Single Output Research Articles

Parametric study of battery module cooling: Configuration optimization using response curve method

Recently, cylindrical lithium-ion battery cells have been widely used in electric vehicles due to efficient automated production and cheap kilowatt-hour capacity. For optimal operation of a cell, the internal temperature of the cell should be maintained within the range of 15–35 °C by employing suitable cooling mechanism. This study comprehensively compares multiple air-cooling configurations specifically designed for lithium-ion battery three-series and three-parallel (3S3P) modules using. The methodology involves an experimental phase to measure the parameters of Bernardi's equation, essential for calculating heat generation with consideration of both Joule's heat and entropic heat. Subsequently, a numerical simulation using Ansys Fluent examines battery heat generation within the 3S3P modules, employing diverse air-cooling configurations. Each configuration undergoes simulation with the aid of design of experiments and parametric analysis, allowing the observation of cooling behavior across various input parameters. To ensure reliability of simulation, the cooling of the unit cell module is simulated under similar conditions. The comparison between these simulated results and experimental values is conducted to validate the accuracy of the overall analysis methodology. The heat measurements indicated a unit cell heat output of 0.9028 W at an average rate of 0.85C. Among the investigated air-cooling configurations, the SIDO (Single Input Double Output) arrangement stood out as the most effective in maintaining a consistently lower average cell temperature, as determined through the application of the response curve method. This study emphasizes the importance of air-cooling design for improving the performance and safety of lithium-ion battery modules used in electric vehicles.

Design of a Ka-Band Heterogeneous Integrated T/R Module of Phased Array Antenna

The central element of a phased array antenna that performs beam electrical scanning, as well as signal transmission and reception, is the transceiver (T/R) module. Higher standards have been set for the integration, volume, power consumption, stability, and environmental adaptability of T/R modules due to the increased operating frequency of phased array antennas, the variability of application platforms, and the diversified development of system functions. Device-based multichannel T/R modules are the key to realizing low-profile Ka-band phased array antenna microsystem architecture. The design and implementation of a low-profile, high-performance, and highly integrated Ka-band phased array antenna T/R module are examined in this paper. Additionally, a dependable Ka-band four-channel T/R module based on Si/GaAs/Low Temperature Co-fired Ceramic (LTCC), applying multi-material heterogeneous integration architecture, is proposed and fabricated. The chip architecture, transceiver link, LTCC substrates, interconnect interface, and packaging are all taken into consideration when designing the T/R module. When compared to a standard phased array antenna, the module’s profile shrunk from 40 mm to 8 mm, and its overall dimensions are only 10.8 mm × 10 mm × 3 mm. It weighs 1 g, and with the same specs, the single channel volume was reduced by 95%. The T/R module has an output power of ≥26 dBm for single-channel transmission, an efficiency of ≥25%, and a noise factor of ≤4.4 dB. When compared to T/R modules based on System-on-Chip (SOC) devices, the RF performance has significantly improved, as seen by an increase in single channel output power and a decrease in the receiving noise factor. This work lays a foundation for the devitalization and engineering application of T/R modules in highly reliable application scenarios.

Blind MMSE Equalization of SISO IIR Channels Using Oversampling and Multichannel Linear Prediction

In this correspondence, a novel linear prediction based blind equalization algorithm for Single Input Single Output (SISO) IIR channels is proposed. The new algorithm is based on second-order statistics and it does not require channel order estimation. By oversampling the channel output, the SISO channel model is converted to a special Single Input Multiple Output (SIMO) model. Two forward linear predictors with consecutive prediction steps are applied to the subchannel outputs of the SIMO model. It is proved that the partial parameters of the SIMO model can be estimated from the difference between the prediction errors when the length of the predictors is sufficiently large. The sufficient filter length for achieving the optimal prediction is also derived. Based on the estimated parameters, both batch and adaptive Minimum-Mean-Square-Error (MMSE) equalizers are developed. The performance of the proposed equalizers is evaluated by computer simulations and compared with existing algorithms.

Application of Fuzzy Mamdani Model for Biogas Yield Prediction in Anaerobic Co-Digestion of Decomposable Wastes

Accurate prediction of biogas yield is crucial for optimizing waste-to-energy conversion systems in anaerobic co-digestion processes. In this study, a double input and single output (DISO) fuzzy mamdani model (FMM) was developed for the prediction of biogas yield in a pilot scale of 105-L mesophilic anaerobic sludge bio-digester. The input variables considered are the combination of cow dung and pig waste and the retention time (RT), while the output variable is the experimental biogas yield. Triangular Fuzzy Membership Functions (TFMF) were utilized to define the input and output datasets, and rules were derived from de-fuzzification. Comparative analysis between the FMM's predicted results and experimental values showcased its effectiveness in forecasting biogas yield during the anaerobic co-digestion of the hybrid wastes. Significantly, the FMM consistently produced results with low error values for the sample dataset, underscoring its accuracy even under stochastic conditions. This study emphasizes the FMM's ability to generate predictions with minimal deviations, offering superior results. As a prospect for future research, the implementation of hybrid algorithms may further enhance biogas yield prediction accuracy within waste-to-energy systems.

Exploring a Controlled Permeability Bypass-Based and Simple Contact Mechanism for MPD System With Single Input and Multiple Outputs

Exploring a Controlled Permeability Bypass-Based and Simple Contact Mechanism for MPD System With Single Input and Multiple Outputs

A Robust Hybrid MRAPID Controller Design for an Underactuated Nonlinear System With Parametric Uncertainty

This paper presents an optimal design and simulation of a novel enhanced model reference adaptive proportional–integral–derivative controller (MRAPIDC) for underactuated nonlinear systems with parametric uncertainty. The controller is applied to a cart‐inverted pendulum mechanical system, a fourth‐order, nonminimum phase system with pronounced nonlinearity and unstable dynamics. This system includes a single input and multiple outputs, specifically the position and velocity of the cart, as well as the angle and angular velocity of the inverted pendulum arm. The main objective of the proposed controller is to maintain the pendulum in an upright position against gravity while moving the cart to a desired displacement regardless of parametric uncertainty, input variation, external disturbances, and random noise. The hybrid controller design is developed by combining the MRAPIDC design with controller gains applied to each output and incorporating the system adaptation error in a specific configuration. Optimal performance is achieved through parameter tuning via the social spider optimization (SSO) algorithm, and MIT (Massachusetts Institute of Technology) rule criteria are employed to ensure system stability. Performance improvements are demonstrated through several error indices, showing enhanced transient and steady‐state responses compared to both the reference model adaptive controller and the conventional proportional–integral–derivative (PID) controller. The proposed controller can effectively achieve system stability with a short settling time of 2.55 s and establishes a steady swinging balance within 2.9 s.

Short-term forecasting approach of single well production based on multi-intelligent agent hybrid model.

The short-term prediction of single well production can provide direct data support for timely guiding the optimization and adjustment of oil well production parameters and studying and judging oil well production conditions. In view of the coupling effect of complex factors on the daily output of a single well, a short-term prediction method based on a multi-agent hybrid model is proposed, and a short-term prediction process of single well output is constructed. First, CEEMDAN method is used to decompose and reconstruct the original data set, and the sliding window method is used to compose the data set with the obtained components. Features of components by decomposition are described as feature vectors based on values of fuzzy entropy and autocorrelation coefficient, through which those components are divided into two groups using cluster algorithm for prediction with two sub models. Optimized online sequential extreme learning machine and the deep learning model based on encoder-decoder structure using self-attention are developed as sub models to predict the grouped data, and the final predicted production comes from the sum of prediction values by sub models. The validity of this method for short-term production prediction of single well daily oil production is verified. The statistical value of data deviation and statistical test methods are introduced as the basis for comparative evaluation, and comparative models are used as the reference model to evaluate the prediction effect of the above multi-agent hybrid model. Results indicated that the proposed hybrid model has performed better with MAE value of 0.0935, 0.0694 and 0.0593 in three cases, respectively. By comparison, the short-term prediction method of single well production based on multi-agent hybrid model has considerably improved the statistical value of prediction deviation of selected oil well data in different periods. Through statistical test, the multi-agent hybrid model is superior to the comparative models. Therefore, the short-term prediction method of single well production based on a multi-agent hybrid model can effectively optimize oilfield production parameters and study and judge oil well production conditions.

A Single DC Source Gradient Driver Circuit With Boosting Output Capability for MRI Applications

Magnetic resonance imaging (MRI) systems gradient driver (GD) circuits, which drive current through gradient coils, have essential roles in imaging quality and speed. They drive large current values, higher than 1000 A, with high fidelity to the commands, low current ripples, and fast transient responses, which lead to high voltage values, larger than 2 kV, to properly drive the coils. Till now, some solutions with parallel and stacked structures have been reported to fulfill such requirements, which need several independent isolated voltages to deliver the necessary output current. Thus, other parts are generally needed to generate these voltages, separately. Here, a new GD circuit with only a single independent voltage source and output voltage boosting capability is proposed to drive such gradient coils. It reduces the semiconductor and magnetic element counts, in the MRI gradient driver power chain. It also reduces the pulsed power demand from the facility, by storing energy. The proposed circuit has been mathematically analyzed, here. A 2.34 MVA,1300A/1800 V GD circuit has been designed and simulated based on the proposed topology to verify its performance. Finally, a laboratory 700 V, 10 A scaled-down prototype converter has been implemented, based on the proposed topology to verify the given analyses and simulation results.

Online adaptive identification of multichannel systems for audio applications.

Impulse responses (IRs) estimation of multi-input acoustic systems is a prerequisite for many audio applications. In this paper, an adaptive identification problem based on the Autostep algorithm is extended to the simultaneous estimation of room IRs for multiple input single output linear time invariant systems without any a priori information. To do so, the proposed algorithm is initially evaluated in a simulated room with several sound sources active at the same time. Finally, an experimental validation is proposed for the cases of a semi-anechoic chamber and an arbitrary room. Special attention is dedicated to the algorithm convergence behavior, considering different meta parameters settings. Results are eventually compared with the other normalized version of the least mean square algorithm.

An Interference Alignment Design with Higher Multiplexing Gain by the Reduced Channel Extension

For a K-user Single Input Single Output fading interference channel, Cadambe and Jafar proposed a scheme that achieves K=2 multiplexing gain asymptotically employing interference alignment technique. This scheme is improved by Choi et al. in which for reduced channel extension, higher multiplexing gain is achievable. But the existing designs require an infinite number of channel extension to achieve the upperbound. Our proposed design attains higher multiplexing gain that is arbitrarily close to the upper-bound by using a lot lower number of channel extension in comparison with the other existing interference alignment schemes. On the other hand, due to the great symbol extension reduction of the channel, the computational complexity to achieve K=2 degrees of freedom (desired upper-bound) is also reduced significantly. Moreover, it can be shown that the proposed design achieves higher interference alignment quality. For a limited channel extension, the proposed scheme leads to a better allocation of the signal space at each receiver to the desired and interfered signal. This results to a higher quality of alignment.

МНОГОФАКТОРНАЯ МОДЕЛЬ ОЦЕНКИ ЭКОЛОГИЧНОСТИ РАЗВИТИЯ ЭКОНОМИКИ РЕГИОНА

One of the most important problems in the socio-economic development of regions is ensuring the proper quality of growth. As a rule, economic growth implies an increase in the intensity of resource consumption, which contributes to increased anthropogenic impact on the environment, deterioration of living conditions, threats to public health and a decrease in social security. Using the example of subjects of the Volga Federal District, the article examines the impact of economic growth on environmental factors, assessing, among other things, the relationship between the state of the environment and the incidence of disease in the population. Various approaches are used for cross-regional comparisons of environmental conditions. The index of environmental well-being, built on the basis of a three-factor model, is considered as the main characteristic. On the basis of this index, an index of environmental efficiency of the regional economy is formed, which is defined as the level of environmental well-being for a single output of the regional economy. The multifactor model showed that if environmental efficiency is maintained in a growing economy, then the level of environmental well-being will decline at a faster rate than the rate of economic growth. To maintain environmental well-being in conditions of economic growth, it is necessary that the average increase in environmental well-being for each factor is not lower than the rate of economic growth. For single-factor models, the relative increase in environmental efficiency actually corresponds to the decoupling index, but for multi-factor models this relationship weakens with economic growth, especially as the model dimension increases. In general, as the ecological efficiency of the economy increases, a positive decoupling effect is observed. A study of the Volga Federal District regions showed that the greatest environmental efficiency in recent years has been observed in the Republic of Mordovia and the Perm Territory. And in the Chuvash Republic and the Saratov region, environmental efficiency remains significantly below the base period of 2010-2014.

Achievable Spectral Efficiency of Line-of-Sight MIMO Fixed Links with Compact Planar Antenna Arrays and Power Amplifier Limitations

Fixed Point-to-Point microwave wireless systems with high spectral efficiency are needed to meet the pervasive and increasing demand for capacity in back-haul networks of mobile radio systems. In this context, spatially multiplexed LoS-MIMO (Line-of-Sight Multiple Input Multiple Output) systems have been studied for about twenty years, particularly in the millimeter wave frequency bands (above 15 GHz). However, their deployment in real networks has been really limited, to the authors’ knowledge. This has been due to several factors, i.e. the practical possibility of using extremely high-level modulation formats (nowadays up to 8192-QAM), the joint use of co-channel dual polarization, and the availability of wider channel bands in the new high frequency ranges (e.g. E-Band). In addition, a crucial reason has been the difficulty of installing multiple antennas spaced apart in order to maximize the MIMO spatial multiplexing so providing the maximum capacity gain. This optimal antenna separation, even for the classical MIMO M×N\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$M \ imes N$$\\end{document} with M = 2 antennas at the receiver and N = 2 antennas at the transmitter, can be several meters, e.g. 5.71 m at 23 GHz on a 5 km link. In this article, we analyze the performance of LoS-MIMO systems where antenna separation is highly sub-optimal, for limiting the array size, and a satisfactory performance is made possible by the exploitation of specific bit loading and power allocation strategies and the setting of the working region of the RF transmitter power amplifiers to operate at a given Signal-to-Inter Modulation Distortion Ratio (SIMDR). The result is an overview of the advantages and drawbacks of compact LoS-MIMO from a wider perspective than in the existing literature, including fundamental aspects for the practical implementation of these systems. Performance is discussed in many cases of interest and compared with the state of the art SISO (Single Input Single Output) system.

A Chromo-fluorogenic Probe for Selective Detection of Picric Acid Alongside Its Recovery by Aliphatic Amines and Construction of Molecular Logic Gates.

Nitroaromatic compounds are illicit explosive chemicals. For environmental security and homeland safety, selective and sensitive identification of these secondary-class explosives has been a reason for the exhaustive research arena of chemists for about a decade. We introduced a sensitive optical sensor with desalted neutral red (NR) dye. After ingressing picric acid (PA) in acetonitrile, the probe becomes non-fluorescent, displaying a colorimetric changefrom yellow to pink. The quenched phenomena and the changed color were re-established with aliphatic amine, trimethylamine (TEA). The reversibility is produced cyclically, both in fluorimetrically and spectrophotometrically. The detection limit for PA with our probe comes out as 0.639µM; this value is significantly lower than many chemosensors available in the literature. Also, NR-stained filter paper strips-based test kit analysis has been deployed as a displayable photonic device for in-situ detection of PA. Furthermore, the whole system was conceptualized to produce single input, single output, and double input single output logic gates, which can be applied to digital devices. The chronological input manner as NTP (NR- TEA-PA) pushed us to configure a molecular keypad lock system, the basis of digital locking devices. The repeatable & reversible detection system exhibits "Write read- Erase-read Write-read' type memory devices.

Data driven approach for weight restricted data envelopment analysis models with single output

This study aims to explore whether a machine learning algorithm can be used to make improvements in assessing unit efficiencies via a data envelopment analysis (DEA) model. In this study, a DEA model is used to calculate the efficiency scores of Desicion Making Units (DMUs). Then, an ML algorithm is trained that aims to predict the single output using inputs. Ranking of input features based on relative feature importance values obtained from the trained ML model is fed to the DEA model as weight restrictions. As a result, the two DEA models are compared with each other. ML-based insights (feature importance ranking) improve the DEA model in the direction of fewer zero weights. The additional weight restrictions are data depdendent, and hence realistic. As a novel approach, this study proposes the use of machine learning-based feature importance values to overcome a limitation of a DEA model.

Combining ternary phase diagrams and multiphase coupled matrix-based Monte Carlo to model phase dependent compositional and molar mass variations in high impact polystyrene synthesis

High impact polystyrene (HIPS) production starts from a homogeneous grafting of styrene (St) on polybutadiene (PB). However, already at low St conversion, the reaction mixture becomes heterogeneous due to the incompatibility between polystyrene (PS) and PB. First a PS-rich phase appears, dispersed in a PB-rich phase, and then the situation reverses. At even higher St conversions, the PB-rich phase also includes PS occlusions (defined as a third phase). In the present work, a multiphase coupled matrix-based Monte Carlo (CMMC) model is presented, tracking the molecular variations of individual molecules for the first time per phase. This is done accounting for (i) phase equilibria as inputted based on a literature-based ternary phase diagram for St-PB-PS mixtures, and (ii) diffusional limitations by means of apparent rate coefficients, demonstrating a preference for the composite kt model for the representation of the gel-effect. The simplified single phase model output is acceptable up to St conversions of 30 %, justifying the previous efforts on tuning modeling parameters also including model validation for high yield general purpose PS synthesis. However, at higher St conversions (up to 60 %), a single phase model predicts too high St amounts in the graft copolymer, and too low PS average chain lengths and dispersities. Furthermore, post-processing at a given St conversion reveals the contributions to the total PS log-molar mass distribution (log-MMD) from the PS-rich phase, the PB-rich phase, and PS occlusions. Moreover, the multimodality of the observed (total) log-MMD is uniquely explained based on these contributions, with specifically a more pronounced second peak due to blocked mass transfer of PS to the PS-rich phase at higher St conversions.

Optical characterization of mass-productive metal-insulator-metal plasmonic waveguide with a linear taper for nanofocusing.

This paper conducts an experimental evaluation of the optical properties of mass-productive metal-insulator-metal linear taper waveguides for nanofocusing. The vertical linear tapers, with controlled angles in the 12-51 degrees range, were realized with dry etching and mixed gas, while tip-thickness was precisely controlled with atomic layer deposition. The transmission efficiency of the linear taper was measured employing an input grating and a single output slit. The maximum transmission efficiency was estimated at 64% at a taper angle of 30 degrees, which aligned with the calculations. This experimental evaluation provides guidance for the design of practical nanofocusing components.

A Single-Stage Isolated Battery Charger Using Nonbridged Positive Cuk Converter Configuration

This article presents a nonbridged isolated positive Cuk (NB-IPCuk) converter-based single-stage battery charging system (SSBCS). The architecture of the suggested charger ensures the intrinsic advantage of power quality improvement in discontinuous current conduction (DCC) mode at the supply mains. The suggested NB-IPCuk converter scheme has fewer components than other bridgeless/nonbridged Cuk converter schemes. This is because the NB-IPCuk converter is a partial integration of two Cuk converters. The usage of the Cuk converter garnishes the system with input and output inductances, which lessens supply current harmonic distortion and, thus supply terminal low pass filter requirement is eradicated. The advantages of the NB-IPCuk converter are the eradication of one inductor and multiple diodes (two back-feeding diodes), which are generally used in NB converter configurations. In place of two separate inductors, the NB-IPCuk converter uses a single secondary side output inductor. The usage of BL configuration of NB-IPCuk converter eradicates the bridge rectifier (BR) stage, and thus, the BR-associated losses also got eradicated. The NB-IPCuk converter also garnishes the system with electrical isolation which adds to the safety standards of the system. DCC mode operation of the NB-IPCuk converter is used in the present work. DCC mode requires lesser sensors in comparison to continuous current conduction mode. The abovementioned benefits of the NB-IPCuk converter make the SSBCS system cheaper, compact, and more efficient. The detailed stability analysis (Bode diagram and pole-zero map) and mathematics for the NB-IPCuk converter are also included in the paper. The prototype and MATLAB/Simulink model of NB-IPCuk converter-based SSBCS system with DCC mode control has been built, and results of both prototype and MATLAB/Simulink are deployed to verify SSBCS system’s performance during dynamic and steady-state conditions.

Single PCB sensor-based output current reproduction for three-phase inverter systems

This study proposes a practical output current measurement system in a three-phase inverter with a single printed circuit board (PCB) Rogowski coil sensor inserted in the bus between the DC-link capacitor and the power semiconductor module. This system demonstrates its advantage over conventional output current sensors, such as the Hall effect current sensors, in terms of the size, weight, operation temperature and cost. The system can be applied to 6-in-1 power modules as it does not require sensors in the inverter phase legs.In our previous works, we have developed a method called “envelope tracking”, which is used in this system as well. This method traces the switching current instead of the output current to reproduce the output current signal in real-time. Envelope tracking successfully reproduced the output current waveform for single phase inverters under certain conditions. However, a large error is observed in the three-phase inverter demonstration under a high switching frequency (narrow pulse) or when the switching of different phases overlap each other. These errors must be completely suppressed to implement the system for feedback control in three-phase inverters.In this study, a new analog basis output current waveform reproduction system is introduced to suppress the above mentioned errors. This system is implemented in a three-phase insulated-gate bipolar transistor (IGBT) inverter and successfully reproduces the output current with a single PCB sensor inserted between a 6-in-1 IGBT power module and DC-link capacitor, operating under a switching frequency of 3.5–7.0 kHz and output current of 6 A with DC-link voltage of 150 V.

Performance analysis of 160 Gbps-60 GHz OFDM-MIMO RoFSO transmission with WDM-PDM dual multiplexing

Abstract An orthogonal frequency division multiplexed-radio over free space optics (OFDM-RoFSO) communication system with dual multiplexing is proposed. Eight input data streams are transmitted simultaneously by using wavelength division multiplexing (WDM) at level 1 and polarization division multiplexing (PDM) at level 2. Input data streams 1–4 and 5–8 are assigned with same set of carrier frequencies i.e. 193.1 THz, 193.3 THz, 193.5 THz and 193.7 THz and separate polarization levels (X and Y polarized) before transmitting through RoFSO link. A total data rate of 160 Gbps (4 × 2 × 20 Gbps) is achieved in this design. With proposed system, channel performance is evaluated under the influence of atmospheric attenuation and turbulence conditions while measuring system BER, Q-factor, SNR and received power etc. The effect of channel crosstalk is analysed for WDM-PDM dual multiplexed design while considering single input single output (SISO) and multiple input multiple output (MIMO) FSO configurations. The overall analysis predicts that a higher transmission rate and improved capacity levels can easily be achieved with dual multiplexed system.

Multi-pulse random fiber laser with wide tuning range in L-band based on tunable band-pass filter and electro-optic modulator

In this paper, a L-band random fiber laser (RFL) with wide tuning range based on tunable band-pass filter (TBF) and electro-optic modulator (EOM) is proposed and studied. The L-band erbium-doped fiber amplifier (L-EDFA) is added to output L-band laser, and a wavelength tunable band-pass filter is used to generate tunable wavelength output. When the pump power is increased from 50mW to 350mW, the output spectra are all chaotic multi-wavelengths. After the filter being added, a stable narrow-band single-wavelength laser can be output in the range of 1564–1618 nm. An EOM is added to introduce actively Q-switched. When the pump power is 50mW, a stable single pulse output can be observed on the oscilloscope. When the pump power is 100mW, the output pulse is double pulse. When the pump power exceeds 100mW, three pulses or four pulses phenomenon appears. The adjustable multi-pulse laser has a wide application prospect in pulse coding, secure communication and other fields.