) Bandpass Filter (BPF) with improved passband performance using a Defected Ground Structure (DGS) is presented in this paper. The proposed BPF is composed of two novel basic WB resonators and six Dumbbell-Shaped (DS) DGSs. By cascading resonators we can achieve better skirt characteristics, and by using DS-DGSs under interdigital coupled I/O lines we can improve the return loss within the passband. The simulated and measured results are found in good agreement with each other showing a wide passband from 4.93 to 11.62 GHz, a wide upper stopband with around 25 dB attenuation up to 20 GHz, and sharp roll-offs around 0.03 in lower and upper edges. Index Terms ─ Dual mode, microstrip bandpass filter, wide passband.
Urban Change Monitoring in Developing Countries Based on Deep Learning Technique by Utilizing Time Series Imageries of the SAR and Optical Satellites

Frequent monitoring of the urban changes is important for urban and economic development planners. Satellite imageries provide chance for mapping the rapid urban expansions and can be effectively used for monitoring the urban changes. This study highlights the automatic extraction methodology of generating land cover maps from single-polarization SAR imageries of TerraSAR-X (HH) of the developing regions in Southeast Asia such as Indonesia and the Philippines by utilizing deep learning algorithm. As single-polarization SAR imageries have difficulty of classification of water areas, the water areas are extracted from optical satellite imagery of Landsat and Sentinel-2. After generating land cover maps, urban areas are extracted. By analyzing time series of satellite imageries in the proposed methodology revealed that there are fast developments of the urban areas in the developing countries. The results were validated by the existing facts of development plans for each country. This study demonstrated about the value of combining SAR and optical satellite imageries for urban change monitoring by utilizing deep learning technique.
A transformerless high step-up conversion ratio dc–dc converter with voltage multiplier

ABSTRACT This paper proposes a non-isolated transformerless high step-up dc–dc converter. The presented converter voltage gain is higher that of the conventional boost, buck boost, CUK, SEPIC and ZETA converters. In addition, in this converter, only one power switch is utilized. The voltage stress across the power switch is low. Hence, the low on-state resistance of the power switch can be selected to decrease switching loss of the switch and improve efficiency. The principle of operation and the mathematical analyses of the proposed converter are explained. The validity of the presented converter is verified by the experimental results.
A Control Strategy for Bidirectional Isolated 3-Phase Current-Fed Dual Active Bridge Converter

This paper examines the characteristics of the zero voltage switching (ZVS) and zero voltage transition (ZVT) soft-switching applied in the 3-phase current fed dual active bridge (3P-CFDAB) converter, which combines the advantages of the dual active bridge (DAB) converter and current-fed full bridge (CFFB) converter. When an active clamp circuit is added to the CFFB converter, the circuit configuration of the DAB converter is shown in part of the entire circuit. This allows the use of pulse width modulation (PWM) techniques which combine the PWM techniques of both the DAB converter and CFFB converter. The proposed converter performs both duty and phase control at the same time in order to reduce the circulating current and ripple current of the output capacitor, which are the disadvantages of the CFFB converter and DAB converter. In addition, the ZVS and ZVT soft switching areas were analyzed by means of the phase current and leakage inductor current in each transformers. To verify the principle and feasibility of the proposed operation techniques, a simulation and experiment were implemented with the 3P-CFDAB.
A Terrain-Based Vehicle Localization Approach Robust to Braking

Terrain-based vehicle localization is a valuable alternative to GPS when the signal is blocked or dynamic occlusions exist. However, braking events can induce the slips and vibrations of the vehicle and, thus, increase the errors of terrain-based position estimations. This paper develops a terrain-based localization approach which is robust to braking events. First, the terrain map is generated and stored before localization, which includes distance measurements, terrain feature data, and the geographic locations. The terrain feature data are pitch differences to eliminate the accumulated error. Next, particle-filter-based and acceleration-considered vehicle localization is proposed for position estimation. It takes into account the influence of braking in the vehicle model and the inference process. Experimental results demonstrate the repeatability of pitch difference measurements and the robustness of the proposed approach in the cases of smooth driving and braking.
Gear fault diagnosis method based on wavelet-packet independent component analysis and support vector machine with kernel function fusion

Aiming at the problem of gear fault diagnosis, in order to effectively extract the features and improve the accuracy of gear fault diagnosis, the method based on wavelet-packet independent component analysis and support vector machine with kernel function fusion is proposed in this research. The proposed wavelet-packet independent component analysis feature extraction method can effectively combine the advantages of wavelet packet and independent component analysis methods and acquire more comprehensive feature information. Besides, the proposed kernel-function-fusion support vector machine can well integrate the advantage characteristics of each kernel function. The energy features of wavelet packet coefficients are acquired with four-layer wavelet packet decomposition and then the extracted energy features are further optimized by the independent component analysis method. The kernel-function-fusion support vector machine method is adopted to realize the gear fault diagnosis. Two kernel function models with the best self-classification accuracy are employed to serve the gear fault diagnosis corporately. The test samples are primarily classified by the main kernel function model, and then some samples are selected to be reclassified with the other kernel function model. Finally, the two kernel function models cooperate to determine the type of test samples. The comparison investigations demonstrate that the proposed method based on wavelet-packet independent component analysis and support vector machine with kernel function fusion achieves very high diagnosis accuracy.
A Comprehensive Review of Winding Short Circuit Fault and Irreversible Demagnetization Fault Detection in PM Type Machines

Contemporary research has shown impetus in the diagnostics of permanent magnet (PM) type machines. The manufacturers are now more interested in building diagnostics features in the control algorithms of machines to make them more salable and reliable. A compact structure, exclusive high-power density, high torque density, and efficiency make the PM machine an attractive option to use in industrial applications. The impact of a harsh operational environment most often leads to faults in PM machines. The diagnosis and nipping of such faults at an early stage have appeared as the prime concern of manufacturers and end users. This paper reviews the recent advances in fault diagnosis techniques of the two most frequently occurring faults, namely inter-turn short fault (ITSF) and irreversible demagnetization fault (IDF). ITSF is associated with a short circuit in stator winding turns in the same phase of the machine, while IDF is associated with the weakening strength of the PM in the rotor. A detailed literature review of different categories of fault indexes and their strengths and weaknesses is presented. The research trends in the fault diagnosis and the shortcomings of available literature are discussed. Moreover, potential research directions and techniques applicable for possible solutions are also extensively suggested.
Role of Non-Idealities in III-V/Si and All III-V Tunnel Field Effect Transistors

Energy scaling of integrated circuits has hit a roadblock as the operating voltage of the MOSFET-based solid state switches has attained a minimum possible value. The thermionic emission mechanism, which governs the switching of the Metal-oxide Semiconductor Field Effect Transistors (MOSFETs), does not allow to achieve subthreshold swing below 60 mV/decade at room temperature, thus establishing a lower limit on the operating voltage. Tunnel Field Effect Transistors (TFETs) which operate on the principle of field modulation of Band-to-band Tunneling (BTBT) can deliver a subthreshold swing less than 60 mV/dec. Therefore, TFETs are considered as a potential candidate to replace MOSFETs as solid-state switches to achieve further scaling of the supply voltage. However, the swing of a TFET is degraded by non-idealities such as traps, band tails, interface roughness, etc., which are inevitably present. To understand the effect of the non-idealities on the TFETs, physics-based models have been developed in this work and implemented in the Technology Computer Aided Design (TCAD) simulator Synopsys Sentaurus Device. Simulations show that channel quantization reduces the on-current of the TFET which is confirmed by comparison with the experimental transfer characteristics of InAs/Si TFETs. Also, interface roughness and band tails are found to degrade the swing. TCAD analysis of experimental InAs/Si and all-III-V TFETs has confirmed that, maximum degradation of the swing results from the traps at the hetero-interface and the oxide interface. Our simulation set-up has achieved good agreement with the experimentally obtained temperature dependent as well as VDS dependent transfer characteristics which confirms reliability of the set-up. Using this set-up, we have shown that, scaling of the
On the equivalence of certain Markov chains

It is shown that an irreducible and aperiodic Markov chain can be altered preserving irreducibility without altering the nature of the chain in the sense that, the modified chain is transient (recurrent) if and only if the original chain is transient (recurrent). Furthermore, it is shown by means of a counterexample that ergodicity (null-recurrence) is not preserved. An interesting application of this result is a simple proof of Pakes's generalization of Foster's criterion for a chain to be recurrent.
Adaptive Hysteresis Current Control Of A Pwm Inverter At Constant Modulation Frequency Applied To Shunt Active Power Filters

This paper proposes a novel adaptive hysteresis current control strategy of a voltage-fed PWM inverter, where the switching frequency always remains constant and the harmonic ripple is minimum, irrespective of dc link voltage fluctuation and load parameter variation. The developed algorithm works well for single-phase as well as multi-phase inverters, although single-phase inverter operation, particularly in active harmonic filter mode, is emphasized in this paper. The algorithm uses fuzzy logic-based current error compensation, and it is simple to implement and does not involve any hysteresis-band calculation. The control strategy has been implemented digitally with a high-speed digital signal processor (TI-TMS320F2812). The proposed scheme has been thoroughly evaluated in laboratory by simulation as well as in experimental studies on a single-phase inverter, and its performance was found to be excellent.
Spectral Efficiency Analysis in Massive MIMO using FBMC-OQAM Modulation

This article covers the potential of Filter Bank Multicarrier (FBMC) modulation as an alternative to be used in the future 5G wireless networks in which Massive Multiple-Input Multiple-Output (MIMO) will be deployed. The study compares orthogonal frequency division multiplexing (OFDM) with FBMC. The former is the multiplexing technique in 4G communications and the latter is one of the strongest candidates to replace OFDM in 5G networks. This comparison evaluates the spectral efficiency (SE) of a Massive MIMO (MM) system uplink under a single-cell environment. The diversity in MM permits a self-equalization of the channel, which the FBMC further benefits from, due to the confinement of the subcarrier in an assigned range. Due to the absence of the cyclic prefix, the FBMC has better SE than the OFDM for increasing signal-to-noise-ratio (SNR). One may find a scarce literature covering the FBMC in a large-scale multiuser MIMO scenario, which considers a large number of antennas at the base station (BS). Various scenarios are considered by varying the number of antennas, users and different cell radius. Moreover, the subcarrier modulations are simulated, and not considered Gaussian distributed, as in Shannon limit theory. In some cases, the FBMC allows doubling the cell radius for the same SE value of 3.8 bits/s/Hz/user. For a fixed cell radius of 750m and a SE of 3.5 bits/s/Hz/user, the OFDM requires three times more antennas than FBMC when both modulations are under the same conditions.
Theoretical analysis and experimental study of a nonlinear U-shaped bi-directional piezoelectric energy harvester

Narrow bandwidth and uni-directional acquisition restrict the application of a conventional cantilever piezoelectric energy harvester. In this study, a magnet-induced nonlinear U-shaped bi-directional piezoelectric harvester is proposed to overcome the shortcomings of the conventional harvester. The U-shaped harvester consists of a beam bent into a U shape with both ends fixed. A pair of piezoelectric plates is attached to the beam for power generation. To introduce nonlinear magnetic force, a magnet is attached to the center of the beam while a pair of magnets are fixed to the base. The theoretical model of the proposed harvester is developed and validated with experimental results. The proposed harvester is investigated in two orthogonal directions of vibration. The proposed harvester shows linear responses in vertical excitations. However, a strong hardening effect can be observed in horizontal excitations especially when the magnet gap is small. It is shown that the hardening effect can improve both the harvesting bandwidth and the output power in horizontal excitations. On the other hand, the resonant frequency of the vertical mode can be increased while that of the horizontal mode is decreased by reducing the magnet gap. This indicates that the magnet gap can be utilized to tune the ratio between the vertical and horizontal resonant frequencies to match the frequencies of vibration sources. Overall, the proposed nonlinear U-shaped harvester demonstrates the capability of bi-directional harvesting and improved performance with the aid of nonlinear magnetic force.
Monitoring of user‐generated reviews via a sequential reverse joint sentiment‐topic model

User‐generated reviews can serve as an efficient tool for evaluating the customer‐perceived quality of online products and services. This article proposes a joint control chart for monitoring the quantitative evolution of document‐level topics and sentiments in online customer reviews. A sequential model is constructed to convert the temporally correlated document collections to topic and sentiment distributions, which are subsequently used to monitor the topics that users are concerned about and the topic‐specific opinions in an ongoing product and service process. Simulation studies on various data scenarios demonstrate the superior performance of the proposed control chart in terms of both detecting shifts and identifying truly out‐of‐control terms.
Imperfect repair

A device is repaired at failure. With probability p, it is returned to the ‘good-as-new' state (perfect repair), with probability 1 – p, it is returned to the functioning state, but it is only as good as a device of age equal to its age at failure (imperfect repair). Repair takes negligible time. We obtain the distribution Fp of the interval between successive good-as-new states in terms of the underlying life distribution F. We show that if F is in any of the life distribution classes IFR, DFR, IFRA, DFRA, NBU, NWU, DMRL, or IMRL, then Fp is in the same class. Finally, we obtain a number of monotonicity properties for various parameters and random variables of the stochastic process. The results obtained are of interest in the context of stochastic processes in general, as well as being useful in the particular imperfect repair model studied.
Is Travel Demand Actually Deep? An Application in Event Areas Using Semantic Information

In transportation, nature, economy, environment, and many other settings, there are multiple simultaneous phenomena happening that are of interest to model and predict. Over the last few years, the traffic data that we have at our disposal have significantly increased, and we have truly entered the era of big data for transportation. Most existing travel demand prediction methods mainly focus on capturing recurrent mobility trends that relate to habitual/routine behavior, and on exploiting short-term correlations with recent observation patterns. However, valuable information that is often available in the form of unstructured data is neglected when attempting to improve forecasting results. Particularly, under non-recurrent conditions, such as large events, or incidents, we need much better models. In this paper, we explore time-series data and semantic information combinations using machine learning and deep learning techniques in the context of creating a prediction model that is able to capture in real-time future stressful situations of the studied transportation system. We apply the proposed approaches in event areas in New York using publicly available taxi data. We empirically show that the proposed models are able to significantly reduce the error in the forecasts. The importance of semantic information is highlighted in all presented methods and the final mean absolute error of our prediction is decreased by 23.8% for a three months testing period.