European Journal of Electrical Engineering and Computer Science

An Integrated Engine Control Unit for a Spark Ignited Internal Combustion Engine

2023-11-20T15:23:56-05:00

A stepping valve system has been proposed before and proved to be feasible. The stepping valve move perpendicular to the piston, thereby avoiding piston-valve collisions associated with interference engines. In this study, the proposed Stepping Valve Control Unit, SVCU, was integrated with the conventional Engine Control Unit, ECU, of a simple SI engine. The resulting Integrated Engine Control Unit, IECU, as it is called, simplified the design of the ECU. The integration involved combining the basic fuel injector and sparking controls with the SVCU. The camshaft and crankshaft sensors were replaced by a Piston Direction Sensor, PDS. The PDS is an optical sensor, which works in conjunction with a gray coded trigger wheel to relay information to the IECU. The IECU was simulated using Quartus II design software. The hardware implementation of the IECU was done using EPM7128SL FPGA contained within the UP1 Altera Development Board. The behavior of the IECU was expected.

Analysis of Electroencephalography (EEG) Electrode-Pair Correlations

2023-11-08T15:19:35-05:00

We measured electroencephalography (EEG) data streams from participants wearing a wireless EEG headset in two modes: eyes open and eyes closed. Then we analyzed the data by computing the correlation coefficients for a pair of electrodes in each measurement mode. We also plotted and visually inspected the associated scatter plots. We observed that for the electrodes selected, the signals were more strongly correlated in the eyes closed mode and relatively weakly correlated in the eyes open mode. In most measurements, the signals were dissimilar. These observations could be harnessed to inform expedient placement of EEG electrodes and efficient selection of data stream channels for further analysis.

Adaptive Demand-Side Management Algorithm for Grid-Integrated PV-Wind-Battery-Hydrogen Systems Using Model Predictive Control

2023-11-10T15:20:04-05:00

Systems for producing green hydrogen will be essential in the move away from fossil fuels and towards technology that produces no carbon emissions. In order to undertake PV-Wind-H2 design for various hybrid configurations, this study provides a novel model for an off-grid hydrogen plant coupled with wind power, solar photovoltaic, and a battery energy storage system. This model makes use of meteorological information as well as component electrical variables. The objectives are to size and operate the systems properly in order to reach production targets while reducing H2 expenses. The direct connection of a PV-Wind-Electrolyser optimises component sizes and hydrogen generation, with the Electrolyser curves determined by the area and number of Electrolyser cells linked to photovoltaic modules. The coupling factor is increased when maximum power point (MPP) tracking is used. However, when compared to optimal PV-Wind-Electrolyser coupling, this gain is minimal. The advantage of battery-assisted electrolysis is that it minimises the size of the electrolyzer, illustrating how easy it is to run it at part loads. As a result, the photovoltaic-Wind and Electrolyzer are bigger to allow H2 generation, but the batteries work much better.

Cluster Head Selection in Device to Device (D2D) Communication Based on Weighted Network Performance Factor

2023-11-14T15:20:50-05:00

In this study, an unsupervised machine learning algorithm, Self Organizing Map was utilized to cluster D2D User Equipment using their network values as inputs. A weighting factor referred to as Hardware Sensing Factor (HSF) was formulated to take into account the device’s channel quality and the status of its underlying hardware circuitry. The values of the HSF were used as inputs to cluster the devices and to select cluster head for each cluster. The performance of SOM when HSF was input was compared with the performance when RSSI, RSRP or RSRQ was used as input. The comparison showed that the use of HSF as input to SOM cluster algorithm gave better cluster performance than the use of respective network values such as RSSI, RSRP or RSRQ. In addition, the use of HSF as input data to both SOM and K-Means algorithms showed that SOM cluster formation has better performance than K-Means algorithm.

Security, Privacy Challenges and Available Countermeasures in Electronic Health Record Systems: A Review

2023-11-20T15:23:43-05:00

Electronic Health Record (EHR) systems have revolutionized the healthcare industry by enabling the efficient storage, retrieval, and sharing of patient health information. However, the widespread adoption of EHR systems has also engendered a myriad of privacy and security challenges that must be spoke to guarantee the privacy, integrity, and accessibility of sensitive patient evidence. A range of countermeasures has been implemented to reduce the risks associated with EHR data privacy and security. These include contact switch tools that limit data access to approved operators, as well as advanced encryption methods like Identity-Based Encryption and Attribute-Based Encryption, specifically tailored for securing EHR data in cloud environments. By employing these protective measures, healthcare providers can enhance the safety of sensitive patient information while adapting to the dynamic digital landscape.

Analysis of Decoupling Capacitor Performance in Improving Power Integrity in Two Layer/Three Layer Printed Circuit Boards

2023-11-22T15:24:58-05:00

Electronic circuits can only function properly if supplied with clean power. The clean power is only possible if the AC. & D.C. noise in the power supply voltage which is supplied to electronic devices is below tolerance limits. To keep this noise within the limits, the impedance of Power Distribution Network (PDN) should be as minimal as possible. The use of Decoupling Capacitors is the most proven strategy to keep the PDN impedance low. In this paper, an attempt has been made to analyze the performance of PDN of a two-layer and three-layer P.C. Board, for the same set of Decoupling Capacitors. The PDN design has been carried out to meet an assumed set of specifications. The values of Interconnection Inductance have been obtained. The Interconnection Inductance is mostly responsible for PDN impedance, especially at higher frequencies. The simulations have been conducted for the PDN impedance of a two-layer as well as a three-layer P.C. Board. From the simulated impedance profiles, it is evident that PDN impedance obtained for a two-layer P.C. board is almost similar to that of a three-layer one if the width of the power supply trace is suitably tailored. It is therefore more prudent to go for a two-layer PDN configuration considering its simplicity and economy.

Smart Control Solution for Single-Stage Solar PV Systems

2023-11-21T15:23:48-05:00

Solar photovoltaic (PV) systems unpredictable characteristics and tight grid-codes demand power electronic-based energy conversion devices. Hence, as the power levels generated by the solar PV systems rise, multi-level voltage source converters (VSC) and their control mechanisms become more necessary for effective energy conversion. Continuous control set model predictive control (CCS-MPC) is a class of predictive control approach that has emerged recently for the applications of power converters and energy conversion systems. In this paper, an artificial neural network (ANN) based controller for single-stage grid-connected PV is implemented. The CCS-MPC is used as an expert / a teacher to generate the data required for off-line training of the neural network controller. After the off-line training, the trained ANN can fully control the inverter’s output voltage and track the maximum power point (MPP) without the need for MPC during testing. The proposed control technique is assessed under various operating conditions. Based on the results obtained, it is observed that the proposed techniques offer improved objective tracking and comparative dynamic response with respect to the classical approaches.

New Methods of Simulating Radar Clutter Return Arrays

2023-07-28T22:43:24-04:00

Acquiring and recording clutter return data in a radar station is a crucial approach but a high price must be paid. Simulating various radar clutters through computer operation is an efficient approach and not much price is paid in a radar laboratory nowadays. Based on three common U(0,1) random sources from Fortran, MatLab, and chaotic Logistic programs, we compare their statistics: autocorrelation, cross-correlation, probability densities, etc. Fortran U(0,1) is found to be a better random source for our sake. Based on the study of uniform-and staggered-PRI (pulse repetition interval) waveforms, coherent transmitting and receiving, pulse compression technology, etc., we propose three algorithms, LU matrix decomposition, FIR (finite impulse response) filtering interpolation, and IIR (infinite impulse response) filtering, for simulating range-azimuth clutter arrays, which engage conventional characteristics: uniform or staggered PRIs and Doppler spectra. Their mathematic equations and algorithm computations are described. Many simulation tests are achieved to verify the validity and effectiveness of the algorithms; the clutter arrays with a few radar signal characteristics are demonstrated. Furthermore, through the study of two-type pulse compressions, phase code and LFM (linear frequency modulation), and large time-width pulse wave’s backscattering, we create a mechanism of discrete and continuous dynamical systems forming the pulse compression clutter returns, then simulate the composite clutter arrays, which characterize pulse compression over range cells and the Doppler spectra over azimuth cells with staggered PRIs. Finally, we discuss combination algorithms for nonstationary radar clutter arrays, which have two typical models of nonstationary environments, continuously-varying spectral parameters, and step-varying translation of backscattering regions.