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Article ; Online: Design and Modeling of Modified Interleaved Phase-Shifted Semi-Bridgeless Boost Converter for EV Battery Charging Applications

Kanchana Kadirvel / Raju Kannadasan / Mohammed H. Alsharif / Zong Woo Geem

Sustainability, Vol 15, Iss 2712, p

2023 Volume 2712

Abstract: Electric vehicles (EVs) are set to become one of the domestic transportation systems that are highly preferred over conventional vehicles. Due to the huge demand for and cost of fuel, many people are switching over to EVs. Companies such as Tesla, BMW, ... ...

Abstract	Electric vehicles (EVs) are set to become one of the domestic transportation systems that are highly preferred over conventional vehicles. Due to the huge demand for and cost of fuel, many people are switching over to EVs. Companies such as Tesla, BMW, Audi, and Mercedes have started marketing EVs. These EVs need charging stations to charge the batteries. The challenges for EV batteries require the implementation of features such as fast charging, long-run utilization, reduced heat emission, a light weight, and a small size. However, fast charging using conventional converters generates an imbalance in current injection due to the passive component selection. In this study, a converter is proposed that uses an interleaved network that provides a balanced current injection; i.e., an improved interleaved phase-shifted semi-bridgeless boost converter (IIPSSBBC) is designed for EV battery charging applications. The suggested approach is mathematically designed using MATLAB/Simulink (2021) software. The result shows that the battery charging current achieves about 16.5 A, which is relatively more than conventional systems. Moreover, the charging time of the proposed converter is about 6 hrs for a 50 Ah battery with a discharge load capacity of 5000 W, which is relatively less than the conventional method. In a nutshell, compared with conventional converters, the IIPSSBBC performs better, and, notably, the charging speed and current injection are increased by two times the amount. Further, a prototype hardware model is developed to assess the performance of the proposed converter.
Keywords	modified interleaved phase-shifted semi-bridgeless boost converter ; battery charging ; electric vehicle ; zero emissions ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Subject code	600
Language	English
Publishing date	2023-02-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Sustainable development of fuel cell using enhanced weighted mean of vectors algorithm

Manish Kumar Singla / Jyoti Gupta / Parag Nijhawan / Mohammed H. Alsharif / Mun-Kyeom Kim

Heliyon, Vol 9, Iss 3, Pp e14578- (2023)

2023

Abstract: Using the mathematical model of a Direct Methanol Fuel Cell (DMFC) stack, a new optimum approach is presented for estimating the seven unknown parameters i.e., (eo, α, R, jeid, C1, β,req) optimally. Specifically, a method is proposed for minimization of ... ...

Abstract	Using the mathematical model of a Direct Methanol Fuel Cell (DMFC) stack, a new optimum approach is presented for estimating the seven unknown parameters i.e., (eo, α, R, jeid, C1, β,req) optimally. Specifically, a method is proposed for minimization of the Sum of Squared Errors (SSE) associated with the estimated polarization profile, based on the experimental data from simulations. The Enhanced Weighted mean of vectors (EINFO) algorithm is a novel metaheuristic method that is proposed to achieve this goal. An analysis of the results of this method is then compared to various metaheuristic algorithms such as the Particle Swarm Optimization (PSO), Sine Cosine Algorithm (SCA), Dragonfly Algorithm (DA), Atom Search Optimization (ASO), and Weighted mean of vectors (INFO) well known in literature. As a final step to confirm the proposed approach's effectiveness, the sensitivity analysis is carried out using temperature changes, along with comparison against different approaches described in the literature to demonstrate its superiority. After comparison of parameter estimation and different operating temperature a non-parametric test is also performed and compared with the rest of the metaheuristic algorithms used in the manuscript. From these tests it is concluded that the proposed algorithm is superior to the rest of the compared algorithms.
Keywords	Parameter extraction ; Mathematical modeling ; Sustainable development ; Optimization ; Non-parametric test ; Science (General) ; Q1-390 ; Social sciences (General) ; H1-99
Subject code	006
Language	English
Publishing date	2023-03-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Sustainable Development of a Direct Methanol Fuel Cell Using the Enhanced LSHADE Algorithm and Newton Raphson Method

Manish Kumar Singla / Jyoti Gupta / Mohammed H. Alsharif / Abu Jahid / Khalid Yahya

Sustainability, Vol 16, Iss 1, p

2023 Volume 62

Abstract: This paper presents a mathematical model for stacks of direct methanol fuel cells (DMFCs) using an optimised method. In order to reduce the sum of squared errors (SSE) in calculating the polarisation profile, the suggested technique makes use of ... ...

Abstract	This paper presents a mathematical model for stacks of direct methanol fuel cells (DMFCs) using an optimised method. In order to reduce the sum of squared errors (SSE) in calculating the polarisation profile, the suggested technique makes use of simulated experimental data. Given that DMFC is one of the viable fuel cell choices, developing an appropriate model is essential for cost reduction. However, resolving this issue has proven difficult due to its complex and highly nonlinear character, particularly when adjusting the DMFC model to various operating temperatures. By combining the algorithm and the objective function, the current work introduces a novel method called LSHADE (ELSHADE) for determining the parameters of the DMFC model. This technique seeks to accurately identify DMFCs’ characteristics. The ELSHADE method consists of two stages, the first of which is controlled by a reliable mutation process and the latter by a chaotic approach. The study also recommends an improved Newton–Raphson (INR) approach to deal with the chaotic nature of the I-V curve equation. The findings show that, when used on actual experimental data, the ELSHADE-INR technique outperforms existing algorithms in a variety of statistical metrics for accurately identifying global solutions.
Keywords	parameter extraction ; sustainability ; modelling of DMFC ; optimisation ; ELSHADE-INR ; operating temperature ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Language	English
Publishing date	2023-12-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A Low Complexity Near-Optimal Iterative Linear Detector for Massive MIMO in Realistic Radio Channels of 5G Communication Systems

Mahmoud A. Albreem / Mohammed H. Alsharif / Sunghwan Kim

Entropy, Vol 22, Iss 4, p

2020 Volume 388

Abstract: Massive multiple-input multiple-output (M-MIMO) is a substantial pillar in fifth generation (5G) mobile communication systems. Although the maximum likelihood (ML) detector attains the optimum performance, it has an exponential complexity. Linear ... ...

Abstract	Massive multiple-input multiple-output (M-MIMO) is a substantial pillar in fifth generation (5G) mobile communication systems. Although the maximum likelihood (ML) detector attains the optimum performance, it has an exponential complexity. Linear detectors are one of the substitutions and they are comparatively simple to implement. Unfortunately, they sustain a considerable performance loss in high loaded systems. They also include a matrix inversion which is not hardware-friendly. In addition, if the channel matrix is singular or nearly singular, the system will be classified as an ill-conditioned and hence, the signal cannot be equalized. To defeat the inherent noise enhancement, iterative matrix inversion methods are used in the detectors’ design where approximate matrix inversion is replacing the exact computation. In this paper, we study a linear detector based on iterative matrix inversion methods in realistic radio channels called QUAsi Deterministic RadIo channel GenerAtor (QuaDRiGa) package. Numerical results illustrate that the conjugate-gradient (CG) method is numerically robust and obtains the best performance with lowest number of multiplications. In the QuaDRiGA environment, iterative methods crave large <semantics> n </semantics> to obtain a pleasurable performance. This paper also shows that when the ratio between the user antennas and base station (BS) antennas ( <semantics> β </semantics> ) is close to 1, iterative matrix inversion methods are not attaining a good detector’s performance.
Keywords	5G ; massive MIMO ; detection ; iterative matrix inversion methods ; QuaDRiGa ; Science ; Q ; Astrophysics ; QB460-466 ; Physics ; QC1-999
Subject code	518
Language	English
Publishing date	2020-03-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Sustainable Delay Minimization Strategy for Mobile Edge Computing Offloading under Different Network Scenarios

Admoon Andrawes / Rosdiadee Nordin / Zaid Albataineh / Mohammed H. Alsharif

Sustainability, Vol 13, Iss 12112, p

2021 Volume 12112

Abstract: The development of mobile edge computing (MEC) is expected to offer better performance in mobile communications than the current cloud computing architecture. MEC involves offering the closest access to the data source or physical mobile network ... ...

Abstract	The development of mobile edge computing (MEC) is expected to offer better performance in mobile communications than the current cloud computing architecture. MEC involves offering the closest access to the data source or physical mobile network environment. The network services are able to respond faster, thus satisfying the demands of the mobile network industry when deploying various potential business applications in real-time. Since the harvested mobile data are transferred to the edge server to make calculations, data transfers and faults in the mobile network can be swiftly pinpointed and removed accurately. Nevertheless, there are still problems in the practical application of the systems, specifically in reducing delays and lessening energy consumption. Because of non-orthogonal multiple access (NOMA) superior spectrum efficiencies, it is best to combine NOMA with MEC for simultaneous support of multiple access for end users, thus reducing transmission latencies and lowering energy consumption. Combining MEC and NOMA would offer many advantages, including superior energy savings, reductions in latency, massive connectivity, and the potential of combining with additional transmission technologies, such as millimetre-wave (mmWave) and M-MIMO. In this paper, designing wireless resource allocation is crucial for an economically viable low-latency wireless network, which can be realised using the Karush–Kuhn–Tucker (KKT) approach to obtain the optimal solution for partial and full offloading network traffic scenarios to minimize the total latency of the MEC network. The convergence and performance for orthogonal multiple access (OMA), pure-NOMA (P-NOMA), and hybrid-NOMA (H-NOMA) are also compared under different network traffic offloading scenarios. The significant results from this study showed the convergence of the optimal resource allocation in the case of full and partial offloading. The results demonstrated that the P-NOMA reduces the total offloading delay by about 11%.
Keywords	mobile edge computing ; NOMA ; full offloading ; partial offloading ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Subject code	303 ; 000
Language	English
Publishing date	2021-11-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: An Anonymous Certificateless Signcryption Scheme for Secure and Efficient Deployment of Internet of Vehicles

Insaf Ullah / Muhammad Asghar Khan / Mohammed H. Alsharif / Rosdiadee Nordin

Sustainability, Vol 13, Iss 10891, p

2021 Volume 10891

Abstract: Internet of Vehicles (IoV) is a specialized breed of Vehicular Ad-hoc Networks (VANETs) in which each entity of the system can be connected to the internet. In the provision of potentially vital services, IoV transmits a large amount of confidential data ...

Abstract	Internet of Vehicles (IoV) is a specialized breed of Vehicular Ad-hoc Networks (VANETs) in which each entity of the system can be connected to the internet. In the provision of potentially vital services, IoV transmits a large amount of confidential data through networks, posing various security and privacy concerns. Moreover, the possibility of cyber-attacks is comparatively higher when data transmission takes place more frequently through various nodes of IoV systems. It is a serious concern for vehicle users, which can sometimes lead to life-threatening situations. The primary security issue in the provision of secure communication services for vehicles is to ensure the credibility of the transmitted message on an open wireless channel. Then, receiver anonymity is another important issue, i.e., only the sender knows the identities of the receivers. To guarantee these security requirements, in this research work, we propose an anonymous certificateless signcryption scheme for IoV on the basis of the Hyperelliptic Curve (HEC). The proposed scheme guarantees formal security analysis under the Random Oracle Model (ROM) for confidentiality, unforgeability, and receiver anonymity. The findings show that the proposed scheme promises better security and reduces the costs of computation and communication.
Keywords	Internet of Things ; Internet of Vehicles ; security ; hyperelliptic curve ; random oracle model ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Subject code	303
Language	English
Publishing date	2021-09-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Electrical and Mechanical Characteristics Assessment of Wind Turbine System Employing Acoustic Sensors and Matrix Converter

Thiyagarajan Rameshkumar / Perumal Chandrasekar / Raju Kannadasan / Venkatraman Thiyagarajan / Mohammed H. Alsharif / James Hyungkwan Kim

Sustainability, Vol 14, Iss 4404, p

2022 Volume 4404

Abstract: Permanent magnet synchronous generator (PMSG)-based wind turbine systems have a wide range of applications, notably, for higher-rated wind energy conversion systems (WECS). A WECS involves integrating several components to generate electrical power ... ...

Abstract	Permanent magnet synchronous generator (PMSG)-based wind turbine systems have a wide range of applications, notably, for higher-rated wind energy conversion systems (WECS). A WECS involves integrating several components to generate electrical power effectively on a large scale due to the advanced wind turbine model. However, it offers several glitches during operation due to various factors, notably, mechanical and electrical stresses. This work focuses on evaluating the mechanical and electrical characteristics of the WECS using two individual schemes. Firstly, wind turbines were examined to assess the vibrational signatures of the drive train components for different wind speed profiles. To apply this need, acoustic sensors were employed that record the vibration signals. However, due to substantial environmental impacts, several noises are logged with the observed signal from sensors. Therefore, this work adapted the acoustic signal and empirical wavelet transform (EWT) to assess the vibration frequency and magnitude to avoid mechanical failures. Further, a matrix converter (MC) with input filters was employed to enhance the efficiency of the system with reduced harmonic contents injected into the grid. The simulated results reveal that the efficiency of the matrix converter with input filter attained a significant scale of about 95.75% and outperformed the other existing converting techniques. Moreover, the total harmonic distortion (THD) for voltage and current were examined and found to be at least about 8.24% and 3.16%, respectively. Furthermore, the frequency and magnitude of the vibration signals show a minimum scale for low wind speed profile and higher range for medium wind profile rather than higher wind profile. Consolidating these results from both mechanical and electrical characteristics, it can be perceived that the combination of these schemes improves the efficiency and quality of generated power with pre-estimation of mechanical failures using acoustic signal and EWT.
Keywords	acoustic sensors ; empirical wavelet transform (EWT) ; matrix converter ; input filter ; power quality ; vibrational assessment ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Subject code	600 ; 551
Language	English
Publishing date	2022-04-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A Hybrid Multi-Objective Optimizer-Based SVM Model for Enhancing Numerical Weather Prediction

Mohanad A. Deif / Ahmed A. A. Solyman / Mohammed H. Alsharif / Seungwon Jung / Eenjun Hwang

Sustainability, Vol 14, Iss 296, p

A Study for the Seoul Metropolitan Area

2022 Volume 296

Abstract: Temperature forecasting is an area of ongoing research because of its importance in all life aspects. However, because a variety of climate factors controls the temperature, it is a never-ending challenge. The numerical weather prediction (NWP) model has ...

Abstract	Temperature forecasting is an area of ongoing research because of its importance in all life aspects. However, because a variety of climate factors controls the temperature, it is a never-ending challenge. The numerical weather prediction (NWP) model has been frequently used to forecast air temperature. However, because of its deprived grid resolution and lack of parameterizations, it has systematic distortions. In this study, a gray wolf optimizer (GWO) and a support vector machine (SVM) are used to ensure accuracy and stability of the next day forecasting for minimum and maximum air temperatures in Seoul, South Korea, depending on local data assimilation and prediction system (LDAPS; a model of local NWP over Korea). A total of 14 LDAPS models forecast data, the daily maximum and minimum air temperatures of in situ observations, and five auxiliary data were used as input variables. The LDAPS model, the multimodal array (MME), the particle swarm optimizer with support vector machine (SVM-PSO), and the conventional SVM were selected as comparison models in this study to illustrate the advantages of the proposed model. When compared to the particle swarm optimizer and traditional SVM, the Gray Wolf Optimizer produced more accurate results, with the average RMSE value of SVM for T max and T min Forecast prediction reduced by roughly 51 percent when combined with GWO and 31 percent when combined with PSO. In addition, the hybrid model (SVM-GWO) improved the performance of the LDAPS model by lowering the RMSE values for T max Forecast and T min Forecast forecasting from 2.09 to 0.95 and 1.43 to 0.82, respectively. The results show that the proposed hybrid (GWO-SVM) models outperform benchmark models in terms of prediction accuracy and stability and that the suggested model has a lot of application potentials.
Keywords	support vector machine (SVM) ; gray wolf optimizer (GWO) ; temperature forecasting ; numerical weather prediction (NWP) model ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Language	English
Publishing date	2022-12-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Optimal Solar Power System for Remote Telecommunication Base Stations

Mohammed H. Alsharif / Jeong Kim

Sustainability, Vol 8, Iss 9, p

A Case Study Based on the Characteristics of South Korea’s Solar Radiation Exposure

2016 Volume 942

Abstract: This paper aims to address both the sustainability and environmental issues for cellular base stations in off-grid sites. For cellular network operators, decreasing the operational expenditures of the network and maintaining profitability are important ... ...

Abstract	This paper aims to address both the sustainability and environmental issues for cellular base stations in off-grid sites. For cellular network operators, decreasing the operational expenditures of the network and maintaining profitability are important issues. Hence, this study addresses the feasibility of a solar power system based on the characteristics of South Korean solar radiation exposure to supply the required energy to a remote cellular base station. The HOMER is used to determine the optimum size of the system components, to perform an energy production analysis, and to analyse the cost details of the project. The simulation results show that the proposed solar power system can achieve total operational expenditure savings of up to 48.6% by using sustainable and clean energy. This result means a significant long-term benefit can be achieved for cellular network operators.
Keywords	PV System ; cellular networks ; solar base station ; HOMER ; OPEX ; sustainable energy ; clean energy ; South Korea ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Subject code	600
Language	English
Publishing date	2016-09-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A Novel Multiobjective Hybrid Technique for Siting and Sizing of Distributed Generation and Capacitor Banks in Radial Distribution Systems

Chandrasekaran Venkatesan / Raju Kannadasan / Mohammed H. Alsharif / Mun-Kyeom Kim / Jamel Nebhen

Sustainability, Vol 13, Iss 3308, p

2021 Volume 3308

Abstract: Distributed generation (DG) and capacitor bank (CB) allocation in distribution systems (DS) has the potential to enhance the overall system performance of radial distribution systems (RDS) using a multiobjective optimization technique. The benefits of CB ...

Abstract	Distributed generation (DG) and capacitor bank (CB) allocation in distribution systems (DS) has the potential to enhance the overall system performance of radial distribution systems (RDS) using a multiobjective optimization technique. The benefits of CB and DG injection in the RDS greatly depend on selecting a suitable number of CBs/DGs and their volume along with the finest location. This work proposes applying a hybrid enhanced grey wolf optimizer and particle swarm optimization (EGWO-PSO) algorithm for optimal placement and sizing of DGs and CBs. EGWO is a metaheuristic optimization technique stimulated by grey wolves. On the other hand, PSO is a swarm-based metaheuristic optimization algorithm that finds the optimal solution to a problem through the movement of the particles. The advantages of both techniques are utilized to acquire mutual benefits, i.e., the exploration ability of the EGWO and the exploitation ability of the PSO. The proposed hybrid method has a high convergence speed and is not trapped in local optimal. Using this hybrid method, technical, economic, and environmental advantages are enhanced using multiobjective functions (MOF) such as minimizing active power losses, voltage deviation index (VDI), the total cost of electrical energy, and total emissions from generation sources and enhancing the voltage stability index (VSI). Six different operational cases are considered and carried out on two standard distribution systems, namely, IEEE 33- and 69-bus RDSs, to demonstrate the proposed scheme’s effectiveness extensively. The simulated results are compared with existing optimization algorithms. From the obtained results, it is observed that the proposed EGWO-PSO gives distinguished enhancements in multiobjective optimization of different conflicting objective functions and high-level performance with global optimal values.
Keywords	capacitor bank (CB) ; distributed generation (DG) ; enhanced grey wolf optimizer and particle swarm optimization (EGWO-PSO) ; power loss ; voltage deviation index (VDI) ; voltage stability index (VSI) ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Subject code	620
Language	English
Publishing date	2021-03-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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