Search results for: Hybrid Electric Vehicle (HEV)

Authors: Choi Younshick, Lee Wonseok, Lee Jaemeun, Park Sun-Hyun, Kim Sunwoung, Park Sua, Kim Eun Ho, Kim Jong-Ki

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Iron accumulation in the brain accelerates Alzheimer’s disease progression. To cure iron toxicity, we assessed the therapeutic effects of noncontact transcranial electric field stimulation to the brain on toxic iron deposits in either the Aβ-fibril structure or the Aβ plaque in a mouse model of Alzheimer’s disease (AD). A capacitive electrode-based alternating electric field (AEF) was applied to a suspension of magnetite (Fe₃O₄) to measure the field-sensitized electro-Fenton effect and resultant reactive oxygen species (ROS) generation. The increase in ROS generation compared to the untreated control was both exposure-time and AEF-frequency dependent. The frequency-specific exposure of AEF to 0.7–1.4 V/cm on a magnetite-bound Aβ-fibril or a transgenic Alzheimer’s disease (AD) mouse model revealed the removal of intraplaque ferrous magnetite iron deposit and Aβ-plaque burden together at the same time compared to the untreated control. The results of the behavioral tests show an improvement in impaired cognitive function following AEF treatment on the AD mouse model. Western blot assay found some disease-modifying biological responses, including down-regulating ferroptosis, neuroinflammation and reactive astrocytes that eventually made cognitive improvement feasible. Tissue clearing and 3D-imaging analysis revealed no induced damage to the neuronal structures of normal brain tissue following AEF treatment. In conclusion, our results suggest that the effective degradation of magnetite-bound amyloid fibrils or plaques in the AD brain by the electro-Fenton effect from electric field-sensitized magnetite offers a potential electroceutical treatment option for AD.

Keywords: electroceutical, intraplaque magnetite, alzheimer’s disease, transcranial electric field, electro-fenton effect

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Authors: Ganiyu Samson Okunlola, Ladanu Abiodun Ajala, Olaide Oluwaseun Adegbayo

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Since the usefulness of articulated vehicles is becoming more apparent and the diesel consumption of these vehicles constitutes a major portion of operating costs, development of mathematical model for their diesel consumption is of a great importance. Therefore, the present work developed a quantitative relationship between diesel consumption and vehicle age, annual use and cost of maintenance of the different makes of articulated vehicles. The vehicles selected for the study were FIAT 682 T3, IVECO 19036 and M.A.N. Diesel 19.240. The operating parameters for 90 vehicles of different age groups were recorded. Multiple regression models for diesel consumption of articulated vehicles of different makes were developed. From the analysis of results, it can be concluded that as the age of the vehicles increases, the diesel consumption increases. Also, as the diesel consumption increases, the cost of maintenance increases and there is a subsequent decrease in annual use. Moreover, FIAT 682 T3 and IVECO 19036 should be replaced at 7 years of age while M.A.N diesel should be replaced at 8 years of age. These are the ages where the diesel consumption becomes abnormal and uneconomical and they are points of optimal overhaul.

Keywords: vehicle, overhaul, age, uneconomical, diesel, consumption

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Authors: H. S. S Abou El-Mal, A. S. Sherbini, H. E. M. Sallam

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Mode II fracture toughness (KIIc) of fiber reinforced concrete has been widely investigated under various patterns of testing geometries. The effect of fiber type, concrete matrix properties, and testing mechanisms were extensively studied. The area of hybrid fiber addition shows a lake of reported research data. In this paper an experimental investigation of hybrid fiber embedded in high strength concrete matrix is reported. Three different types of fibers; namely steel (S), glass (G), and polypropylene (PP) fibers were mixed together in four hybridization patterns, (S/G), (S/PP), (G/PP), (S/G/PP) with constant cumulative volume fraction (Vf) of 1.5%. The concrete matrix properties were kept the same for all hybrid fiber reinforced concrete patterns. In an attempt to estimate a fairly accepted value of fracture toughness KIIc, four testing geometries and loading types are employed in this investigation. Four point shear, Brazilian notched disc, double notched cube, and double edge notched specimens are investigated in a trial to avoid the limitations and sensitivity of each test regarding geometry, size effect, constraint condition, and the crack length to specimen width ratio a/w. The addition of all hybridization patterns of fiber reduced the compressive strength and increased mode II fracture toughness in pure mode II tests. Mode II fracture toughness of concrete KIIc decreased with the increment of a/w ratio for all concretes and test geometries. Mode II fracture toughness KIIc is found to be sensitive to the hybridization patterns of fiber. The (S/PP) hybridization pattern showed higher values than all other patterns, while the (S/G/PP) showed insignificant enhancement on mode II fracture toughness (KIIc). Four point shear (4PS) test set up reflects the most reliable values of mode II fracture toughness KIIc of concrete. Mode II fracture toughness KIIc of concrete couldn’t be assumed as a real material property.

Keywords: fiber reinforced concrete, Hybrid fiber, Mode II fracture toughness, testing geometry

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Authors: Kaushik Vaideeswaran, Jean Gobet, Patrick Margraf, Olha Sereda

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Nitrocarburisation is a surface hardening technique often applied to improve the wear resistance of steel surfaces. It is considered to be a promising solution in comparison with other processes such as flame spraying, owing to the formation of a diffusion layer which provides mechanical integrity, as well as its cost-effectiveness. To improve other tribological properties of the surface such as the coefficient of friction (COF), dry lubricants are utilized. Currently, the lifetime of steel components in many applications using either of these techniques individually are faced with the limitations of the two: high COF for nitrocarburized surfaces and low wear resistance of dry lubricant coatings. To this end, the current study involves the creation of a hybrid surface using the impregnation of a dry lubricant on to a nitrocarburized surface. The mechanical strength and hardness of Gerster SA’s nitrocarburized surfaces accompanied by the impregnation of the porous outermost layer with a solid lubricant will create a hybrid surface possessing both outstanding wear resistance and a low friction coefficient and with high adherence to the substrate. Gerster SA has the state-of-the-art technology for the surface hardening of various steels. Through their expertise in the field, the nitrocarburizing process parameters (atmosphere, temperature, dwelling time) were optimized to obtain samples that have a distinct porous structure (in terms of size, shape, and density) as observed by metallographic and microscopic analyses. The porosity thus obtained is suitable for the impregnation of a dry lubricant. A commercially available dry lubricant with a thermoplastic matrix was employed for the impregnation process, which was optimized to obtain a void-free interface with the surface of the nitrocarburized layer (henceforth called hybrid surface). In parallel, metallic samples without nitrocarburisation were also impregnated with the same dry lubricant as a reference (henceforth called reference surface). The reference and the nitrocarburized surfaces, with and without the dry lubricant were tested for their tribological behavior by sliding against a quenched steel ball using a nanotribometer. Without any lubricant, the nitrocarburized surface showed a wear rate 5x lower than the reference metal. In the presence of a thin film of dry lubricant ( < 2 micrometers) and under the application of high loads (500 mN or ~800 MPa), while the COF for the reference surface increased from ~0.1 to > 0.3 within 120 m, the hybrid surface retained a COF < 0.2 for over 400m of sliding. In addition, while the steel ball sliding against the reference surface showed heavy wear, the corresponding ball sliding against the hybrid surface showed very limited wear. Observations of the sliding tracks in the hybrid surface using Electron Microscopy show the presence of the nitrocarburized nodules as well as the lubricant, whereas no traces of the lubricant were found in the sliding track on the reference surface. In this manner, the clear advantage of combining nitrocarburisation with the impregnation of a dry lubricant towards forming a hybrid surface has been demonstrated.

Keywords: dry lubrication, hybrid surfaces, improved wear resistance, nitrocarburisation, steels

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Authors: Rade M. Ciric

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The paper shows the development and implementation of the syllabus of the subject 'Distribution and Industrial Networks', attended by the vocational specialist Year 4 students of the Electric Power Engineering study programme at the Higher Education Technical School of Vocational Studies in Novi Sad. The aim of the subject is to equip students with the knowledge necessary for planning, exploitation and management of distributive and industrial electric power networks in an open electricity market environment. The results of the evaluation of educational outcomes on the subject are presented and discussed.

Keywords: engineering education, power distribution network, syllabus implementation, outcome evaluation

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Authors: Wanchalerm Patanacharoenwong, Panaya Sudta, Prachya Bumrungkun

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The paper focuses on the development of a system that combines Internet of Things (IoT) technologies and deep learning algorithms for anomaly detection in residential Electric Vehicle (EV) charging in smart cities. With the increasing number of EVs, ensuring efficient and reliable charging systems has become crucial. The aim of this research is to develop an integrated IoT and deep learning system for detecting anomalies in residential EV charging and enhancing EV load profiling and event detection in smart cities. This approach utilizes IoT devices equipped with infrared cameras to collect thermal images and household EV charging profiles from the database of Thailand utility, subsequently transmitting this data to a cloud database for comprehensive analysis. The methodology includes the use of advanced deep learning techniques such as Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) algorithms. IoT devices equipped with infrared cameras are used to collect thermal images and EV charging profiles. The data is transmitted to a cloud database for comprehensive analysis. The researchers also utilize feature-based Gaussian mixture models for EV load profiling and event detection. Moreover, the research findings demonstrate the effectiveness of the developed system in detecting anomalies and critical profiles in EV charging behavior. The system provides timely alarms to users regarding potential issues and categorizes the severity of detected problems based on a health index for each charging device. The system also outperforms existing models in event detection accuracy. This research contributes to the field by showcasing the potential of integrating IoT and deep learning techniques in managing residential EV charging in smart cities. The system ensures operational safety and efficiency while also promoting sustainable energy management. The data is collected using IoT devices equipped with infrared cameras and is stored in a cloud database for analysis. The collected data is then analyzed using RNN, LSTM, and feature-based Gaussian mixture models. The approach includes both EV load profiling and event detection, utilizing a feature-based Gaussian mixture model. This comprehensive method aids in identifying unique power consumption patterns among EV owners and outperforms existing models in event detection accuracy. In summary, the research concludes that integrating IoT and deep learning techniques can effectively detect anomalies in residential EV charging and enhance EV load profiling and event detection accuracy. The developed system ensures operational safety and efficiency, contributing to sustainable energy management in smart cities.

Keywords: cloud computing framework, recurrent neural networks, long short-term memory, Iot, EV charging, smart grids

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Authors: Mansilla, Juan Camilo

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According to many studies, public space in the cities of Global South is constantly morcellated and captured by a multiplicity of actors in a permanent struggle for power. This imposed public space restricts the access to services and political actions to many inhabitants. The author has conducted several focus group sessions using video in a reflective mode with low-income communities in Medellín, Colombia in order to study how people in this city are shift from a physical public space to a hybrid public space shaped by internet. Beyond the fragmented city and the violent urban context manifested by participants, these activities have highlighted how the access to the city is currently going through a dialectic movement between the physical and the digital space. The purpose of this article is to make explicit the link between this hybrid public space and the boundaries of exclusion in the city. Urban marginality is closely related with the idea of access and space. Low-income communities in Medellín assume the digital realm like a “not controlled space” of resistance, where alternative ways of expression like hip hop movement, graffiti, dance, video and virtual communities produce effective changes in the physical realm.

Keywords: access to the city, hybrid public space, low-income communities, Medellín, urban marginality

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Authors: Solomon Neway Jida, Jean-Francois Hetet, Pascal Chesse

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Vehicular emission is the key source of air pollution in the urban environment. This includes both fine particles (PM_2.5) and coarse particulate matters (PM₁₀). However, particulate matter emissions from road traffic comprise emissions from exhaust tailpipe and emissions due to wear and tear of the vehicle part such as brake, tire and clutch and re-suspension of dust (non-exhaust emission). This study estimates the share of the two sources of pollutant particle emissions from on-roadside vehicles in the Addis Ababa municipality, Ethiopia. To calculate its share, two methods were applied; the exhaust-tailpipe emissions were calculated using the Europeans emission inventory Tier II method and Tier I for the non-exhaust emissions (like vehicle tire wear, brake, and road surface wear). The results show that of the total traffic-related particulate emissions in the city, 63% emitted from vehicle exhaust and the remaining 37% from non-exhaust sources. The annual roads transport exhaust emission shares around 2394 tons of particles from all vehicle categories. However, from the total yearly non-exhaust particulate matter emissions’ contribution, tire and brake wear shared around 65% and 35% emanated by road-surface wear. Furthermore, vehicle tire and brake wear were responsible for annual 584.8 tons of coarse particles (PM₁₀) and 314.4 tons of fine particle matter (PM_2.5) emissions in the city whereas surface wear emissions were responsible for around 313.7 tons of PM₁₀ and 169.9 tons of PM_2.5 pollutant emissions in the city. This suggests that non-exhaust sources might be as significant as exhaust sources and have a considerable contribution to the impact on air quality.

Keywords: Addis Ababa, automotive emission, emission estimation, particulate matters

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Authors: V. M. Levshakov, N. A. Steshenkova, N. A. Nosyrev

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Application of hulls processing technologies, based on high-concentrated energy sources (laser and plasma technologies), allow improve shipbuilding production. It is typical for high-speed vessels construction using steel and aluminum alloys with high precision hulls required. Report describes high-performance technologies for plasma welding (using direct current of reversed polarity), laser, and hybrid laser-arc welding of hulls structures developed by JSC “SSTC”.

Keywords: flat sections, hybrid laser-arc welding, plasma welding, plasmatron

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Authors: N. Nandan A. M. Nagaraj, L. Sanjeev Kumar

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In the rapidly growing population, the requirement of electrical power is increasing day by day. In order to meet the needs, we need to generate the power using alternate method. In this paper, a presentable approach is developed by analysis and can be implemented by utilizing heat energy, which is generated in numerous ways in some of the rural areas in India. The thermoelectric generator unit will be developed by combing with control circuits and converts, which is used to light the LED lamps. The temperature difference which is available in the kitchens, especially the exhaust pipes/chimneys of wooden fire stoves, where more heat is dissipated into the atmosphere, can be utilized for electrical power generation. Hence, the temperature rise of surroundings atmosphere can be reduced.

Keywords: thermo electric generator, LED, converts, temperature

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Authors: John Morales, Eduardo Orduña

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Currently the Principal Component Analysis (PCA) theory has been used to develop algorithms regarding to Electric Power Systems (EPS). In this context, this paper presents a practical tutorial of this technique detailed their concept, on-line and off-line mathematical foundations, which are necessary and desirables in EPS algorithms. Thus, features of their eigenvectors which are very useful to real-time process are explained, showing how it is possible to select these parameters through a direct optimization. On the other hand, in this work in order to show the application of PCA to off-line and on-line signals, an example step to step using Matlab commands is presented. Finally, a list of different approaches using PCA is presented, and some works which could be analyzed using this tutorial are presented.

Keywords: practical guide; on-line; off-line, algorithms, faults

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Authors: Atefeh Pourshafie, Homayoun Bakhtiari

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The main task of power distribution companies is to supply the power required by customers in an acceptable level of quality and reliability. Some key performance indicators for electric power distribution companies are those evaluating the continuity of supply within the network. More than other problems, power outages (due to lightning, flood, fire, earthquake, etc.) challenge economy and business. In addition, end users expect a reliable power supply. Reliability indices are evaluated on an annual basis by the specialized holding company of Tavanir (Power Produce, Transmission& distribution company of Iran) . Evaluation of reliability indices is essential for distribution companies, and with regard to the privatization of distribution companies, it will be of particular importance to evaluate these indices and to plan for their improvement in a not too distant future. According to IEEE-1366 standard, there are too many indices; however, the most common reliability indices include SAIFI, SAIDI and CAIDI. These indices describe the period and frequency of blackouts in the reporting period (annual or any desired timeframe). This paper calculates reliability indices for three sample feeders in Lorestan Electric Power Distribution Company and defines the threshold values in a ten-month period. At the end, strategies are introduced to reach the threshold values in order to increase customers' satisfaction.

Keywords: power, distribution network, reliability, outage

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Authors: Donggun Lee, Q-Han Park

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Due to its coarse grid, the Pseudo-Spectral Time Domain (PSTD) method has advantages against the Finite Difference Time Domain (FDTD) method in terms of memory requirement and operation time. However, since the efficiency of parallelization is much lower than that of FDTD, PSTD is not a useful method for a large-scale electromagnetic simulation in a parallel platform. In this paper, we propose the parallelization technique of the hybrid PSTD-FDTD (HPF) method which simultaneously possesses the efficient parallelizability of FDTD and the quick speed and low memory requirement of PSTD. Parallelization cost of the HPF method is exactly the same as the parallel FDTD, but still, it occupies much less memory space and has faster operation speed than the parallel FDTD. Experiments in distributed memory systems have shown that the parallel HPF method saves up to 96% of the operation time and reduces 84% of the memory requirement. Also, by combining the OpenMP library to the MPI library, we further reduced the operation time of the parallel HPF method by 50%.

Keywords: FDTD, hybrid, MPI, OpenMP, PSTD, parallelization

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Authors: Gia Sirbiladze

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Route planning problems are among the activities that have the highest impact on logistical planning, transportation, and distribution because of their effects on efficiency in resource management, service levels, and client satisfaction. In extreme conditions, the difficulty of vehicle movement between different customers causes the imprecision of time of movement and the uncertainty of the feasibility of movement. A feasibility level of vehicle movement on the closed route of the disaster-streaking zone is defined for the construction of an objective function. Experts’ evaluations of the uncertain parameters in q-rung ortho-pair fuzzy numbers (q-ROFNs) are presented. A fuzzy bi-objective combinatorial optimization problem of fuzzy vehicle routine problem (FVRP) is constructed based on the technique of possibility theory. The FVRP is reduced to the bi-criteria partitioning problem for the so-called “promising” routes which were selected from the all-admissible closed routes. The convenient selection of the “promising” routes allows us to solve the reduced problem in real-time computing. For the numerical solution of the bi-criteria partitioning problem, the -constraint approach is used. The main results' support software is designed. The constructed model is illustrated with a numerical example.

Keywords: q-rung ortho-pair fuzzy sets, facility location selection problem, multi-objective combinatorial optimization problem, partitioning problem

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Authors: C. P. Chukwuka, E. V. Chukwuka, F. Ukwadi

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This paper focuses on the advancement and societal impact of artificial intelligence (AI) systems. It explores the need for a theoretical framework in corporate governance, specifically in the context of 'hybrid' companies that have a mix of private and government ownership. The paper emphasizes the potential of AI to address challenges faced by these companies and highlights the importance of the less-explored state model in corporate governance. The aim of this research is to enhance AI systems for global impact and positive societal outcomes. It aims to explore the role of AI in refining corporate governance in hybrid companies and uncover nuanced insights into complex ownership structures. The methodology involves leveraging the capabilities of AI to address the challenges faced by hybrid companies in corporate governance. The researchers will analyze existing theoretical frameworks in corporate governance and integrate AI systems to improve problem-solving and understanding of intricate systems. The paper suggests that improved AI systems have the potential to shape a more informed and responsible corporate landscape. AI can uncover nuanced insights and navigate complex ownership structures in hybrid companies, leading to greater efficacy and positive societal outcomes. The theoretical importance of this research lies in the exploration of the role of AI in corporate governance, particularly in the context of hybrid companies. By integrating AI systems, the paper highlights the potential for improved problem-solving and understanding of intricate systems, contributing to a more informed and responsible corporate landscape. The data for this research will be collected from existing literature on corporate governance, specifically focusing on hybrid companies. Additionally, data on AI capabilities and their application in corporate governance will be collected. The collected data will be analyzed through a systematic review of existing theoretical frameworks in corporate governance. The researchers will also analyze the capabilities of AI systems and their potential application in addressing the challenges faced by hybrid companies. The findings will be synthesized and compared to identify patterns and potential improvements. The research concludes that AI systems have the potential to enhance corporate governance in hybrid companies, leading to greater efficacy and positive societal outcomes. By leveraging AI capabilities, nuanced insights can be uncovered, and complex ownership structures can be navigated, shaping a more informed and responsible corporate landscape. The findings highlight the importance of integrating AI in refining problem-solving and understanding intricate systems for global impact.

Keywords: advancement, artificial intelligence, challenges, societal impact

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Authors: H. Mekki, A. Djerioui, S. Zeghlache, L. Chrifi-Alaoui

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Induction motor (IM)Induction motor (IM) are nowadays widely used in industrial applications specially in electric vehicles (EVs) and traction locomotives, due to their high efficiency high speed and lifetime. However, since EV motors are easily influenced by un-certainties parameter variations and external load disturbance, both robust control techniques have received considerable attention during the past few decades. This paper present a robust controller design based sliding mode control (SMC) and high gain flux observer (HGO) for induction motor (IM) based Electric Vehicles (EV) drives. This control technique is obtained by the combination between the field oriented and the sliding mode control strategy and present remarkable dynamic performances just as a good robustness with respect to EV drives load torque. A high gain flux observer is also presented and associated in order to design sensorless control by estimating the rotor flux only using measurements of the stator voltages and currents. Simulations results are provided to evaluate the consistency and to show the effectiveness of the proposed SMC strategy also the performance of the HGO for Electric Vehicles system are nowadays widely used in industrial applications specially in electric vehicles (EVs) and traction locomotives, due to their high efficiency high speed and lifetime. However, since EV motors are easily influenced by un-certainties parameter variations and external load disturbance, both robust control techniques have received considerable attention during the past few decades. This paper present a robust controller design based sliding mode control (SMC) and high gain flux observer (HGO) for induction motor (IM) based Electric Vehicles (EV) drives. This control technique is obtained by the combination between the field oriented and the sliding mode control strategy and present remarkable dynamic performances just as a good robustness with respect to EV drives load torque. A high gain flux observer is also presented and associated in order to design sensorless control by estimating the rotor flux only using measurements of the stator voltages and currents. Simulations results are provided to evaluate the consistency and to show the effectiveness of the proposed SMC strategy also the performance of the HGO for Electric Vehicles system.

Keywords: electric vehicles, sliding mode control, induction motor drive, high gain observer

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Authors: Suresh Salla

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In this paper, author explores for most sustainable last mile transport mode addressing present problems of traffic congestion, jams, pollution and travel stress. Development of energy-efficient sustainable integrated transport system(s) is/are must to make our cities more livable. Emphasis on autonomous, connected, electric, sharing system for effective utilization of systems (vehicles and public infrastructure) is on the rise. Many surface mobility innovations like PBS, Ride hailing, ride sharing, etc. are, although workable but if we analyze holistically, add to the already congested roads, difficult to ride in hostile weather, causes pollution and poses commuter stress. Sustainability of transportation is evaluated with respect to public adoption, average speed, energy consumption, and pollution. Why public prefer certain mode over others? How commute time plays a role in mode selection or shift? What are the factors play-ing role in energy consumption and pollution? Based on the study, it is clear that public prefer a transport mode which is exhaustive (i.e., less need for interchange – network is widespread) and intensive (i.e., less waiting time - vehicles are available at frequent intervals) and convenient with latest technologies. Average speed is dependent on stops, number of intersections, signals, clear route availability, etc. It is clear from Physics that higher the kerb weight of a vehicle; higher is the operational energy consumption. Higher kerb weight also demands heavier infrastructure. Pollution is dependent on source of energy, efficiency of vehicle, average speed. Mode can be made exhaustive when the unit infrastructure cost is less and can be offered intensively when the vehicle cost is less. Reliable and seamless integrated mobility till last ¼ mile (Five Minute Walk-FMW) is a must to encourage sustainable public transportation. Study shows that average speed and reliability of dedicated modes (like Metro, PRT, BRT, etc.) is high compared to road vehicles. Electric vehicles and more so battery-less or 3rd rail vehicles reduce pollution. One potential mode can be Cycleloop PRT, where commuter rides e-cycle in a dedicated path – elevated, at grade or underground. e-Bike with kerb weight per rider at 15 kg being 1/50th of car or 1/10th of other PRT systems makes it sustainable mode. Cycleloop tube will be light, sleek and scalable and can be modular erected, either on modified street lamp-posts or can be hanged/suspended between the two stations. Embarking and dis-embarking points or offline stations can be at an interval which suits FMW to mass public transit. In terms of convenience, guided e-Bike can be made self-balancing thus encouraging driverless on-demand vehicles. e-Bike equipped with smart electronics and drive controls can intelligently respond to field sensors and autonomously move reacting to Central Controller. Smart switching allows travel from origin to destination without interchange of cycles. DC Powered Batteryless e-cycle with voluntary manual pedaling makes it sustainable and provides health benefits. Tandem e-bike, smart switching and Platoon operations algorithm options provide superior through-put of the Cycleloop. Thus Cycleloop PRT will be exhaustive, intensive, convenient, reliable, speedy, sustainable, safe, pollution-free and healthy alternative mode for last mile connectivity in cities.

Keywords: cycleloop PRT, five-minute walk, lean modular infrastructure, self-balanced intelligent e-cycle

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Authors: Meimei Wen, Chang Nyung Kim

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In the current study, three-dimensional liquid metal (LM) magneto-hydrodynamic (MHD) flows in a manifold with three sub-channels under a uniform magnetic field are numerically investigated. In the manifold, the electrical current can cross channel walls, thus having influence on the flow distribution in each sub-channel. A case with various arrangements of electric conductivity for different parts of channel walls is considered, yielding different current distributions as well as flow distributions in each sub-channel. Here, the imbalance of mass flow rates in the three sub-channels is addressed. Meanwhile, predicted are detailed behaviors of the flow velocity, pressure, current and electric potential of LM MHD flows with three sub-channels. Commercial software CFX is used for the numerical simulation of LM MHD flows.

Keywords: CFX, liquid metal, manifold, MHD flow

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Authors: Judith Mwakalonge, Geophrey Mbatta, Saidi Siuhi, Gurcan Comert, Cuthbert Ruseruka

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Transportation agencies worldwide continuously monitor their roads' conditions to minimize road maintenance costs and maintain public safety and rideability quality. Existing methods for carrying out road condition surveys involve manual observations of roads using standard survey forms done by qualified road condition surveyors or engineers either on foot or by vehicle. Automated road condition survey vehicles exist; however, they are very expensive since they require special vehicles equipped with sensors for data collection together with data processing and computing devices. The manual methods are expensive, time-consuming, infrequent, and can hardly provide real-time information for road conditions. This study contributes to this arena by utilizing built-in vehicle technologies, drones, and deep learning to automate road condition surveys while using low-cost technology. A single model is trained to capture flexible pavement distresses (Potholes, Rutting, Cracking, and raveling), thereby providing a more cost-effective and efficient road condition monitoring approach that can also provide real-time road conditions. Additionally, data fusion is employed to enhance the road condition assessment with data from vehicles and drones.

Keywords: road conditions, built-in vehicle technology, deep learning, drones

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Authors: Gaohuizi Guo, Ning Zhang

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Firefly algorithm (FA) and Sine Cosine algorithm (SCA) are two very popular and advanced metaheuristic algorithms. However, these algorithms applied to multi-objective optimization problems have some shortcomings, respectively, such as premature convergence and limited exploration capability. Combining the privileges of FA and SCA while avoiding their deficiencies may improve the accuracy and efficiency of the algorithm. This paper proposes a hybridization of FA and SCA algorithms, named multi-objective firefly-sine cosine algorithm (MFA-SCA), to develop a more efficient meta-heuristic algorithm than FA and SCA.

Keywords: firefly algorithm, hybrid algorithm, multi-objective optimization, sine cosine algorithm

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Authors: Tali Capua, Karin Hermon, Miguel Glatstein, Oren Tavor, Ayelet Rimon

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Background: Electric bicycles (E-bikes) are one of a wide range of light electric vehicles that provide convenient local transportation and attractive recreational opportunities. Along with their growing use worldwide, the E-bike related injury rate increases. To the best of our knowledge, this study is the first to specifically compare E-bike with classic bicycle related injuries in children. Methods: Data of all pediatric ( < 16 years of age) bicycle related injuries presenting to an urban level I trauma center between 2014 and 2015 were collected and analyzed. The recorded data included age, gender, details of the accident, as well severity of injury, medical diagnosis, and the outcome. Abbreviated Injury Score (AIS) and Injury Severity Score (ISS) were calculated for each patient. Data of E-bike related injuries and classic bicycle were then compared. Results: A total of 124 bicycle related injuries and 97 E-bike related injuries presented to the emergency department. Once pedestrians and bicycle passengers were removed, the groups of riders consisted of 111 bikers and 85 E-bikers. The mean age of bikers was 9.9 years (range 3-16 years) and of E-bikers was 13.7 years (range 7.5-16 years). Injuries to the head and the extremities were common in both groups. Compared to bikers, E-bikers had significantly more injuries to intra-abdominal organs (p = 0.04). Twenty patients (16%) with bicycle related injuries were admitted, and 13 (15%) patients with E-bike related injuries, of the latter group four underwent surgical intervention. ISS scores were low overall, but the injuries of higher severity (ISS > 9) were among the E-bikers. Conclusions: This study provides unique information which suggests that injuries in E-bikers tend to be more severe than in classic bikers. There is a need for regulation regarding the use of E-bikes to enhance the safety of both bikers and other road and pavement users.

Keywords: bicycle, electric bicycle, injury, pediatric, trauma

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Authors: M. Veeresham

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The microstructure, texture, phase stability, and tensile properties of annealed Ta_0.5Nb_0.5Hf_0.5ZrTi_1.5 alloy have been investigated in the present research. The alloy was severely hybrid-rolled up to 93.5% thickness reduction, subsequently rolled samples subjected to an annealing treatment at 800 °C and 1000 °C temperatures for 1 h. Consequently, the rolled condition and both annealed temperatures have a body-centered cubic (BCC) structure. Furthermore, quantitative texture measurements (orientation distribution function (ODF) analysis) and microstructural examinations (analytical electron backscatter diffraction (EBSD) maps) permitted to establish a good relationship between annealing texture and microstructure and universal testing machine (UTM) utilized for obtaining the mechanical properties. Impressive room temperature tensile properties combination with the tensile strength (1380 MPa) and (24.7%) elongation is achieved for the 800 °C heat-treated condition. The evolution of the coarse microstructure featured in the case of 1000 °C annealed temperature ascribed to the influence of high thermal energy.

Keywords: refractory high entropy alloys, hybrid-rolling, recrystallization, microstructure, tensile properties

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Authors: S. A. M. Sabrina, Gouget Lammel, Anne Chantal, Chazalviel, Jean Noël, Ozanam François, Etcheberry Arnaud, Tighlit Fatma Zohra, B. Samia, Gabouze Noureddine

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The elaboration and characterization of hybrid nano materials give rise to considerable interest due to the new properties that arising. They are considered as an important category of new materials having innovative characteristics by combining the specific intrinsic properties of inorganic compounds (semiconductors) with the grafted organic species. This open the way to improved properties and spectacular applications in various and important fields, especially in the environment. In this work, nano materials based-semiconductors were elaborated by chemical route. The obtained surfaces were grafted with organic functional groups. The functionalization process was optimized in order to confer to the hybrid nano material a good stability as well as the right properties required for the subsequent applications. Different characterization techniques were used to investigate the resulting nano structures, such as SEM, UV-Visible, FTIR, Contact angle and electro chemical measurements. Finally, applications were envisaged in environmental area. The elaborated nano structures were tested for the detection and the elimination of pollutants.

Keywords: hybrid materials, porous silicon, peptide, metal detection

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Authors: A. M. Tahsini, S. A. Hosseini

Abstract:

In the present study, the surface temperature history of the adaptor part in a two-stage supersonic launch vehicle is accurately predicted. The full Navier-Stokes equations are used to estimate the aerodynamic heat flux. The one-dimensional heat conduction in solid phase is used to compute the temperature history. The instantaneous surface temperature is used to improve the applied heat flux, to improve the accuracy of the results.

Keywords: aerodynamic heating, heat conduction, numerical simulation, supersonic flight, launch vehicle

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Authors: S. Wagner, C. Boley, Y. Forouzandeh

Abstract:

When digging excavations, groundwater bearing layers are often encountered. In order to allow anhydrous excavation, soil groutings are carried out, which form a water-impermeable layer. As it is injected into groundwater areas, the effects of the materials used on the environment must be known. Developing an eco-friendly, economical and low viscous acrylic gel which has a sealing effect on groundwater is therefore a significant task. At this point the study begins. Basic investigations with the rheometer and a reverse column experiment have been performed with different mixing ratios of an acrylic gel. A dynamic rheology study was conducted to determine the time at which the gel still can be processed and the maximum gel strength is reached. To examine the effect of acrylic gel grouting on determine the parameters pH value, turbidity, electric conductivity, and total organic carbon on groundwater, an acrylic gel was injected in saturated sand filled the column. The structure was rinsed with a constant flow and the eluate was subsequently examined. The results show small changes in pH values and turbidity but there is a dependency between electric conductivity and total organic carbon. The curves of the two parameters react at the same time, which means that the electrical conductivity in the eluate can be measured constantly until the maximum is reached and only then must total organic carbon (TOC) samples be taken.

Keywords: acrylic gel grouting, dynamic rheology study, electric conductivity, total organic carbon

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Authors: Shengqi Yu, Jinwei Zhao

Abstract:

This paper presents a kind of analog circuit based temperature control system, which is mainly composed by threshold control signal circuit, synchronization signal circuit and trigger pulse circuit. Firstly, the temperature feedback signal function is realized by temperature sensor TS503F3950E. Secondly, the main control circuit forms the cycle controlled pulse signal to control the thyristor switching model. Finally two reverse paralleled thyristors regulate the output power by their switching state. In the consequence, this is a modernized and energy-saving domestic electric heating system.

Keywords: time base circuit, automatic control, zero-crossing trigger, temperature control

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Authors: Tanmaya Pradhan, K. Midhun, M. Joy Thomas

Abstract:

Increasing the shelf life and improving the quality are important objectives for the success of packaged liquid food industry. One of the methods by which this can be achieved is by deactivating the micro-organisms present in the liquid food through pasteurization. Pasteurization is done by heating, but some serious disadvantages such as the reduction in food quality, flavour, taste, colour, etc. were observed because of heat treatment, which leads to the development of newer methods instead of pasteurization such as treatment using UV radiation, high pressure, nuclear irradiation, pulsed electric field, etc. In recent years the use of the pulsed electric field (PEF) for inactivation of the microbial content in the food is gaining popularity. PEF uses a very high electric field for a short time for the inactivation of microorganisms, for which we require a high voltage pulsed power source. Pulsed power sources used for PEF treatments are usually in the range of 5kV to 50kV. Different pulse shapes are used, such as exponentially decaying and square wave pulses. Exponentially decaying pulses are generated by high power switches with only turn-on capacity and, therefore, discharge the total energy stored in the capacitor bank. These pulses have a sudden onset and, therefore, a high rate of rising but have a very slow decay, which yields extra heat, which is ineffective in microbial inactivation. Square pulses can be produced by an incomplete discharge of a capacitor with the help of a switch having both on/off control or by using a pulse forming network. In this work, a pulsed power-based system is designed with the help of high voltage capacitors and solid-state switches (IGBT) for the inactivation of pathogenic micro-organism in liquid food such as fruit juices. The high voltage generator is based on the Marx generator topology, which can produce variable amplitude, frequency, and pulse width according to the requirements. Liquid food is treated in a chamber where pulsed electric field is produced between stainless steel electrodes using the pulsed output voltage of the supply. Preliminary bacterial inactivation tests were performed by subjecting orange juice inoculated with Escherichia Coli bacteria. With the help of the developed pulsed power source and the chamber, the inoculated orange has been PEF treated. The voltage was varied to get a peak electric field up to 15kV/cm. For a total treatment time of 200µs, a 30% reduction in the bacterial count has been observed. The detailed results and analysis will be presented in the final paper.

Keywords: Escherichia coli bacteria, high voltage generator, microbial inactivation, pulsed electric field, pulsed forming line, solid-state switch

Procedia PDF Downloads 169

Authors: Masao Nakagawa, Toshiki Hirogaki, Eiichi Aoyama, Mohamed Ali Ben Abbes

Abstract:

A planetary gear set is widely used in hybrid vehicles as the power distribution system or in electric vehicles as the high reduction system, but due to its complexity with planet gears, its dynamic characteristic is not fully understood. There are many reports on two-axes driving or displacement of the planet gears under these conditions, but only few reports deal with three-axes driving. A three-axes driving condition is tested using three-axes torque measurement and focuses on the dynamic characteristic around the planet gears in this report. From experimental result, it was confirmed that the transition forces around the planet gears were balanced and the torques were also balanced around the instantaneous rotation center. The meshing frequency under these conditions was revealed to be the harmonics of two meshing frequencies; meshing frequency of the ring gear and that of the planet gears. The input power of the ring gear is distributed to the carrier and the sun gear in the dynamic sequential change of three fixed conditions; planet, star and solar modes.

Keywords: dynamic characteristic, gear, planetary gear set, torque measuring

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Authors: Maryam Mosleh, Mahmood Otadi

Abstract:

The hybrid differential equations have a wide range of applications in science and engineering. In this paper, the homotopy analysis method (HAM) is applied to obtain the series solution of the hybrid differential equations. Using the homotopy analysis method, it is possible to find the exact solution or an approximate solution of the problem. Comparisons are made between improved predictor-corrector method, homotopy analysis method and the exact solution. Finally, we illustrate our approach by some numerical example.

Keywords: Fuzzy number, parametric form of a fuzzy number, fuzzy integrodifferential equation, homotopy analysis method

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Authors: Hussain Syed Asad, Richard Kwok Kit Yuen, Gongsheng Huang

Abstract:

Real-time optimization has been considered an effective approach for improving energy efficient operation of heating, ventilation, and air-conditioning (HVAC) systems. In model-based real-time optimization, model mismatches cannot be avoided. When model mismatches are significant, the performance of the real-time optimization will be impaired and hence the expected energy saving will be reduced. In this paper, the model mismatches for chiller plant on real-time optimization are considered. In the real-time optimization of the chiller plant, simplified semi-physical or grey box model of chiller is always used, which should be identified using available operation data. To overcome the model mismatches associated with the chiller model, hybrid Genetic Algorithms (HGAs) method is used for online real-time training of the chiller model. HGAs combines Genetic Algorithms (GAs) method (for global search) and traditional optimization method (i.e. faster and more efficient for local search) to avoid conventional hit and trial process of GAs. The identification of model parameters is synthesized as an optimization problem; and the objective function is the Least Square Error between the output from the model and the actual output from the chiller plant. A case study is used to illustrate the implementation of the proposed method. It has been shown that the proposed approach is able to provide reliability in decision making, enhance the robustness of the real-time optimization strategy and improve on energy performance.

Keywords: energy performance, hybrid adaptive modeling, hybrid genetic algorithms, real-time optimization, heating, ventilation, and air-conditioning

Procedia PDF Downloads 403