Search results for: solar powered vehicle

Authors: Ali Mashayekh, Mahdiye Khorasani, Thomas weyh

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The demand for battery electric vehicles (BEV) is steadily increasing, and it can be assumed that electric mobility will dominate the market for individual transportation in the future. Regarding BEVs, the focus of state-of-the-art research and development is on vehicle batteries since their properties primarily determine vehicles' characteristic parameters, such as price, driving range, charging time, and lifetime. State-of-the-art battery packs consist of invariable configurations of battery cells, connected in series and parallel. A promising alternative is battery systems based on multilevel inverters, which can alter the configuration of the battery cells during operation via semiconductor switches. The main benefit of such topologies is that a three-phase AC voltage can be directly generated from the battery pack, and no separate power inverters are required. Therefore, modular battery systems based on different multilevel inverter topologies and reconfigurable battery systems are currently under investigation. Another advantage of the multilevel concept is that the possibility to reconfigure the battery pack allows battery cells with different states of charge (SoC) to be connected in parallel, and thus low-loss balancing can take place between such cells. In contrast, in conventional battery systems, parallel connected (hard-wired) battery cells are discharged via bleeder resistors to keep the individual SoCs of the parallel battery strands balanced, ultimately reducing the vehicle range. Different multilevel inverter topologies and reconfigurable batteries have been described in the available literature that makes the before-mentioned advantages possible. However, what has not yet been described is how an intelligent operating algorithm needs to look like to keep the SoCs of the individual battery strands of a modular battery system with integrated power electronics balanced. Therefore, this paper suggests an SoC balancing approach for Battery Modular Multilevel Management (BM3) converter systems, which can be similarly used for reconfigurable battery systems or other multilevel inverter topologies with parallel connectivity. The here suggested approach attempts to simultaneously utilize all converter modules (bypassing individual modules should be avoided) because the parallel connection of adjacent modules reduces the phase-strand's battery impedance. Furthermore, the presented approach tries to reduce the number of switching events when changing the switching state combination. Thereby, the ohmic battery losses and switching losses are kept as low as possible. Since no power is dissipated in any designated bleeder resistors and no designated active balancing circuitry is required, the suggested approach can be categorized as a proactive balancing approach. To verify the algorithm's validity, simulations are used.

Keywords: battery management system, BEV, battery modular multilevel management (BM3), SoC balancing

Procedia PDF Downloads 120

Authors: Kristine Nore, Alexander Severnisen, Petter Arnestad, Dimitris Kraniotis, Roy Rossebø

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Natural materials like wood, absorb and release moisture. Thus wood can buffer indoor climate. When used wisely, this buffer potential can be used to counteract the outer climate influence on the building. The mass of moisture used in the buffer is defined as the potential hygrothermal mass, which can be an energy storage in a building. This works like a natural heat pump, where the moisture is active in damping the diurnal changes. In Norway, the ability of wood as a material used for climate buffering is tested in several buildings with the extensive use of wood, including supermarkets. This paper defines the potential of hygrothermal mass in a supermarket building. This includes the chosen ventilation strategy, and how the climate impact of the building is reduced. The building is located above the arctic circle, 50m from the coastline, in Valnesfjord. It was built in 2015, has a shopping area, including toilet and entrance, of 975 m². The climate of the area is polar according to the Köppen classification, but the supermarket still needs cooling on hot summer days. In order to contribute to the total energy balance, wood needs dynamic influence to activate its hygrothermal mass. Drying and moistening of the wood are energy intensive, and this energy potential can be exploited. Examples are to use solar heat for drying instead of heating the indoor air, and raw air with high enthalpy that allow dry wooden surfaces to absorb moisture and release latent heat. Weather forecasts are used to define the need for future cooling or heating. Thus, the potential energy buffering of the wood can be optimized with intelligent ventilation control. The ventilation control in Valnesfjord includes the weather forecast and historical data. That is a five-day forecast and a two-day history. This is to prevent adjustments to smaller weather changes. The ventilation control has three zones. During summer, the moisture is retained to dampen for solar radiation through drying. In the winter time, moist air let into the shopping area to contribute to the heating. When letting the temperature down during the night, the moisture absorbed in the wood slow down the cooling. The ventilation system is shut down during closing hours of the supermarket in this period. During the autumn and spring, a regime of either storing the moisture or drying out to according to the weather prognoses is defined. To ensure indoor climate quality, measurements of CO₂ and VOC overrule the low energy control if needed. Verified simulations of the Valnesfjord building will build a basic model for investigating wood as a climate regulating material also in other climates. Future knowledge on hygrothermal mass potential in materials is promising. When including the time-dependent buffer capacity of materials, building operators can achieve optimal efficiency of their ventilation systems. The use of wood as a climate regulating material, through its potential hygrothermal mass and connected to weather prognoses, may provide up to 25% energy savings related to heating, cooling, and ventilation of a building.

Keywords: climate buffer, energy, hygrothermal mass, ventilation, wood, weather forecast

Procedia PDF Downloads 215

Authors: Rasaq Bolakale Salau, Maimuna Muhammad Abubakar, Jonathan Yisa, Muhammad Tauheed Bisiriyu, Jimoh Oladejo Tijani, Alexander Ifeanyi Ajai

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Vegetables oils are widely consumed in Nigeria. This has led to competitive manufacture of various oil brands. This leads increasing tendencies for fraud, labelling misinformation and other unwholesome practices. A total of thirty samples including raw and corresponding branded samples of vegetable oils were collected. The Oils were extracted from raw ground nut, soya bean and oil palm fruits. The GC-MS data was subjected to chemometric techniques of PCA and HCA. The SOLO 8.7 version of the standalone chemometrics software developed by Eigenvector research incorporated and powered by PLS Toolbox was used. The GCMS fingerprint gave basis for discrimination as it reveals four predominant but unevenly distributed fatty acids: Hexadecanoic acid methyl ester (10.27- 45.21% PA), 9,12-octadecadienoic acid methyl ester (10.9 - 45.94% PA), 9-octadecenoic acid methyl ester (18.75 - 45.65%PA), and Eicosanoic acid methyl ester (1.19% - 6.29%PA). In PCA modelling, two PCs are retained at cumulative variance captured at 73.15%. The score plots indicated that palm oil brands are most aligned with raw palm oil. PCA loading plot reveals the signature retention times between 4.0 and 6.0 needed for quality assurance and authentication of the oils samples. They are of aromatic hydrocarbons, alcohols and aldehydes functional groups. HCA dendrogram which was modeled using Euclidian distance through Wards method, indicated co-equivalent samples. HCA revealed the pair of raw palm oil brand and palm oil brand in the closest neighbourhood (± 1.62 % A difference) based on variance weighted distance. It showed Palm olein brand to be most authentic. In conclusion, based on the GCMS data with chemometrics, the authenticity of the branded samples is ranked as: Palm oil > Soya oil > groundnut oil.

Keywords: vegetable oil, authenticity, chemometrics, PCA, HCA, GC-MS

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Authors: Gian Bhushan, Vinkel Arora, M. L. Aggarwal

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The objective of the present study is to determine better eye end design of a mono leaf spring used in light motor vehicle. A conventional 65Si7 spring steel leaf spring model with standard eye, casted and riveted eye end are considered. The CAD model of the leaf springs is prepared in CATIA and analyzed using ANSYS. The standard eye, casted, and riveted eye leaf springs are subjected to similar loading conditions. The CAE analysis of the leaf spring is performed for various parameters like deflection and Von-Mises stress. Mass reduction of 62.9% is achieved in case of riveted eye mono leaf spring as compared to standard eye mono leaf spring for the same loading conditions.

Keywords: CAE, leaf spring, standard, casted, riveted eye

Procedia PDF Downloads 371

Authors: Kelaiaia Mounia Samira, Labar Hocine, Mesbah Tarek, Kelaiaia samia

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The photovoltaic panel produces green power, and because of its availability across the globe, it can supply isolated loads (site away of the electrical network or difficult of access). Unfortunately this energy remains very expensive. The most application of these types of power needs storage devices, the Lithium batteries are commonly used because of its powerful storage capability. Using a solar panel or an array of panels without a controller that can perform MPPT will often result in wasted power, which results in the need to install more panels for the same power requirement. For devices that have the battery connected directly to the panel, this will also result in premature battery failure or capacity loss. In this paper it is proposed a modified P&O algorithm for the MPPT which takes in account the battery’s internal resistance vs temperature and stage of charging. Of course the temperature variation and irradiation of the PV panel are also introduced.

Keywords: modeling, battery, MPPT, charging, PV Panel

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Authors: Christian Doppler, Gernot Hirschl, Gerhard Zsiga

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Starting from 2020, an EU-wide CO2-limitation of 95g/km is scheduled for the average of an OEMs passenger car fleet. Considering that, further measures of optimization on the diesel cycle will be necessary in order to reduce fuel consumption and emissions while keeping performance values adequate at the least. The present article deals with charge air cooling (CAC) on the basis of a diesel passenger car model in a 0D/1D-working process calculation environment. The considered engine is a 2.4 litre EURO VI diesel engine with variable geometry turbocharger (VGT) and low-pressure exhaust gas recirculation (LP EGR). The object of study was the impact of charge air cooling on the engine working process at constant boundary conditions which could have been conducted with an available and validated engine model in AVL BOOST. Part load was realized with constant power and NOx-emissions, whereas full load was accomplished with a lambda control in order to obtain maximum engine performance. The informative results were used to implement a simulation model in Matlab/Simulink which is further integrated into a full vehicle simulation environment via coupling with ICOS (Independent Co-Simulation Platform). Next, the dynamic engine behavior was validated and modified with load steps taken from the engine test bed. Due to the modular setup in the Co-Simulation, different CAC-models have been simulated quickly with their different influences on the working process. In doing so, a new cooler variation isn’t needed to be reproduced and implemented into the primary simulation model environment, but is implemented quickly and easily as an independent component into the simulation entity. By means of the association of the engine model, longitudinal dynamics vehicle model and different CAC models (air/air & water/air variants) in both steady state and transient operational modes, statements are gained regarding fuel consumption, NOx-emissions and power behavior. The fact that there is no more need of a complex engine model is very advantageous for the overall simulation volume. Beside of the simulation with the mentioned demonstrator engine, there have also been conducted several experimental investigations on the engine test bench. Here the comparison of a standard CAC with an intake-manifold-integrated CAC was executed in particular. Simulative as well as experimental tests showed benefits for the water/air CAC variant (on test bed especially the intake manifold integrated variant). The benefits are illustrated by a reduced pressure loss and a gain in air efficiency and CAC efficiency, those who all lead to minimized emission and fuel consumption for stationary and transient operation.

Keywords: air/water-charge air cooler, co-simulation, diesel working process, EURO VI fuel consumption

Procedia PDF Downloads 269

Authors: András Fülöp, Lejla Heilmann, Zsolt Szabó, Ákos Koós

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Microbial fuel cells (MFCs) present a sustainable biotechnological solution to future energy demands. The aim of this study was to construct soil based, single cell, membrane-less MFC systems, operated without treatment to continuously power on-site monitoring and control systems during the soil bioremediation processes. Our Pseudomonas aeruginosa 541 isolate is an ideal choice for MFCs, because it is able to produce pyocyanin which behaves as electron-shuttle molecule, furthermore, it also has a significant antimicrobial effect. We tested several materials and structural configurations to obtain long term high power output. Comparing different configurations, a proton exchange membrane-less, 0.6 m long with 0.05 m diameter MFC tubes offered the best long-term performances. The long-term electricity production were tested from starch, yeast extract (YE), carboxymethyl cellulose (CMC) with humic acid (HA) as a mediator. In all cases, 3 kΩ external load have been used. The two best-operated systems were the Pseudomonas aeruginosa 541 containing MFCs with 1 % carboxymethyl cellulose and the MFCs with 1% yeast extract in the anode area and 35% hydrogel in the cathode chamber. The first had 3.3 ± 0.033 mW/m2 and the second had 4.1 ± 0.065 mW/m2 power density values. These systems have operated for 230 days without any treatment. The addition of 0.2 % HA and 1 % YE referred to the volume of the anode area resulted in 1.4 ± 0.035 mW/m2 power densities. The mixture of 1% starch with 0.2 % HA gave 1.82 ± 0.031 mW/m2. Using CMC as retard carbon source takes effect in the long-term bacterial survivor, thus enable the expression of the long term power output. The application of hydrogels in the cathode chamber significantly increased the performance of the MFC units due to their good water retention capacity.

Keywords: microbial fuel cell, bioremediation, Pseudomonas aeruginosa, biotechnological solution

Procedia PDF Downloads 291

Authors: Elmo Thiago Lins Cöuras Ford, Valentina Alessandra Carvalho do Vale

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The simulation in wind tunnel is used thoroughly to model real situations of drainages of air. Besides the automotive industry, a great number of applications can be numbered: dispersion of pollutant, studies of pedestrians comfort and dispersion of particles. This work had the objective of visualizing the characteristics aerodynamics of two automobiles in different ways. To accomplish that drainage of air a fan that generated a speed exists (measured with anemometer of hot thread) of 4,1m/s and 4,95m/s. To visualize the path of the air through the cars, in the wind tunnel, smoke was used, obtained with it burns of vegetable oil. For “to do smoke” vegetable oil was used, that was burned for a tension of 20 V generated by a thread of 2,5 mm. The cars were placed inside of the wind tunnel with the drainage of “air-smoke” and photographed, registering like this the path lines around them, in the 3 different speeds.

Keywords: aerodynamics, vehicle drag, vegetable oil, wind tunnel

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Authors: Srinivas Vangari

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In the era of big data, ensuring the accuracy, consistency, and reliability of critical data assets is crucial for data-driven enterprises. Master Data Management (MDM) plays a crucial role in this endeavor. This paper investigates the role of Artificial Intelligence (AI) in enhancing MDM, focusing on how AI-driven solutions can automate and optimize various stages of the master data lifecycle. By integrating AI (Quantitative and Qualitative Analysis) into processes such as data creation, maintenance, enrichment, and usage, organizations can achieve significant improvements in data quality and operational efficiency. Quantitative analysis is employed to measure the impact of AI on key metrics, including data accuracy, processing speed, and error reduction. For instance, our study demonstrates an 18% improvement in data accuracy and a 75% reduction in duplicate records across multiple systems post-AI implementation. Furthermore, AI’s predictive maintenance capabilities reduced data obsolescence by 22%, as indicated by statistical analyses of data usage patterns over a 12-month period. Complementing this, a qualitative analysis delves into the specific AI-driven strategies that enhance MDM practices, such as automating data entry and validation, which resulted in a 28% decrease in manual errors. Insights from case studies highlight how AI-driven data cleansing processes reduced inconsistencies by 25% and how AI-powered enrichment strategies improved data relevance by 24%, thus boosting decision-making accuracy. The findings demonstrate that AI significantly enhances data quality and integrity, leading to improved enterprise performance through cost reduction, increased compliance, and more accurate, real-time decision-making. These insights underscore the value of AI as a critical tool in modern data management strategies, offering a competitive edge to organizations that leverage its capabilities.

Keywords: artificial intelligence, master data management, data governance, data quality

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Authors: Angelos Kaminis, Dakotah Stirnweis

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Advances in robotic technology have driven the development of improved robotic companions in the last couple decades. However, commercially available robotic companions lack the ability to create an emotional connection with their user. By developing a companion robot that has a symbiotic relationship with a plant, an element of co-dependency is introduced into the human companion robot dynamic. This companion robot, while theoretically capable of providing most of the plant’s needs, still requires human interaction for watering, moving obstacles, and solar panel cleaning. To facilitate the interaction between human and robot, the robot is capable of limited auditory and visual communication to help express its and the plant’s needs. This paper seeks to fully describe the Autonomous Plant Care Robot system and its symbiotic relationship with its botanical ward and the plant and robot’s dependent relationship with their owner.

Keywords: symbiotic, robotics, autonomous, plant-care, companion

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Authors: Nairy Kechichian

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The original Leclerc Bridge is a covered wooden bridge that is considered a Quebec heritage structure with an index of 60, making it a very important provincial bridge from a historical point of view. It was constructed in 1927 and is in the rural area of Abitibi-Temiscamingue. It is a “town Québécois” type of structure, which is generally rare but common for covered bridges in Abitibi-Temiscamingue. This type of structure is composed of two trusses on both sides formed with diagonals, internal bracings, uprights and top and bottom chords to allow the transmission of loads. This structure is mostly known for its solidity, lightweightness, and ease of construction. It is a single-span bridge with a length of 25.3 meters and allows the passage of one vehicle at a time with a 4.22-meter driving lane. The structure is composed of 2 trusses located at each end of the deck, two gabion foundations at both ends, uprights and top and bottom chords. WSP (Williams Sale Partnership) Canada inc. was mandated by the Transport Minister of Quebec in 2019 to increase the capacity of the bridge from 5 tons to 30.6 tons and rehabilitate it, as it has deteriorated quite significantly over the years. The bridge was damaged due to material deterioration over time, exposure to humidity, high load effects and insect infestation. To allow the passage of 3 axle trucks, as well as to keep the integrity of this heritage structure, the final design chosen to rehabilitate the bridge involved adding a new deck independent from the roof structure of the bridge. Essentially, new steel beams support the deck loads and the desired vehicle loads. The roof of the bridge is linked to the steel deck for lateral support, but it is isolated from the wooden deck. The roof is preserved for aesthetic reasons and remains intact as it is a heritage piece. Due to strict traffic management obstacles, an efficient construction method was put into place, which consisted of building a temporary bridge and moving the existing roof onto it to allow the circulation of vehicles on one side of the temporary bridge while providing a working space for the repairs of the roof on the other side to take place simultaneously. In parallel, this method allowed the demolition and reconstruction of the existing foundation, building a new steel deck, and transporting back the roof on the new bridge. One of the main criteria for the rehabilitation of the wooden bridge was to preserve, as much as possible, the existing patrimonial architectural design of the bridge. The project was completed successfully by the end of 2021.

Keywords: covered bridge, wood-steel, short span, town Québécois structure

Procedia PDF Downloads 67

Authors: Aydin Azizi, Aburrahman Tanira

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The main source of energy used in this modern age is fossil fuels. There is a myriad of problems that come with the use of fossil fuels, out of which the issues with the greatest impact are its scarcity and the cost it imposes on the planet. Fossil fuels are the only plausible option for many vital functions and processes; the most important of these is transportation. Thus, using this source of energy wisely and as efficiently as possible is a must. The aim of this work was to explore utilising mathematical modelling and artificial intelligence techniques to enhance fuel consumption in passenger cars by focusing on the speed at which cars are driven. An artificial neural network with an error less than 0.05 was developed to be applied practically as to predict the rate of fuel consumption in vehicles.

Keywords: mathematical modeling, neural networks, fuel consumption, fossil fuel

Procedia PDF Downloads 405

Authors: Papakonstantinou Apostolos, Argyrios Moustakas, Panagiotis Zervos, Dimitrios Stefanakis, Manolis Tsapakis, Nektarios Spyridakis, Mary Paspaliari, Christos Kontos, Antonis Legakis, Sarantis Houzouris, Konstantinos Topouzelis

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For years unmanned and remotely operated robots have been used as tools in industry research and education. The rapid development and miniaturization of sensors that can be attached to remotely operated vehicles in recent years allowed industry leaders and researchers to utilize them as an affordable means for data acquisition in air, land, and sea. Despite the recent developments in the ground and unmanned airborne vehicles, a small number of Unmanned Surface Vehicle (USV) platforms are targeted for mapping and monitoring environmental parameters for research and industry purposes. The ARGO project is developed an open-design USV equipped with multi-level control hardware architecture and state-of-the-art sensors and payloads for the autonomous monitoring of environmental parameters in large sea areas. The proposed USV is a catamaran-type USV controlled over a wireless radio link (5G) for long-range mapping capabilities and control for a ground-based control station. The ARGO USV has a propulsion control using 2x fully redundant electric trolling motors with active vector thrust for omnidirectional movement, navigation with opensource autopilot system with high accuracy GNSS device, and communication with the 2.4Ghz digital link able to provide 20km of Line of Sight (Los) range distance. The 3-meter dual hull design and composite structure offer well above 80kg of usable payload capacity. Furthermore, sun and friction energy harvesting methods provide clean energy to the propulsion system. The design is highly modular, where each component or payload can be replaced or modified according to the desired task (industrial or research). The system can be equipped with Multiparameter Sonde, measuring up to 20 water parameters simultaneously, such as conductivity, salinity, turbidity, dissolved oxygen, etc. Furthermore, a high-end multibeam echo sounder can be installed in a specific boat datum for shallow water high-resolution seabed mapping. The system is designed to operate in the Aegean Sea. The developed USV is planned to be utilized as a system for autonomous data acquisition, mapping, and monitoring bathymetry and various environmental parameters. ARGO USV can operate in small or large ports with high maneuverability and endurance to map large geographical extends at sea. The system presents state of the art solutions in the following areas i) the on-board/real-time data processing/analysis capabilities, ii) the energy-independent and environmentally friendly platform entirely made using the latest aeronautical and marine materials, iii) the integration of advanced technology sensors, all in one system (photogrammetric and radiometric footprint, as well as its connection with various environmental and inertial sensors) and iv) the information management application. The ARGO web-based application enables the system to depict the results of the data acquisition process in near real-time. All the recorded environmental variables and indices are presented, allowing users to remotely access all the raw and processed information using the implemented web-based GIS application.

Keywords: monitor marine environment, unmanned surface vehicle, mapping bythometry, sea environmental monitoring

Procedia PDF Downloads 139

Authors: Shengzhu Cao, Hui Zhou, Gan Wu, Lanxi Wanhg, Kaifeng Zhang, Rui Wang, Hu Wang

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The functional micro and nanostructures, which can endow material surface with unique properties such as super-absorptance, hydrophobic and drag reduction. Recently, femtosecond laser ablation has been demonstrated to be a promising technology for surface functional micro and nanostructures fabrication. In this paper, using femtosecond laser ablation processing technique, we fabricated functional micro and nanostructures on Ti and Al alloy surfaces, test results showed that processed surfaces have 82%~96% absorptance over a broad wavelength range from ultraviolet to infrared. The surface function properties, which determined by micro and nanostructures, could be modulated by variation laser parameters. These functional surfaces may find applications in such areas as photonics, plasmonics, spaceborne devices, thermal radiation sources, solar energy absorbers and biomedicine.

Keywords: surface functional, micro and nanostructures, femtosecond laser, ablation

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Authors: Pelin Onelcin, Yalcin Alver

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This paper investigates the walking speed and delays of pedestrians at two signalized intersections where the vehicle speed limits are different. Data was collected during afternoon and evening peak hours on November 15, 2013 and on December 6, 2013. Observational surveys were conducted by video recording technique. Pedestrians were categorized according to their gender, group size, stuff carrying condition and age. Results showed that individuals walked fastest when the group size is taken into consideration. The smallest 15th percentile walking speed was seen in the oldest age group (over 60 years old). Pedestrians experienced high delays both at roadsides and at medians. Factors affecting the pedestrian walking speed were analyzed by ANOVA.

Keywords: pedestrian delay, pedestrian walking speed, signalized crosswalk, ANOVA

Procedia PDF Downloads 395

Authors: Julius Agaka Yusufu, Tsutomu Dei, Hanif Ibrahim Awal

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This study undertakes the development of an optimal PV-diesel hybrid power system tailored to the specific energy landscape of Vimtim Mubi, Nigeria, utilizing real-world wind speed, solar radiation, and diesel cost data. Employing HOMER simulation, the research meticulously assesses the technical and financial viability of this hybrid configuration. Additionally, a rigorous performance comparison is conducted between the PV-diesel system and the conventional grid-connected alternative, offering crucial insights into the potential advantages and economic feasibility of adopting hybrid renewable energy solutions in regions grappling with energy access and reliability challenges, with implications for sustainable electrification efforts in similar communities worldwide.

Keywords: Vimtim-Nigeria, Homer, renewable energy, PV-diesel hybrid system

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Authors: Gaurav Kumar Sinha

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In an era marked by increasing concerns about energy sustainability, this research endeavors to address the pressing challenge of energy consumption in buildings and industries. This study delves into the transformative potential of AWS services in optimizing energy efficiency. The research is founded on the recognition that effective management of energy consumption is imperative for both environmental conservation and economic viability. Buildings and industries account for a substantial portion of global energy use, making it crucial to develop advanced techniques for analysis and reduction. This study sets out to explore the integration of AWS services with big data analytics to provide innovative solutions for energy consumption analysis. Leveraging AWS's cloud computing capabilities, scalable infrastructure, and data analytics tools, the research aims to develop efficient methods for collecting, processing, and analyzing energy data from diverse sources. The core focus is on creating predictive models and real-time monitoring systems that enable proactive energy management. By harnessing AWS's machine learning and data analytics capabilities, the research seeks to identify patterns, anomalies, and optimization opportunities within energy consumption data. Furthermore, this study aims to propose actionable recommendations for reducing energy consumption in buildings and industries. By combining AWS services with metrics-driven insights, the research strives to facilitate the implementation of energy-efficient practices, ultimately leading to reduced carbon emissions and cost savings. The integration of AWS services not only enhances the analytical capabilities but also offers scalable solutions that can be customized for different building and industrial contexts. The research also recognizes the potential for AWS-powered solutions to promote sustainable practices and support environmental stewardship.

Keywords: energy consumption analysis, big data analytics, AWS services, energy efficiency

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Authors: Mina Malak Zakaria Henin

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The finite detail evaluation of magnetic fields in electromagnetic devices shows that the machine cores revel in extraordinary flux patterns consisting of alternating and rotating fields. The rotating fields are generated in different configurations variety, among circular and elliptical, with distinctive ratios between the fundamental and minor axes of the flux locus. Experimental measurements on electrical metal uncovered one-of-a-kind flux patterns that divulge distinctive magnetic losses in the samples below the test. Therefore, electric machines require unique interest throughout the core loss calculation technique to bear in mind the flux styles. In this look, a circular rotational unmarried sheet tester is employed to measure the middle losses in the electric-powered metallic pattern of M36G29. The sample becomes exposed to alternating fields, circular areas, and elliptical fields with axis ratios of zero.2, zero. Four, 0.6 and 0.8. The measured statistics changed into applied on 6-4 switched reluctance motors at 3 distinctive frequencies of interest to the industry 60 Hz, 400 Hz, and 1 kHz. The effects reveal an excessive margin of error, which can arise at some point in the loss calculations if the flux pattern difficulty is overlooked. The mistake in exceptional components of the gadget associated with considering the flux styles may be around 50%, 10%, and a couple of at 60Hz, 400Hz, and 1 kHz, respectively. The future paintings will focus on the optimization of gadget geometrical shape, which has a primary effect on the flux sample on the way to decrease the magnetic losses in system cores.

Keywords: converters, electric machines, MEA (more electric aircraft), PES (power electronics systems) synchronous machine, vector control Multi-machine/ Multi-inverter, matrix inverter, Railway tractionalternating core losses, finite element analysis, rotational core losses

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Authors: Sarah Abdourraziq, Rachid Elbachtiri

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The use of solar energy as a source for pumping water is one of the promising areas in the photovoltaic (PV) application. The energy of photovoltaic pumping systems (PVPS) can be widely improved by employing an MPPT algorithm. This will lead consequently to maximize the electrical motor speed of the system. This paper presents a modified incremental conductance (IncCond) MPPT algorithm with direct control method applied to a standalone PV pumping system. The influence of the algorithm parameters on system behavior is investigated and compared with the traditional (INC) method. The studied system consists of a PV panel, a DC-DC boost converter, and a PMDC motor-pump. The simulation of the system by MATLAB-SIMULINK is carried out. Simulation results found are satisfactory.

Keywords: photovoltaic pumping system (PVPS), incremental conductance (INC), MPPT algorithm, boost converter

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Authors: Emily Gould, Walter Wehremeyer, David Greaves, Rodney Turtle

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This paper considers current thinking on the pathway for electric vehicles, identifying the development blocks of alternative innovation within the market and analyse technological lock-in. The relationship between transition pathways and technological lock-in is largely under-researched particularly in the field of e-mobility. This paper is based on a study with three commercial-urban fleets that examines strategic decisions in new technology adaption alongside vehicle procurement and driver perspective. The paper will analyse the fleet’s decision matrix upon electric vehicles and seek to understand the influence of company culture, strategy and technology applicability, within the context of transition pathways.

Keywords: electric vehicles, fleets, path dependencies, transition pathways

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Authors: Babak Bahri, Fatemeh Yassaee Meybodi, Changiz Eslahchi

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In the pursuit of effective cancer therapies, the exploration of combinatorial drug regimens is crucial to leverage synergistic interactions between drugs, thereby improving treatment efficacy and overcoming drug resistance. However, identifying synergistic drug pairs poses challenges due to the vast combinatorial space and limitations of experimental approaches. This study introduces ClusterSyn, a machine learning (ML)-powered framework for classifying anti-cancer drug synergy scores. ClusterSyn employs a two-step approach involving drug clustering and synergy score prediction using a fully connected deep neural network. For each cell line in the training dataset, a drug graph is constructed, with nodes representing drugs and edge weights denoting synergy scores between drug pairs. Drugs are clustered using the Markov clustering (MCL) algorithm, and vectors representing the similarity of drug pairs to each cluster are input into the deep neural network for synergy score prediction (synergy or antagonism). Clustering results demonstrate effective grouping of drugs based on synergy scores, aligning similar synergy profiles. Subsequently, neural network predictions and synergy scores of the two drugs on others within their clusters are used to predict the synergy score of the considered drug pair. This approach facilitates comparative analysis with clustering and regression-based methods, revealing the superior performance of ClusterSyn over state-of-the-art methods like DeepSynergy and DeepDDS on diverse datasets such as Oniel and Almanac. The results highlight the remarkable potential of ClusterSyn as a versatile tool for predicting anti-cancer drug synergy scores.

Keywords: drug synergy, clustering, prediction, machine learning., deep learning

Procedia PDF Downloads 79

Authors: Lemonakis Panagiotis, Eliou Nikos, Karakasidis Theodoros, Botzoris George

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It is well known that trajectory along with speed are two of the most important contributing factors in road accidents. Trajectory is meant as the "line“, usually different from the center-line that a driver traverses through horizontal curves which depends on the characteristics of the road environment (especially the curvature), the vehicle and the driver himself. Drivers and especially riders, tend to broaden their paths in order to succeed greater path radiuses and hence, reduce the applied centrifugal force enhancing safety. The objective of the present research is to investigate riders’ path on horizontal curves. Within the context of the research, field measurements were conducted on a rural two lane highway, with the participation of eight riders and the use of an instrumented motorcycle. The research has shown that the trajectory of the riders is correlated to the radius and the length of the horizontal curve as well.

Keywords: trajectory, path, riders, horizontal curves

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Authors: Ram Kishor

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The Lyapunov characteristic exponent (LCE) is an important tool to describe behavior of a dynamical system, which measures the average rate of divergence (or convergence) of a trajectory emanating in the vicinity of initial point. To analyze the behavior of nearby trajectory emanating in the neighborhood of an equilibrium point in the restricted three-body problem under the influence of perturbations in the form of radiation pressure and oblateness, we compute LCEs of first order with the help of slandered method which is based on variational equation of the system. It is observed that trajectories are chaotic in nature due positive LCEs. Also, we analyze the effect of radiation pressure and oblateness on the LCEs. Results are applicable to study the behavior of more generalized RTBP in the presence of perturbations such as PR drag, solar wind drag etc.

Keywords: Lyapunov characteristic exponent, RTBP, radiation pressure, oblateness

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Authors: Nadjib Drouiche, Abdenour Lami, Salaheddine Aoudj, Tarik Ouslimane

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Although solar cells manufacturing is a conservative industry, economics drivers continue to encourage innovation, feedstock savings and cost reduction. Kerf slurry waste is a complex product containing both valuable substances as well as contaminants. The valuable substances are: i) high purity silicon, ii) polyethylene glycol, and iii) silicon carbide. The contaminants mainly include metal fragments and organics. Therefore, recycling of the kerf slurry waste is an important subject not only from the treatment of waste but also from the recovery of valuable products. The present paper relates to processes for the recovery of valuable products from the kerf slurry waste in which they are contained, such products comprising nanoparticles, polyethylene glycol, high purity silicon, and silicon carbide.

Keywords: photovoltaic cell, Kerf slurry waste, recycling, silicon carbide

Procedia PDF Downloads 331

Authors: Olukunle C. Olawole, Dilip Kumar De

Abstract:

We have modified Richardson-Dushman equation considering thermal expansion of lattice and change of chemical potential with temperature in material. The corresponding modified Richardson-Dushman (MRDE) equation fits quite well the experimental data of thermoelectronic current density (J) vs T from carbon nanotubes. It provides a unique technique for accurate determination of W0 Fermi energy, EF0 at 0 K and linear thermal expansion coefficient of carbon nano-tube in good agreement with experiment. From the value of EF0 we obtain the charge carrier density in excellent agreement with experiment. We describe application of the equations for the evaluation of performance of concentrated solar thermionic energy converter (STEC) with emitter made of carbon nanotube for future applications.

Keywords: carbon nanotube, modified Richardson-Dushman equation, fermi energy at 0 K, charge carrier density

Procedia PDF Downloads 378

Authors: Anna Dziubinska

Abstract:

The applications of magnesium alloys in transport include all kinds of vehicle wheels for cars, motorcycles, bicycles, trolleys, etc. Modern technologies of manufacturing products from these materials have been noticeably improved recently, creating new possibilities for their application. Continuously developed technologies for forming Mg alloys must not be overlooked, which make it possible to manufacture products with better properties compared to those obtained by casting only. The article reviews the specialized literature on magnesium wheel forming and presents a concept of technology for forging magnesium wheels for light vehicles from cast preforms. The research leading to these results has received funding from the Norway Grants 2014-2021 via the National Centre for Research and Development.

Keywords: forming, forging, magnesium alloy, wheels, vehicles

Procedia PDF Downloads 141

Authors: Alex Ellery

Abstract:

Geoengineering approaches to climate change mitigation are unpopular and regarded with suspicion. Of these, space-based approaches are regarded as unworkable and enormously costly. Here, a space-based approach is presented that is modest in cost, fully controllable and reversible, and acts as a natural spur to the development of solar power satellites over the longer term as a clean source of energy. The low-cost approach exploits self-replication technology which it is proposed may be enabled by 3D printing technology. Self-replication of 3D printing platforms will enable mass production of simple spacecraft units. Key elements being developed are 3D-printable electric motors and 3D-printable vacuum tube-based electronics. The power of such technologies will open up enormous possibilities at low cost including space-based geoengineering.

Keywords: 3D printing, in-situ resource utilization, self-replication technology, space-based geoengineering

Procedia PDF Downloads 423

Authors: M. Hemnath, S. Kannan, R. Kiran, K. Thanigaivelu

Abstract:

This paper is based on exploring the possible opportunities and applications using Power Line Communication (PLC) for security and surveillance operations. Various research works are done for introducing PLC into onboard vehicle communication and networking (CAN, LIN etc.) and various international standards have been developed. Wireless power transfer (WPT) is also an emerging technology which is studied and tested for recharging purposes. In this work we present a system which embeds the detection and the response into one which eliminates the need for dedicated network for data transmission. Also we check the feasibility for integrating wireless power transfer system into this proposed security system for transmission of power to detection unit wirelessly from the response unit.

Keywords: power line communication, wireless power transfer, surveillance

Procedia PDF Downloads 535

Authors: Alisa Kazarina, Guntis Gerhards, Elina Petersone-Gordina, Ilva Pole, Viktorija Igumnova, Janis Kimsis, Valentina Capligina, Renate Ranka

Abstract:

Human body is inhabited by a vast number of microorganisms, collectively known as the human microbiome, and there is a tremendous interest in evolutionary changes in human microbial ecology, diversity and function. The field of paleomicrobiology, study of ancient human microbiome, is powered by modern techniques of Next Generation Sequencing (NGS), which allows extracting microbial genomic data directly from archaeological sample of interest. One of the major techniques is 16S rRNA gene sequencing, by which certain 16S rRNA gene hypervariable regions are being amplified and sequenced. However, some limitations of this method exist including the taxonomic precision and efficacy of different regions used. The aim of this study was to evaluate the phylogenetic sensitivity of different 16S rRNA gene hypervariable regions for microbiome studies in the archaeological samples. Towards this aim, archaeological bone samples and corresponding soil samples from each burial environment were collected in Medieval cemeteries in Latvia. The Ion 16S™ Metagenomics Kit targeting different 16S rRNA gene hypervariable regions was used for library construction (Ion Torrent technologies). Sequenced data were analysed by using appropriate bioinformatic techniques; alignment and taxonomic representation was done using Mothur program. Sequences of most abundant genus were further aligned to E. coli 16S rRNA gene reference sequence using MEGA7 in order to identify the hypervariable region of the segment of interest. Our results showed that different hypervariable regions had different discriminatory power depending on the groups of microbes, as well as the nature of samples. On the basis of our results, we suggest that wider range of primers used can provide more accurate recapitulation of microbial communities in archaeological samples. Acknowledgements. This work was supported by the ERAF grant Nr. 1.1.1.1/16/A/101.

Keywords: 16S rRNA gene, ancient human microbiome, archaeology, bioinformatics, genomics, microbiome, molecular biology, next-generation sequencing

Procedia PDF Downloads 190

Authors: Vivek Anand, Rainer Naegele

Abstract:

Industry 4.0 envisages 'smart' manufacturing and services, taking the automation of the 3rd Industrial Revolution to the autonomy of the 4th Industrial Revolution. Powered by innovations in technology and business models, this disruptive transformation is revitalising industry by integrating silos across and beyond value chains. Motivated by the challenges faced by SMEs and Startups in understanding and adopting Industry 4.0, this paper aims to analyse the concept of Growth Poles and evaluate the possibility of its application to Innovation Clusters that strive to propel Industry 4.0 adoption and capacity building. The proposed paper applies qualitative research methodologies including focus groups and survey questionnaires to identify the various factors that affect formation and development of Innovation Clusters. Employing content analysis, the interaction between SMEs and other ecosystem players in such clusters is studied. A strong collaborative culture is a key driver of digital transformation and technology adoption across sectors, value chains and supply chains; and will position these cluster-based growth poles at the forefront of industrial renaissance. Motivated by this argument, and based on the results of the qualitative research, a roadmap will be proposed to position Innovation Clusters as Growth Poles and effective ecosystems to support Industry 4.0 adoption in a region in the medium to long term. This paper will contribute to the current understanding of the role of Innovation Clusters in capacity building. Relevant management and policy implications stem from the analysis. Furthermore, the findings will be helpful for academicians and policymakers alike, who can leverage an ‘innovation cluster policy’ to enable Industry 4.0 Growth Poles in their regions.

Keywords: digital transformation, fourth industrial revolution, growth poles, industry 4.0, innovation clusters, innovation policy, SMEs and startups

Procedia PDF Downloads 230