Search results for: collision reduction of vehicles

Authors: Anuj Abraham, N. Pappa, Daniel Honc, Rahul Sharma

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In this paper, an analysis of some model order reduction techniques is presented. A new hybrid algorithm for model order reduction of linear time invariant systems is compared with the conventional techniques namely Balanced Truncation, Hankel Norm reduction and Dominant Pole Algorithm (DPA). The proposed hybrid algorithm is known as Clustering Dominant Pole Algorithm (CDPA) is able to compute the full set of dominant poles and its cluster center efficiently. The dominant poles of a transfer function are specific eigenvalues of the state space matrix of the corresponding dynamical system. The effectiveness of this novel technique is shown through the simulation results.

Keywords: balanced truncation, clustering, dominant pole, Hankel norm, model reduction

Procedia PDF Downloads 599

Authors: Enes Huylu, Sude Erkin, Nur A. Özdemir, Hatice K. Güney, Cemre S. Atılgan, Hüseyin Y. Altıntaş, Aysemin Top, Muammer Yılman, Özak Durmuş

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Remanufacturing (reman) applications allow manufacturers to contribute to the circular economy and help to introduce products with almost the same quality, environment-friendly, and lower cost. The objective of this study is to present that the carbon footprint of automotive spare parts used in vehicles could be reduced by reman applications based on Life Cycle Analysis which was framed with ISO 14040 principles. In that case, it was aimed to investigate reman applications for 21 parts in total. So far, research and calculations have been completed for the alternator, turbocharger, starter motor, compressor, manual transmission, auto transmission, and DPF (diesel particulate filter) parts, respectively. Since the aim of Ford Motor Company and Ford OTOSAN is to achieve net zero based on Science-Based Targets (SBT) and the Green Deal that the European Union sets out to make it climate neutral by 2050, the effects of reman applications are researched. In this case, firstly, remanufacturing articles available in the literature were searched based on the yearly high volume of spare parts sold. Paper review results related to their material composition and emissions released during incoming production and remanufacturing phases, the base part has been selected to take it as a reference. Then, the data of the selected base part from the research are used to make an approximate estimation of the carbon footprint reduction of the relevant part used in Ford OTOSAN. The estimation model is based on the weight, and material composition of the referenced paper reman activity. As a result of this study, it was seen that remanufacturing applications are feasible to apply technically and environmentally since it has significant effects on reducing the emissions released during the production phase of the vehicle components. For this reason, the research and calculations of the total number of targeted products in yearly volume have been completed to a large extent. Thus, based on the targeted parts whose research has been completed, in line with the net zero targets of Ford Motor Company and Ford OTOSAN by 2050, if remanufacturing applications are preferred instead of recent production methods, it is possible to reduce a significant amount of the associated greenhouse gas (GHG) emissions of spare parts used in vehicles. Besides, it is observed that remanufacturing helps to reduce the waste stream and causes less pollution than making products from raw materials by reusing the automotive components.

Keywords: greenhouse gas emissions, net zero targets, remanufacturing, spare parts, sustainability

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Authors: Tayyibah Khanam, Mohammad Saad Alam, Sanchari Deb, Yasser Rafat

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Electric vehicles are considered as viable replacements to gasoline cars since they help in reducing harmful emissions and stimulate power generation through renewable energy sources, hence contributing to sustainability. However, one of the significant obstacles in the mass deployment of electric vehicles is the charging time anxiety among users and, thus, the subsequent large waiting times for available chargers at charging stations. Data analytics, on the other hand, has revolutionized the decision-making tasks of management and operating systems since its arrival. In this paper, we attempt to optimize the choice of EV charging stations for users in their vicinity by minimizing the time taken to reach the charging stations and the waiting times for available chargers. Time taken to travel to the charging station is calculated by the Google Maps API and the waiting times are predicted by polynomial regression of the historical data stored. The proposed framework utilizes real-time data and historical data from all operating charging stations in the city and assists the user in finding the best suitable charging station for their current situation and can be implemented in a mobile phone application. The algorithm successfully predicts the most optimal choice of a charging station and the minimum required time for various sample data sets.

Keywords: charging data, electric vehicles, machine learning, waiting times

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Authors: Neera Singh, Devendra Kumar, Om Parkash

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We have synthesized nanocrystalline Fe-Ni alloy powders where Ni varies as 10, 30 and 50 mole% by a wet chemical route (sol-gel auto-combustion) followed by reduction in hydrogen atmosphere. The ratio of citrate to nitrate was maintained at 0.3 where citric acid has worked as a fuel during combustion. The reduction of combusted powders was done at 700°C/1h in hydrogen atmosphere using an atmosphere controlled quartz tube furnace. Phase and microstructure analysis has shown the formation of α-(Fe,Ni) and γ-(Fe,Ni) phases after reduction. An increase in Ni concentration resulted in more γ-(Fe,Ni) formation where complete γ-(Fe,Ni) formation was achieved at 50 mole% Ni concentration. Formation of particles below 50 nm size range was confirmed using Scherrer’s formula and Transmission Electron Microscope. The work is aimed at the effect of Ni concentration on phase, microstructure and magnetic properties of synthesized alloy powders.

Keywords: combustion, microstructure, nanocrystalline, reduction

Procedia PDF Downloads 181

Authors: Nicholas Lambert, Seungyeon Ryu, Mehmet Mulla, Albert Kim

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In this paper, an interactive in-car interface called HoloDash is presented. It is intended to provide information and infotainment in both autonomous vehicles and ‘connected cars’, vehicles equipped with Internet access via cellular services. The research focuses on the development of interactive avatars for this system and its gesture-based control system. This is a case study for the development of a possible human-centred means of presenting a connected or autonomous vehicle’s On-Board Diagnostics through a projected ‘holographic’ infotainment system. This system is termed a Holographic Human Vehicle Interface (HHIV), as it utilises a dashboard projection unit and gesture detection. The research also examines the suitability for gestures in an automotive environment, given that it might be used in both driver-controlled and driverless vehicles. Using Human Centred Design methods, questions were posed to test subjects and preferences discovered in terms of the gesture interface and the user experience for passengers within the vehicle. These affirm the benefits of this mode of visual communication for both connected and driverless cars.

Keywords: gesture, holographic interface, human-computer interaction, user-centered design

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Authors: Alcardo Alex Barakabitze, Saddam Aziz, Muhammad Zubair

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The Orthogonal Frequency Division Multiplexing (OFDM) is a special form of multicarrier transmission that splits the total transmission bandwidth into a number of orthogonal and non-overlapping subcarriers and transmit the collection of bits called symbols in parallel using these subcarriers. In this paper, we explore the Peak to Average Power Reduction (PAPR) problem in OFDM systems. We provide the performance analysis of CCDF and BER through MATLAB simulations.

Keywords: bit error ratio (BER), OFDM, peak to average power reduction (PAPR), sub-carriers

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Authors: Rafi Ullah, Shah Muhammad Emaduddin, Taha Jilani

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Vehicle Adhoc Networks (VANET) belongs to a special class of Mobile Adhoc Network (MANET) with high mobility. Network is created by road side vehicles equipped with communication devices like GPS and Wifi etc. Since the environment is highly dynamic due to difference in speed and high mobility of vehicles and weak stability of the network connection, it is a challenging task to design an efficient routing protocol for such an unstable environment. Our proposed algorithm uses heuristic for the calculation of optimal path for routing the packet efficiently in collaboration with several other parameters like geographical location, speed, priority, the distance among the vehicles, communication range, and networks congestion. We have incorporated probabilistic, heuristic and machine learning based approach inconsistency with the relay function of the memory buffer to keep the packet moving towards the destination. These parameters when used in collaboration provide us a very strong and admissible heuristics. We have mathematically proved that the proposed technique is efficient for the routing of packets, especially in a medical emergency situation. These networks can be used for medical emergency, security, entertainment and routing purposes.

Keywords: heuristics routing, intelligent routing, VANET, route optimization

Procedia PDF Downloads 176

Authors: Man Chul Jeong, Hyoung Jin Lee, Sang Yoon Lee, Ji Hyun Park, Min Wook Chang, In-Seuck Jeung

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This study focus on the drag reduction effect of the base bleed at supersonic flow. Base bleed is the method which bleeds the gas on the tail of the flight vehicle and reduces the base drag, which occupies over 50% of the total drag in any flight speed. Thus base bleed can reduce the total drag significantly, and enhance the total flight range. Drag reduction ratio of the base bleed is strongly related to the mass flow rate of the bleeding gas. Thus selecting appropriate mass flow rate is important. However, since the flight vehicle has various flight speed, same mass flow rate of the base bleed can have different drag reduction effect during the flight. Thus, this study investigates the effect of the drag reduction depending on the flight speed by numerical analysis using STAR-CCM+. The analysis model is 155mm diameter projectile with boat-tailed shape base. Angle of the boat-tail is chosen previously for minimum drag coefficient. Numerical analysis is conducted for Mach 2 and Mach 3, with various mass flow rate, or the injection parameter I, of the bleeding gas and the temperature of the bleeding gas, is fixed to 300K. The results showed that I=0.025 has the minimum drag at Mach 2, and I=0.014 has the minimum drag at Mach 3. Thus as the Mach number is higher, the lower mass flow rate of the base bleed has more effect on drag reduction.

Keywords: base bleed, supersonic, drag reduction, recirculation

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Authors: Mostafa Dastori, Sirus Mohammadi

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While plug-in electric vehicles (PEVs) potentially have the capability to fulfill the energy storage needs of the electric grid, the degradation on the battery during this operation makes it less preferable by the auto manufacturers and consumers. On the other hand, the on-board chargers can also supply energy storage system applications such as reactive power compensation, voltage regulation, and power factor correction without the need of engaging the battery with the grid and thereby preserving its lifetime. It presents the design motives of single-phase on-board chargers in detail and makes a classification of the chargers based on their future vehicle-to-grid usage. The pros and cons of each different ac–dc topology are discussed to shed light on their suit- ability for reactive power support. This paper also presents and analyzes the differences between charging-only operation and capacitive reactive power operation that results in increased demand from the dc-link capacitor (more charge/discharge cycles and in- creased second harmonic ripple current). Moreover, battery state of charge is spared from losses during reactive power operation, but converter output power must be limited below its rated power rating to have the same stress on the dc-link capacitor.

Keywords: energy storage system, battery unit, cost, optimal sizing, plug-in electric vehicles (PEVs), smart grid

Procedia PDF Downloads 343

Authors: S. Malarvizhi, S. Sadiq Basha, M. Santhosh Kumar, K. Saravanan, R. Sasikumar, R. Satheesh

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This is a web based application which provides authorization for the vehicle identification and registration. It also provides mutual authentication between the police and users in order to avoid misusage. The QR code generation in this application overcomes the difficulty in the manual registration of the vehicle documents. This generated QR code is placed in the number plates of the vehicles. The QR code is scanned using the QR Reader installed in the smart devices. The police officials can check the vehicle details and file cases on accidents, theft and traffic rules violations using QR code. In addition to vehicle insurance payments and renewals, the renewal alert is sent to the vehicle owner about payment deadline. The non-permitted vehicles can be blocked in the next check-post by sending the alert messages.

Keywords: QR code, QR reader, registration, authentication, idenfication

Procedia PDF Downloads 494

Authors: Tapan Upadhyay, Aqib Siddiqui, Sameer Khan

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Railway crossing system in India is a manually operated level crossing system, either manned or unmanned. The main aim is to protect pedestrians and vehicles from colliding with trains, which pass at regular intervals, as India has the largest and busiest railway network. But because of human error and negligence, every year thousands of lives are lost due to accidents at railway crossings. To avoid this, we suggest a solution, by using Programmable Logical Controller (PLC) based automatic system, which will automatically control the barrier as well as roadblocks to stop people from crossing while security warning is given. Often people avoid security warning, and pass two-wheelers from beneath the barrier, while the train is at a distance away. This paper aims at reducing the fatality and accident rate by controlling barrier and roadblocks using sensors which sense the incoming train and vehicles and sends a signal to PLC. The PLC in return sends a signal to barrier and roadblocks. Once the train passes, the barrier and roadblocks retrieve back, and the passage is clear for vehicles and pedestrians to cross. PLC’s are used because they are very flexible, cost effective, space efficient, reduces complexity and minimises errors. Supervisory Control And Data Acquisition (SCADA) is used to monitor the functioning.

Keywords: level crossing, PLC, sensors, SCADA

Procedia PDF Downloads 427

Authors: M. Uysal, M. Yilmaz, I. Tiryakioğlu

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Digital Terrain Model (DTM) is a digital numerical representation of the Earth's surface. DTMs have been applied to a diverse field of tasks, such as urban planning, military, glacier mapping, disaster management. In the expression of the Earth' surface as a mathematical model, an infinite number of point measurements are needed. Because of the impossibility of this case, the points at regular intervals are measured to characterize the Earth's surface and DTM of the Earth is generated. Hitherto, the classical measurement techniques and photogrammetry method have widespread use in the construction of DTM. At present, RADAR, LiDAR, and stereo satellite images are also used for the construction of DTM. In recent years, especially because of its superiorities, Airborne Light Detection and Ranging (LiDAR) has an increased use in DTM applications. A 3D point cloud is created with LiDAR technology by obtaining numerous point data. However recently, by the development in image mapping methods, the use of unmanned aerial vehicles (UAV) for photogrammetric data acquisition has increased DTM generation from image-based point cloud. The accuracy of the DTM depends on various factors such as data collection method, the distribution of elevation points, the point density, properties of the surface and interpolation methods. In this study, the random data reduction method is compared for DTMs generated from image based point cloud data. The original image based point cloud data set (100%) is reduced to a series of subsets by using random algorithm, representing the 75, 50, 25 and 5% of the original image based point cloud data set. Over the ANS campus of Afyon Kocatepe University as the test area, DTM constructed from the original image based point cloud data set is compared with DTMs interpolated from reduced data sets by Kriging interpolation method. The results show that the random data reduction method can be used to reduce the image based point cloud datasets to 50% density level while still maintaining the quality of DTM.

Keywords: DTM, Unmanned Aerial Vehicle (UAV), uniform, random, kriging

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Authors: Yaser E. Hawas, Md. Didarul Alam

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Rollover crashes are complex events entailing interactions of driver, road, vehicle, and environmental factors. The primary objective of this paper is to present an empirical approach that can be used to characterise the rollover crashes and to identify some of the important factors that may lead to rollovers. Among the studied factors are the vehicle types and the rollover occurrence rate after hitting various barrier types. The carried analysis indicated that 71% of the rollover crashes occurred after impact and the type of rollover initiation is “trip/turn over” (nearly 50%). It was also found that light trucks (LTVs) vehicles are more likely to rollover than the sedan vehicles. Barrier impacts are associated with increased incidence of rollover.

Keywords: empirical, hitting barrier, in-depth crash investigation, rollover, severe crash

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Authors: Tuğrul Aksoy, Hüseyin Karabıyık

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Reloading vehicles are the vehicles which are generally equipped with a crane and used to carry a stowage from a point and locate onto the vehicle or vice versa. In this study, structural analysis of a reloading vehicle was performed under the loads which are predicted to be exposed under operating conditions via the finite element method. Among the finite element analysis results, the stress and displacement distributions of the vehicle and the contact pressure distributions of the guide rings within the stabilization legs were examined. Vehicle design was improved by strengthening certain parts according to the analysis results. The analyses performed for the final design were verified by the experiments involving strain gauge measurements.

Keywords: structural analysis, reloading vehicle, crane, strain gauge

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Authors: Shahin A. Abdel-Naby, Asad T. Hassan

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Astrophysical plasma environments can be classified into collisionally ionized (CP) and photoionizedplasmas (PP). In the PP, ionization is caused by an external radiation field, while it is caused by electron collision in the CP. Accurate and reliable laboratory astrophysical data for electron-ion recombination is needed for plasma modeling for low and high-temperatures. Dielectronic recombination (DR) is the dominant recombination process for the CP for most of the ions. When a free electron is captured by an ion with simultaneous excitation of its core, a doubly-exited intermediate state may be formed. The doubly excited state relaxes either by electron emission (autoionization) or by radiative decay (photon emission). DR process takes place when the relaxation occurs to a bound state by a photon emission. DR calculations at low-temperatures are problematic and challenging since small uncertaintiesin the low-energy DR resonance positions can produce huge uncertainties in DR rate coefficients.DR rate coefficients for N²⁺ and O³⁺ ions are calculated using state-of-the-art multi-configurationBreit-Pauli atomic structure AUTOSTRUCTURE collisional package within the generalized collisional-radiative framework. Level-resolved calculations for RR and DR rate coefficients from the ground and metastable initial states are produced in an intermediate coupling scheme associated withn = 0 and n = 1 core-excitations. DR cross sections for these ions are convoluted with the experimental electron-cooler temperatures to produce DR rate coefficients. Good agreements are foundbetween these rate coefficients and theexperimental measurements performed at CRYRING heavy-ionstorage ring for both ions.

Keywords: atomic data, atomic process, electron-ion collision, plasmas

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Authors: Nur A. Özdemir, Sude Erkin, Hatice K. Güney, Cemre S. Atılgan, Enes Huylu, Hüseyin Y. Altıntaş, Aysemin Top, Özak Durmuş

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Carbon emissions produced during a product’s life cycle, from extraction of raw materials up to waste disposal and market consumption activities are the major contributors to global warming. In the light of the science-based targets (SBT) leading the way to a zero-carbon economy for sustainable growth of the companies, carbon footprint reporting of the purchased goods has become critical for identifying hotspots and best practices for emission reduction opportunities. In line with Ford Otosan's corporate sustainability strategy, research was conducted to evaluate the carbon footprint of purchased products in accordance with Scope 3 of the Greenhouse Gas Protocol (GHG). The purpose of this paper is to develop a systematic and transparent methodology to calculate carbon footprint of the products produced by automotive OEMs (Original Equipment Manufacturers) within the context of automobile supply chain management. To begin with, primary material data were collected through IMDS (International Material Database System) corresponds to company’s three distinct types of vehicles including Light Commercial Vehicle (Courier), Medium Commercial Vehicle (Transit and Transit Custom), Heavy Commercial Vehicle (F-MAX). Obtained material data was classified as metals, plastics, liquids, electronics, and others to get insights about the overall material distribution of produced vehicles and matched to the SimaPro Ecoinvent 3 database which is one of the most extent versions for modelling material data related to the product life cycle. Product life cycle analysis was calculated within the framework of ISO 14040 – 14044 standards by addressing the requirements and procedures. A comprehensive literature review and cooperation with suppliers were undertaken to identify the production methods of parts used in vehicles and to find out the amount of scrap generated during part production. Cumulative weight and material information with related production process belonging the components were listed by multiplying with current sales figures. The results of the study show a key modelling on carbon footprint of products and processes based on a scientific approach to drive sustainable growth by setting straightforward, science-based emission reduction targets. Hence, this study targets to identify the hotspots and correspondingly provide broad ideas about our understanding of how to integrate carbon footprint estimates into our company's supply chain management by defining convenient actions in line with climate science. According to emission values arising from the production phase including raw material extraction and material processing for Ford OTOSAN vehicles subjected in this study, GHG emissions from the production of metals used for HCV, MCV and LCV account for more than half of the carbon footprint of the vehicle's production. Correspondingly, aluminum and steel have the largest share among all material types and achieving carbon neutrality in the steel and aluminum industry is of great significance to the world, which will also present an immense impact on the automobile industry. Strategic product sustainability plan which includes the use of secondary materials, conversion to green energy and low-energy process design is required to reduce emissions of steel, aluminum, and plastics due to the projected increase in total volume by 2030.

Keywords: automotive, carbon footprint, IMDS, scope 3, SimaPro, sustainability

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Authors: Derlis Gregor, Kevin Cikel, Mario Arzamendia, Raúl Gregor

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This paper presents a self-sustaining mobile system for counting and classification of vehicles through processing video. It proposes a counting and classification algorithm divided in four steps that can be executed multiple times in parallel in a SBC (Single Board Computer), like the Raspberry Pi 2, in such a way that it can be implemented in real time. The first step of the proposed algorithm limits the zone of the image that it will be processed. The second step performs the detection of the mobile objects using a BGS (Background Subtraction) algorithm based on the GMM (Gaussian Mixture Model), as well as a shadow removal algorithm using physical-based features, followed by morphological operations. In the first step the vehicle detection will be performed by using edge detection algorithms and the vehicle following through Kalman filters. The last step of the proposed algorithm registers the vehicle passing and performs their classification according to their areas. An auto-sustainable system is proposed, powered by batteries and photovoltaic solar panels, and the data transmission is done through GPRS (General Packet Radio Service)eliminating the need of using external cable, which will facilitate it deployment and translation to any location where it could operate. The self-sustaining trailer will allow the counting and classification of vehicles in specific zones with difficult access.

Keywords: intelligent transportation system, object detection, vehicle couting, vehicle classification, video processing

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Authors: Phillip Garrad, Saritha Unnikrishnan

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The recent popularity of connected and autonomous vehicles (CAV) corresponds with an increase in the risk of cyber-attacks. These cyber-attacks have been instigated by both researchers or white-coat hackers and cyber-criminals. As Connected Vehicles move towards full autonomy, the impact of these cyber-attacks also grows. The current research details challenges faced in cybersecurity testing of CAV, including access and cost of the representative test setup. Other challenges faced are lack of experts in the field. Possible solutions to how these challenges can be overcome are reviewed and discussed. From these findings, a software simulated CAV network is established as a cost-effective representative testbed. Penetration tests are then performed on this simulation, demonstrating a cyber-attack in CAV. Studies have shown Artificial Intelligence (AI) to improve runtime, increase efficiency and comprehensively cover all the typical test aspects in penetration testing in other industries. There is an attempt to introduce similar AI models to the software simulation. The expectation from this implementation is to see similar improvements in runtime and efficiency for the CAV model. If proven to be an effective means of penetration test for CAV, this methodology may be used on a full CAV test network.

Keywords: cybersecurity, connected vehicles, software simulation, artificial intelligence, penetration testing

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Authors: Sihyun Park, Hyunwoo Kim, Wooyoung Jung, Dongwoo You

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Regular maintenance works are very important on the axial forces of the cable-band bolts in suspension bridges. The band bolts show stress reduction for several reasons, including cable wire creep, the bolt relaxation, load fluctuation and cable rearrangements, etc., with time. In this study, with respect to the stress reduction that occurs over time, we carried out the theoretical review of the main cause based on the field measurements. As a result, the main cause of reduction in the cable-band bolt axial force was confirmed by the plastic deformation of the zinc plating layer used in the main cable wire, and thus, the theoretical process was established for the practical use in the field.

Keywords: cable-band Bolts, field test, maintenance, stress reduction

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Authors: Alexander J. Severinsky, Allen L. Sessoms

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Atmospheric carbon dioxide (CO₂) has dominated the discussion about the causes of climate change. This is a reflection of the time horizon that has become the norm adopted by the IPCC as the planning horizon. Recently, it has become clear that a 100-year time horizon is much too long, and yet almost all mitigation efforts, including those in the near-term horizon of 30 years, are geared toward it. In this paper, we show that, for a 30-year time horizon, methane (CH₄) is the greenhouse gas whose radiative forcing exceeds that of CO₂. In our analysis, we used radiative forcing of greenhouse gases in the atmosphere since they directly affect the temperature rise on Earth. In 2019, the radiative forcing of methane was ~2.5 W/m² and that of carbon dioxide ~2.1 W/m². Under a business-as-usual (BAU) scenario until 2050, such forcing would be ~2.8 W/m² and ~3.1 W/m², respectively. There is a substantial spread in the data for anthropogenic and natural methane emissions as well as CH₄ leakages from production to consumption. We estimated the minimum and maximum effects of the reduction of these leakages. Such action may reduce the annual radiative forcing of all CH₄ emissions by between ~15% and ~30%. This translates into a reduction of the RF by 2050 from ~2.8 W/m² to ~2.5 W/m² in the case of the minimum effect and to ~2.15 W/m² in the case of the maximum. Under the BAU, we found that the RF of CO₂ would increase from ~2.1 W/m² nowadays to ~3.1 W/m² by 2050. We assumed a reduction of 50% of anthropogenic emission linearly over the next 30 years. That would reduce radiative forcing from ~3.1 W/m² to ~2.9 W/m². In the case of ‘net zero,’ the other 50% of reduction of only anthropogenic emissions would be limited to either from sources of emissions or directly from the atmosphere. The total reduction would be from ~3.1 to ~2.7, or ~0.4 W/m². To achieve the same radiative forcing as in the scenario of maximum reduction of methane leakages of ~2.15 W/m², then an additional reduction of radiative forcing of CO₂ would be approximately 2.7 -2.15=0.55 W/m². This is a much larger value than in expectations from ‘net zero’. In total, one needs to remove from the atmosphere ~660 GT to match the maximum reduction of current methane leakages and ~270 GT to achieve ‘net zero.’ This amounts to over 900 GT in total.

Keywords: methane leakages, methane radiative forcing, methane mitigation, methane net zero

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Authors: I. Muslih, A. Alkhalailah, A. Merdji

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Photovoltaic efficiency is highly affected by dust accumulation; the dust particles prevent direct solar radiation from reaching the panel surface; therefore a reduction in output power will occur. A study of dust and soiling accumulation effect on the output power of PV panels was conducted for different periods of time from May to October in three countries of the MENA region, Jordan, Egypt, and Algeria, under local weather conditions. This study leads to build a more realistic equation to estimate the power reduction as a function of time. This logarithmic function shows the high reduction in power in the first days with 10% reduction in output power compared to the reference system, where it reaches a steady state value after 60 days to reach a maximum value of 30%.

Keywords: dust effect, MENA, solar energy, PV system

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Authors: Dimitrios I. Tselentis, Simon P. Washington

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Considerable literature has been focused over the last few decades on forecasting the consumer demand of Energy Efficient Vehicles (EEVs). These methodological issues range from how to capture recent purchase decisions in revealed choice studies and how to set up experiments in stated preference (SP) studies, and choice of analysis method for analyzing such data. This paper reviews the plethora of published studies on the field of forecasting demand of EEVs since 1980, and provides a review and annotated bibliography of that literature as it pertains to this particular demand forecasting problem. This detailed review addresses the literature not only to Transportation studies, but specifically to the problem and methodologies around forecasting to the time horizons of planning studies which may represent 10 to 20 year forecasts. The objectives of the paper are to identify where existing gaps in literature exist and to articulate where promising methodologies might guide longer term forecasting. One of the key findings of this review is that there are many common techniques used both in the field of new product demand forecasting and the field of predicting future demand for EEV. Apart from SP and RP methods, some of these new techniques that have emerged in the literature in the last few decades are survey related approaches, product diffusion models, time-series modelling, computational intelligence models and other holistic approaches.

Keywords: demand forecasting, Energy Efficient Vehicles (EEVs), forecasting methodologies review, methodological approaches

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Authors: Ismail Kurt, Necibe Fusun Oyman Serteller

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Today, with the reduction in semiconductor system costs, Brushless Direct Current (BLDC) motors have become widely preferred. Based on rotor architecture, BLDC structures are divided into internal permanent magnet (IPM) and surface permanent magnet (SPM). However, permanent magnet (PM) motors in electric vehicles (EVs) are still predominantly based on interior permanent magnet (IPM) motors, as the rotors do not require sleeves, the PMs are better protected by the rotor cores, and the air-gap lengths can be much smaller. This study discusses the IPM rotor structure in detail, highlighting its higher torque levels, reluctance torque, wide speed range operation, and production advantages. IPM rotor structures are particularly preferred in EVs due to their high-speed capabilities, torque density and field weakening (FW) features. In FW applications, the motor becomes more suitable for operation at torques lower than the rated torque but at speeds above the rated speed. Although V-type and triangular IPM rotor structures are generally preferred in EV applications, the spoke-type rotor structure offers distinct advantages, making it a competitive option for these systems. The flux barriers in the rotor significantly affect motor performance, providing notable benefits in both motor efficiency and cost. This study utilizes ANSYS/Maxwell simulation software to analyze the spoke-type IPM motor and examine its key design parameters. Through analytical and 2D analysis, preliminary motor design and parameter optimization have been carried out. During the parameter optimization phase, torque ripple a common issue, especially for IPM motors has been investigated, along with the associated changes in motor parameters.

Keywords: electric vehicle, field weakening, flux barrier, spoke rotor.

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Authors: Ali J. Ghandour, Houssam A. Krayem, Abedelkarim A. Jezzini

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High-resolution satellite images and remote sensing can provide global information in a fast way compared to traditional methods of data collection. Under such high resolution, a road is not a thin line anymore. Objects such as cars and trees are easily identifiable. Automatic vehicles enumeration can be considered one of the most important applications in traffic management. In this paper, autonomous vehicle detection and classification approach in highway environment is proposed. This approach consists mainly of three stages: (i) first, a set of preprocessing operations are applied including soil, vegetation, water suppression. (ii) Then, road networks detection and delineation is implemented using built-up area index, followed by several morphological operations. This step plays an important role in increasing the overall detection accuracy since vehicles candidates are objects contained within the road networks only. (iii) Multi-level Otsu segmentation is implemented in the last stage, resulting in vehicle detection and classification, where detected vehicles are classified into cars and trucks. Accuracy assessment analysis is conducted over different study areas to show the great efficiency of the proposed method, especially in highway environment.

Keywords: remote sensing, object identification, vehicle and road extraction, vehicle and road features-based classification

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Authors: Nelson Andres, Meeko C. Masangcap, John Denver D. Catapang

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Balanga City as, the heart of Bataan, is a growing City and is now at its fast pace of development. The growth of commerce in the city results to an increase in commuters who travel back and forth through the city, leading to congestions. Consequently, queuing of vehicles along national roads and even in the highways of the city have become a regular occurrence. This common scenario of commuters flocking the city, private and public vehicles going bumper to bumper, especially during the rush hours, greatly affect the flow of traffic vehicles and is now a burden not only to the commuters but also to the government who is trying to address this dilemma. Seeing these terrible events, the implementation of an elevated Automated Guide-way transit is seen as a possible solution to help in the decongestion of the affected parts of Balanga City.In response to the problem, the researchers identify if it is feasible to have an elevated guide-way transit in the vicinity of Sapphire Street in Balanga City, Bataan. Specifically, the study aims to determine who will be the riders based on the demographic profile, where the trip can be generated and distributed, the time when volume of people usually peaks and the estimated volume of passengers. Statistical analysis is applied to the data gathered to find out if there is an important relationship between the demographic profile of the respondents and their preference of having an elevated railway transit in the City of Balanga.

Keywords: ridership, AGT, railway, elevated track

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Authors: Mulatu Kassie Birhanu

Abstract:

Electrochemical reduction of CO₂ is an emerging and current issue for its conversion in to valuable product upon minimization of its atmospheric level for contribution of maintaining within the range of permissible limit. Among plenty of electro-catalysts gold and copper are efficient and effective catalysts, which are synthesized and applicable for this research work. The two metal catalysts were prepared in inert environment with different compositions through co-reduction process from their corresponding precursors and then by adding multi-walled carbon nano-tube as a supporter and enhanced the conductivity. The catalytic performance of CO₂ reduction for each composition was performed and resulted an outstanding catalytic activity with generation of high current density (70 mA/cm² at 0.91V vs. RHE) and relatively small onset potential. The catalytic performance, compositions, morphologies, structure and geometric arrangements were evaluated by electrochemical analysis (LSV, impedance, chronoamperometry & tafel plot), EDS, SEM and XAS respectively. The composite metals showed better selectivity of products and faradaic efficiencies due to the synergetic effects of the combined nano-particles in addition to the impact of grain size in reduction of CO₂. Carbon monoxide, hydrogen, formate and ethanol are the reduction products, which are detected and quantifiable by chromatographic techniques considering their physical state of each product.

Keywords: carbondioxide, faradaic efficiency, electrocatalyst, current density

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Authors: Sonali Panigrahy, Manjunatha K., Sudip Barman

Abstract:

Electrocatalytic reduction methods hold significant promise in addressing the urgent need to mitigate excessive greenhouse gas emissions, particularly carbon dioxide (CO₂). A highly effective catalyst is essential for achieving the conversion of CO₂ into valuable products due to the complex, multi-electron, and multi-product nature of the CO₂ reduction process. The electrochemical reduction of CO₂, driven by renewable energy sources, presents a valuable opportunity for simultaneously reducing CO₂ emissions while generating valuable chemicals and fuels, with syngas being a noteworthy product. Silver-based electrodes have been the focus of extensive research due to their low overpotential and remarkable selectivity in promoting the generation of carbon monoxide (CO) in the electrocatalytic carbon dioxide reduction reaction (CO₂RR). In this study, we delve into the synthesis of carbon-supported silver nanoparticles (Ag/C), which serve as efficient electrocatalysts for the reduction of CO₂. The as-prepared catalyst, Ag/C, is not only cost-effective but also highly proficient in facilitating the conversion of CO₂ and H₂O into syngas, which is a customizable mixture of hydrogen (H₂) and carbon monoxide (CO). The highest faradic efficiency for the production of CO on Ag/C was calculated to be 56.4% at -1.4 V vs Ag/AgCl. The maximum partial current density for the generation of CO was determined to be -9.4 mA cm-2 at a potential of -1.6 V vs Ag/AgCl. This research demonstrates the potential of Ag/C as an electrocatalyst to enable the sustainable production of syngas, contributing to the reduction of CO₂ emissions and the synthesis of valuable chemical precursors and fuels.

Keywords: CO₂, carbon monooxide, electrochemical, silver

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Authors: Ahmet Karagoz, Irfan Karagoz

Abstract:

Synthetic Aperture Radar (SAR) is a radar mechanism that can be integrated into manned and unmanned aerial vehicles to create high-resolution images in all weather conditions, regardless of day and night. In this study, SAR images of military vehicles with different azimuth and descent angles are pre-processed at the first stage. The main purpose here is to reduce the high speckle noise found in SAR images. For this, the Wiener adaptive filter, the mean filter, and the median filters are used to reduce the amount of speckle noise in the images without causing loss of data. During the image segmentation phase, pixel values are ordered so that the target vehicle region is separated from other regions containing unnecessary information. The target image is parsed with the brightest 20% pixel value of 255 and the other pixel values of 0. In addition, by using appropriate parameters of statistical region merging algorithm, segmentation comparison is performed. In the step of feature extraction, the feature vectors belonging to the vehicles are obtained by using Gabor filters with different orientation, frequency and angle values. A number of Gabor filters are created by changing the orientation, frequency and angle parameters of the Gabor filters to extract important features of the images that form the distinctive parts. Finally, images are classified by sparse representation method. In the study, l₁ norm analysis of sparse representation is used. A joint database of the feature vectors generated by the target images of military vehicle types is obtained side by side and this database is transformed into the matrix form. In order to classify the vehicles in a similar way, the test images of each vehicle is converted to the vector form and l₁ norm analysis of the sparse representation method is applied through the existing database matrix form. As a result, correct recognition has been performed by matching the target images of military vehicles with the test images by means of the sparse representation method. 97% classification success of SAR images of different military vehicle types is obtained.

Keywords: automatic target recognition, sparse representation, image classification, SAR images

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Authors: Z. Jovanovic, Z. Masonicic, S. Dragutinovic, Z. Sakota

Abstract:

In this paper, a methodology for noise reduction of motor vehicles in use is presented. The methodology relies on synergic model of noise generation as a function of time. The arbitrary number of motor vehicle noise sources act in concert yielding the generation of the overall noise level of motor vehicle thereafter. The number of noise sources participating in the overall noise level of motor vehicle is subjected to the constraint of the calculation of the acoustic potential of each noise source under consideration. It is the prerequisite condition for the calculation of the acoustic potential of the whole vehicle. The recast form of pertinent set of equations describing the synergic model is laid down and solved by dint of Gauss method. The bunch of results emerged and some of them i.e. those ensuing from model application to MDD FAP Priboj motor vehicle in use are particularly elucidated.

Keywords: noise abatement, MV noise sources, noise source identification, muffler

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Authors: Nittaya Nokham, Nattaphon Kamon, Pipatpong Pimkhot, Pedcharada Yusuk

Abstract:

Testing efficacy of a bio-product (bp) to reduce amount of arsenic was carried out in soil which were used for cultivation of organic vegetables, at Watchan Royal Project Development Center, Kulayaniwattana district, Chiang Mai. The test consists of 6 treatments e.g. Tr.1) Control: To underlie the planting pits (pp)with compost; Tr.2) Using bp: To underlie thepp with compost mixed with (+) bp at 100 g/pit; Tr.3) Using bp: To underlie the pp with compost + bp at 100 g/pit and to spray the vegetables with bp at 2 l/20 l of water, once a week; Tr.4) Using bp: To spread the compost bp on the planting area at 3 kg/1 m2 ; Tr.5) Using bp: To spread the compost + bp on the planting area at 3 kg/1 m2and to spray vegetables with bp at 2 l/20 l of water; Tr.6) Using bp: To spray vegetables with bp at 2 l/20 l of water. Result showed that after first trial of pointed cabbage cultivation, only Tr.6 had a small reduction of arsenic; while the others had higher amount of the metal. After second trial of growing red oak leaf, Tr.6 had more reduction of arsenic while Tr.5 and Tr.3 had less reduction compared to Tr.6 but more reduction than the others. In the third trial of growing mustard, very small reduction could be found on Tr.6 and Tr.5 but more reduction in Tr.3. For the fourth (last) trial with cos romaine lettuce: Tr.6, Tr.5 showed most reduction of arsenic to about half of the original amount. So, it can be concluded that this bio-product can help reducing arsenic when using this product by spraying the bp to vegetables at concentration of 2 l/20 l of water once week (Tr.6), or using the bio-product mixed with compost to spread on the planting area at 3 kg/1 m2 together with spraying the product (Tr.5). The results obtained from continuous planting 4 kinds of vegetables at the same area. The amount of arsenic found in roots and stem is very small in the 4 vegetables.

Keywords: organic vegetables, bio-product, arsenic, soil

Procedia PDF Downloads 279