Academic literature on the topic 'Electric car range prediction'
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Journal articles on the topic "Electric car range prediction"
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Abdul Karim, Kasrul, Md Nazri Othman, Wan Ahmas Redhauddin, Mohd Ismadi Bugis, Zulkifli Ramli, Abdul Rahim Abdullah, and Auzani Jidin. "Electric Vehicle Development and Prediction of Battery Consumption Based on a Journey Profile." Applied Mechanics and Materials 699 (November 2014): 794–99. http://dx.doi.org/10.4028/www.scientific.net/amm.699.794.
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The lack of internal combustion engine (ICE) for electric vehicle (EV) makes it solely dependable on battery supply. Due to this, the prediction of battery consumption becomes crucial to determine the accurate driving range before the car needs to be re-charged. The developed prediction model can also be applied as simulation tool and help in reducing the length and the cost of the EV design process. This paper presents the prediction of battery power requirement for a small re-engineered EV converted from a commercial ICE car by using vehicle dynamic mathematical equations. The prediction is performed based on multiple journey profile that gathered before the actual test. The development of re-engineered EV is also presented, along with the experimental result of an actual drive test on a racing circuit to validate the prediction model.
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Bucher, Dominik, Henry Martin, Jannik Hamper, Atefeh Jaleh, Henrik Becker, Pengxiang Zhao, and Martin Raubal. "Exploring Factors that Influence Individuals’ Choice Between Internal Combustion Engine Cars and Electric Vehicles." AGILE: GIScience Series 1 (July 15, 2020): 1–23. http://dx.doi.org/10.5194/agile-giss-1-2-2020.
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Abstract. The adoption of electric vehicles has the potential to help decarbonizing the transport sector if they are powered by renewable energy sources. Limitations commonly associated with e-cars are their comparatively short ranges and long recharging cycles, leading to anxiety when having to travel long distances. Other factors such as temperature, destination or weekday may influence people in choosing an e-car for a certain trip. Using a unique dataset of 129 people who own both an electric vehicle (EV) as well as one powered by an internal combustion engine (ICE), we analyze tracking data over a year in order to have an empirically verified choice model. Based on a wide range of predictors, this model tells us for an individual journey if the person would rather choose the EV or the ICE car. Our findings show that there are only weak relations between the predictor and target variables, indicating that for many people the switch to an e-car would not affect their lifestyle and the related range anxiety diminishes when actually owning an electric vehicle. In addition, we find that choice behavior does not generalize well over different users.
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Lee, Choong Hoon. "Transient Fuel Injection Rate and Fuel Economy Prediction for a Vehicle Driven with FTP-75 Mode Using an ECU HILS." Advanced Materials Research 772 (September 2013): 543–48. http://dx.doi.org/10.4028/www.scientific.net/amr.772.543.
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A fuel injection system which is operated with ECU HILS was used to evaluate the transient fuel injection rate and fuel economy. Several sensor signals from a car such as the engine speed, car speed, cam position, crank position, air mass flow, throttle position and several other sensor signals are measured and recorded as a data file with DAQ-system for a vehicle driven in FTP-75 mode in a chassis dynamometer. Electric signals that are equivalent to the sensor signals from the car are reconstructed from the recorded data file using DAQ boards and a computer. All the reconstructed sensor signals are provided to the ECU with synchronized timing. Injectors were connected to the ECU output pins and were driven by the system to measure the quantity of injected fuel. The ECU HILS show that the transient fuel injection rate and fuel economy for the car driving mode could be successfully predicted. Also, the repeatability of the generation of sensor signals can enhance the accuracy of a range of experiments related to cars fuel injection experiment.
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Philipsen, Ralf, Teresa Brell, Hannah Biermann, and Martina Ziefle. "Under Pressure—Users’ Perception of Range Stress in the Context of Charging and Traditional Refueling." World Electric Vehicle Journal 10, no. 3 (August 1, 2019): 50. http://dx.doi.org/10.3390/wevj10030050.
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Although electric drives can locally reduce the environmental impact of traffic, the penetration rates of battery electric vehicles (BEV) are far below expectations, not least because the charging infrastructure network is still considered insufficient by potential users. Therefore, the planning of charging infrastructure that considers both needs and user requirements is essential to remove an important barrier to widespread adaptation of e-vehicles, but it is also a challenge. A better understanding of the charging behavior and the underlying usage motivation is therefore needed. A frequently mentioned factor is the so-called range stress. While there are many studies on this subject with new BEV users, there is a lack of approaches that also include experienced e-vehicle users and at the same time allow a comparison with drivers of cars with internal combustion engines (ICE). In this paper, this is realized with the help of a questionnaire study ( n = 204 ). The results show that ICE and BEV users at different experience levels hardly differ regarding the perceived range stress; BEV users even perceive less stress. BEV users also showed more trust in the vehicle and in the tank/battery indicators, while this trust depends only marginally on the type of information provided by the car. Furthermore, there is a correlation between users’ technology commitment and risk-taking, on the one hand, and range stress, on the other. However, for the prediction of range stress, gender, experience with e-cars, and the question of whether cars are privately owned, or car-sharing is used, are more relevant.
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Gonsrang, S., and R. Kasper. "Optimisation-Based Power Management System for an Electric Vehicle with a Hybrid Energy Storage System." International Journal of Automotive and Mechanical Engineering 15, no. 4 (December 24, 2018): 5729–47. http://dx.doi.org/10.15282/ijame.15.4.2018.2.0439.
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Hybridisation of energy storage sources is necessary for extending mileage of electric vehicles. However, coordination of multiple devices with different characteristics is challenging. This paper presents a power management system (PMS) for an electric car equipped with a battery pack, supercapacitor bank, and range extender. The proposed PMS deals with vehicular load distribution by solving a power management problem, formulated as a constrained quadratic program (CQP). Then, the optimised variables, such as the desired speed and optimised operation points of the car’s components, are implemented by controllers at a component level. Complete knowledge about the trip is unwanted because the proposed PMS considers a power management problem only over a controlled horizon of one sampling period. Furthermore, this work varies weight factors to tackle various difficulties, for instance, regenerative power management. The simulation results revealed that the proposed system optimally allocated an electric power load to the car components, without violating any physical constraints. Also, the comparative study showed that the performance of the CQP in power management was comparable to that of the benchmark, based on a nonlinear model predictive control.
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Elsherbiny, Hanaa, Mohamed Kamal Ahmed, and Mahmoud Elwany. "Comparative Evaluation for Torque Control Strategies of Interior Permanent Magnet Synchronous Motor for Electric Vehicles." Periodica Polytechnica Electrical Engineering and Computer Science 65, no. 3 (July 6, 2021): 244–61. http://dx.doi.org/10.3311/ppee.16672.
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This paper presents a detailed analysis and comparative investigation for the torque control techniques of interior permanent magnet synchronous motor (IPMSM) for electric vehicles (EVs). The study involves the field-oriented control (FOC), direct torque control (DTC), and model predictive direct torque control (MPDTC) techniques. The control aims to achieve vehicle requirements that involve maximum torque per ampere (MTPA), minimum torque ripples, maximum efficiency, fast dynamics, and wide speed range. The MTPA is achieved by the direct calculation of reference flux-linkage as a function of commanded torque. The calculation of reference flux-linkage is done online by the solution of a quartic equation. Therefore, it is a more practical solution compared to look-up table methods that depend on machine parameters and require extensive offline calculations in advance. For realistic results, the IPMSM model is built considering iron losses. Besides, the IGBTs and diodes losses (conduction and switching losses) in power inverter are modeled and calculated to estimate properly total system efficiency. In addition, a bidirectional dc-dc boost converter is connected to the battery to improve the overall drive performance and achieve higher efficiency values. Also, instead of the conventional PI controller which suffers from parameter variation, the control scheme includes an adaptive fuzzy logic controller (FLC) to provide better speed tracking performance. It also provides a better robustness against disturbance and uncertainties. Finally, a series of simulation results with detailed analysis are executed for a 60 kW IPMSM. The electric vehicle (EV) parameters are equivalent to Nissan Leaf 2018 electric car.
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Xu, Qiwei, Chuan Zhou, Hong Huang, and Xuefeng Zhang. "Research on the Coordinated Control of Regenerative Braking System and ABS in Hybrid Electric Vehicle Based on Composite Structure Motor." Electronics 10, no. 3 (January 20, 2021): 223. http://dx.doi.org/10.3390/electronics10030223.
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An antilock braking system (ABS) can ensure that the wheels are not locked during the braking process which is an important system to ensure the safety of braking. Regenerative braking is also a crucial system for hybrid vehicles and helps to improve the cruising range of the car. As such, the coordinated control of a braking system and an ABS is an important research direction. This paper researches the coordinated control of the regenerative braking system and the ABS in the hybrid vehicle based on the composite structure motor (CSM-HEV). Firstly, two new braking modes which are engine-motor coordinated braking (EMCB) and dual-motor braking (DMB) are proposed and the coordinated control model of regenerative braking and ABS is established. Then, for the purpose of optimal operating efficiency and guaranteeing the vehicle brake slip rate, a braking force distribution strategy based on predictive control algorithm is proposed. Finally, the Simulink model is established to simulate the control strategy. Results show that the slip rate can well track the target and ensure the efficient operation of the system. Compared with the normal braking mode, the braking energy recovery rate of EMCB is similar, but it can reduce the fuel loss of the engine during the braking process by 30.1%, DMB can improve the braking energy recovery efficiency by 16.78%, and the response time to track target slip is increased by 12 ms.
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Conradi, Peter. "Range Prediction for Electric Vehicles." ATZelektronik worldwide 7, no. 3 (June 2012): 16–21. http://dx.doi.org/10.1365/s38314-012-0089-y.
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Conradi, Peter. "Range Prediction for Electric Vehicles." ATZautotechnology 12, no. 3 (June 2012): 54–59. http://dx.doi.org/10.1365/s35595-012-0122-z.
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Muslim, Supari, Tri Wrahatnolo, Sri Handayani, Erina Rahmadyanti, Nita Kusumawati, and Achmad Imam Agung. "Development of Electrical Car Learning Media as A Future Alternative Car." JETL (Journal of Education, Teaching and Learning) 5, no. 1 (March 31, 2020): 199. http://dx.doi.org/10.26737/jetl.v5i1.1822.
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This research aims to: (1) develop Electric Car Learning Media through research and development (R&D) ADDIE Model (Analysis, Design, Development, Implementation, and Evaluation); (2) knowing the level of feasibility of learning media for electric cars (LMEC) in a learning perspective; and (3) to determine the effectiveness of LMEC in the learning process. The study found that: (1) based on the validator's assessment, that the LMEC that had been developed was very suitable for use in learning Electric Cars; (2) based on student assessment, that LMEC is very suitable for use in learning Electric Cars in the Department of Electrical Engineering, State University of Surabaya; and (3) LMEC is very effective, proven as many as 24 (77.41%) of students get a score of learning outcomes in the range 71-100, with good and excellent categories.
Dissertations / Theses on the topic "Electric car range prediction"
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Roebuck, C. A. "Testing and frequency response analysis of an electric vehicle traction drive." Thesis, Coventry University, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.384599.
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Kammerer, Sven Daniel. "Development and evaluation of a range anxiety-reducing business model for connected full electric vehicles." reponame:Repositório Institucional do FGV, 2012. http://hdl.handle.net/10438/10258.
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This thesis develops and evaluates a business model for connected full electric vehicles (FEV) for the European market. Despite a promoting political environment, various barriers have thus far prevented the FEV from becoming a mass-market vehicle. Besides cost, the most noteworthy of these barriers is represented by range anxiety, a product of FEVs’ limited range, lacking availability of charging infrastructure, and long recharging times. Connected FEVs, which maintain a constant connection to the surrounding infrastructure, appear to be a promising element to overcome drivers’ range anxiety. Yet their successful application requires a well functioning FEV ecosystem which can only be created through the collaboration of various stakeholders such as original equipment manufacturers (OEM), first tier suppliers (FTS), charging infrastructure and service providers (CISP), utilities, communication enablers, and governments. This thesis explores and evaluates how a business model, jointly created by these stakeholders, could look like, i.e. how stakeholders could collaborate in the design of products, services, infrastructure, and advanced mobility management, to meet drivers with a sensible value proposition that is at least equivalent to that of internal combustion engine (ICE) cars. It suggests that this value proposition will be an end-2-end package provided by CISPs or OEMs that comprises mobility packages (incl. pay per mile plans, battery leasing, charging and battery swapping (BS) infrastructure) and FEVs equipped with an on-board unit (OBU) combined with additional services targeted at range anxiety reduction. From a theoretical point of view the thesis answers the question which business model framework is suitable for the development of a holistic, i.e. all stakeholder-comprising business model for connected FEVs and defines such a business model. In doing so the thesis provides the first comprehensive business model related research findings on connected FEVs, as prior works focused on the much less complex scenario featuring only 'offline' FEVs.
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Lamprecht, Andreas. "Energieprädiktion und Reichweitendarstellung durch Navigationsdaten im Kraftfahrzeug." Doctoral thesis, Universitätsbibliothek Chemnitz, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-213218.
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Im Zuge der immer größer werdenden Knappheit fossiler Ressourcen und des damit verbundenen Anstiegs des Rohölpreises ergibt sich ein Trend hin zur Elektromobilität. In den nächsten Jahren werden jedoch nur Elektrofahrzeuge mit deutlich eingeschränkter maximaler Reichweite im Vergleich zu Benzin- oder Dieselfahrzeugen produziert werden können. Um den täglichen Umgang des Kunden mit einem Elektrofahrzeug trotzdem möglichst reibungslos zu ermöglichen, wurde im Rahmen dieser Arbeit eine neuartige Anzeige der verbleibenden Reichweite auf der Navigationskarte entwickelt. Nach detaillierter Analyse vorhandener Ansätze wurde je ein empirisches und ein modellbasiertes Verfahren ausgearbeitet. Die Ansätze wurden systematisch verglichen und zu einem komplett neuartigen, hybriden Ansatz kombiniert. Die auftretenden Verbräuche des Fahrzeugs werden im Kundenbetrieb erfasst, je nach Fahrsituation klassifiziert und für eine Extrapolation in der Zukunft verwendet. Die entwickelte Methodik zur Untersuchung der erreichbaren Genauigkeit ergab ein erzielbares Fehlermaß von durchschnittlich unter 10%Due to the prospect of a worldwide shortage of fossil fuels and the correlated increase of prices for crude-oil, a global trend to invest in electric mobility has started. During the next couple of years, electric vehicles will still have restrictions on the maximum distance that can be driven before having the need to recharge the battery. The potential costumers face the so-called „range-anxiety“, the fear to be stranded prior to reaching the destination. In order to provide a safe and easy way of operating such a vehicle, the work conducted in the course of this doctoral thesis led to a new way of displaying the remaining range of the vehicle on a navigation map. After detailed analysis of the state of the art, an empirical- and a model-based solution for calculating the remaining range were developed utilizing predictive map-data from a roadnetwork. After a systematical optimization of the developed solutions, an embedded prototype was developed which captured the driving situation of the vehicle together with the corresponding energy-consumption in order to provide a context-aware interpolation of the remaining range, depending on where the costumer would drive next. A developed methodology of objectively determining the error produced by the system resulted in a mean-deviation of 10% of absolute value
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Hegde, Bharatkumar. "Look-Ahead Energy Management Strategies for Hybrid Vehicles." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu153199304661774.
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Lamprecht, Andreas. "Energieprädiktion und Reichweitendarstellung durch Navigationsdaten im Kraftfahrzeug: Energieprädiktion und Reichweitendarstellung durch Navigationsdaten im Kraftfahrzeug." Doctoral thesis, 2015. https://monarch.qucosa.de/id/qucosa%3A20591.
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Im Zuge der immer größer werdenden Knappheit fossiler Ressourcen und des damit verbundenen Anstiegs des Rohölpreises ergibt sich ein Trend hin zur Elektromobilität. In den nächsten Jahren werden jedoch nur Elektrofahrzeuge mit deutlich eingeschränkter maximaler Reichweite im Vergleich zu Benzin- oder Dieselfahrzeugen produziert werden können. Um den täglichen Umgang des Kunden mit einem Elektrofahrzeug trotzdem möglichst reibungslos zu ermöglichen, wurde im Rahmen dieser Arbeit eine neuartige Anzeige der verbleibenden Reichweite auf der Navigationskarte entwickelt. Nach detaillierter Analyse vorhandener Ansätze wurde je ein empirisches und ein modellbasiertes Verfahren ausgearbeitet. Die Ansätze wurden systematisch verglichen und zu einem komplett neuartigen, hybriden Ansatz kombiniert. Die auftretenden Verbräuche des Fahrzeugs werden im Kundenbetrieb erfasst, je nach Fahrsituation klassifiziert und für eine Extrapolation in der Zukunft verwendet. Die entwickelte Methodik zur Untersuchung der erreichbaren Genauigkeit ergab ein erzielbares Fehlermaß von durchschnittlich unter 10%.Due to the prospect of a worldwide shortage of fossil fuels and the correlated increase of prices for crude-oil, a global trend to invest in electric mobility has started. During the next couple of years, electric vehicles will still have restrictions on the maximum distance that can be driven before having the need to recharge the battery. The potential costumers face the so-called „range-anxiety“, the fear to be stranded prior to reaching the destination. In order to provide a safe and easy way of operating such a vehicle, the work conducted in the course of this doctoral thesis led to a new way of displaying the remaining range of the vehicle on a navigation map. After detailed analysis of the state of the art, an empirical- and a model-based solution for calculating the remaining range were developed utilizing predictive map-data from a roadnetwork. After a systematical optimization of the developed solutions, an embedded prototype was developed which captured the driving situation of the vehicle together with the corresponding energy-consumption in order to provide a context-aware interpolation of the remaining range, depending on where the costumer would drive next. A developed methodology of objectively determining the error produced by the system resulted in a mean-deviation of 10% of absolute value.
Books on the topic "Electric car range prediction"
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Riley, Richard D., Danielle van der Windt, Peter Croft, and Karel G. M. Moons, eds. Prognosis Research in Health Care. Oxford University Press, 2019. http://dx.doi.org/10.1093/med/9780198796619.001.0001.
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What is going to happen to me, doctor?’ ‘What outcomes am I likely to experience?’ ‘Will this treatment work for me?’ Prognosis—forecasting the future—has always been a part of medical practice and caring for the sick. In modern healthcare it now has a new importance, with large financial investments being made to personalize clinical decisions and tailor treatment strategies to improve individual health outcomes based on prognostic information. Prognosis research—the study of future outcomes in people with a particular health condition—provides the critical evidence for obtaining, evaluating, and implementing prognostic information within modern healthcare. This new book, written and edited by experts in the field, including clinicians, epidemiologists, statisticians, and other healthcare professionals, is a comprehensive and unified account of prognosis research in the broadest sense. It explains the concepts behind prognosis in medical practice and prognosis research, and provides a practical foundation for those developing, conducting, interpreting, synthesizing, and appraising prognosis studies. It recommends a framework of four basic prognosis research types, pioneered by the PROGRESS group, and provides explicit guidance on the conduct, analysis, and reporting of prognosis studies for each type. Key topics are overall prognosis in clinically relevant populations; prognostic factors associated with changes in prognosis across individuals; prognostic models for individual outcome risk prediction; and predictors of treatment effects. Examples are given of the impact of prognosis research across a broad range of healthcare topics, and the book also signals the latest developments in prognosis research, including systematic reviews and meta-analysis of prognosis studies, and the use of electronic health records and machine learning in prognosis research.
Book chapters on the topic "Electric car range prediction"
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Conradi, Peter, Philipp Bouteiller, and Sascha Hanßen. "Dynamic Cruising Range Prediction for Electric Vehicles." In Advanced Microsystems for Automotive Applications 2011, 269–77. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21381-6_26.
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Kriescher, Michael, Sebastian Scheibe, and Tilo Maag. "Development of the Safe Light Regional Vehicle (SLRV): A Lightweight Vehicle Concept with a Fuel Cell Drivetrain." In Small Electric Vehicles, 179–89. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-65843-4_14.
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AbstractThe safe light regional vehicle (SLRV) concept was developed within the DLR project next-generation car (NGC). NGC SLRV addresses the safety concern of typical L7e vehicles. The SLRV is therefore specifically designed to demonstrate significant improvements to the passive safety of small vehicles. Another important goal of the NGC SLRV concept is to offer solutions to some of the main challenges of electric vehicles: to provide an adequate range and at the same time a reasonable price of the vehicle. In order to address these challenges a major goal of the concept is to minimize the driving resistance of the vehicle, by use of lightweight sandwich structures. A fuel cell drivetrain also helps to keep the overall size and weight of the vehicle low, while still providing sufficient range.
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Griesemann, J. C., D. Corgier, P. Achard, R. Metkemeyer, B. Marcenaro, F. Federici, P. Ekdunge, et al. "Hydrogen Air Fuel Cell Powered Passenger Car Fever — Fuel Cell Electric Vehicle for Efficiency and Range." In Hydrogen Power: Theoretical and Engineering Solutions, 1–11. Dordrecht: Springer Netherlands, 1998. http://dx.doi.org/10.1007/978-94-015-9054-9_1.
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Kumar, Abhishek. "40-GHz Inductor Less VCO." In AI Techniques for Reliability Prediction for Electronic Components, 288–98. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-1464-1.ch016.
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In a modern communication system, voltage-controlled oscillator (VCO) acts as a basic building block for frequency generation. VCO with LC tank is preferred with passive inductor and varactor in radio frequency. Practical tuning range of VCO is low and unsuitable for wideband application. Switched capacitor and inductor can widen but at cost of chip area and complex system architecture. To overcome it, an equivalent circuit of the inductor is created. In this work, inductor-less VCO is implemented with CMOS 90nm technology that has center frequency 40GHz and frequency tuning range 37.7GHz to 41.9GHz.
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Carlos de Carvalho Pereira, José. "Energy Harvesting Prediction from Piezoelectric Materials with a Dynamic System Model." In Piezoelectric Actuators - Principles, Design, Experiments and Applications [Working Title]. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.96626.
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Piezoelectric vibration energy harvesting has been investigated for different applications due to the amount of wasted vibration from dynamic systems. In the case of piezoelectric materials, this energy lost to the environment can be recovered through the vibration of energy harvesting devices, which convert mechanical vibration into useful electrical energy. In this context, this chapter aims to present the mechanical/electrical coupling on a simple dynamic system model in which a linear piezoelectric material model is incorporated. For this purpose, a mechanical/electrical element of a piezoelectric disk is developed and integrated into a lumped mass, viscous damping, and spring assembling, similar to a quarter car suspension system. Equations of motion for this dynamic system in the time domain can be solved using the finite element method. The recovered electric power and energy density for PZT (Lead Zirconate Titanate) from the wasted vibration can be predicted considering that the road roughness is introduced as an input mode.
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"Prologue." In Prognosis Research in Health Care, edited by Richard D. Riley, Danielle A. van der Windt, Peter Croft, and Karel GM Moons, 1–8. Oxford University Press, 2019. http://dx.doi.org/10.1093/med/9780198796619.003.0001.
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‘What is going to happen to me, doctor?’ ‘What outcomes am I likely to experience?’ ‘Will this treatment work for me?’ Prognosis—forecasting the future—has always been a part of medical practice and caring for the sick. In modern healthcare it now has a new importance, with large financial investments being made to personalize clinical decisions and tailor treatment strategies to improve individual health outcomes based on prognostic information. Prognosis research—the study of future outcomes in people with a particular health condition—provides the critical evidence for obtaining, evaluating, and implementing prognostic information within modern healthcare. This new book, written and edited by experts in the field, including clinicians, epidemiologists, statisticians, and other healthcare professionals, is a comprehensive and unified account of prognosis research in the broadest sense. It explains the concepts behind prognosis in medical practice and prognosis research, and provides a practical foundation for those developing, conducting, interpreting, synthesizing, and appraising prognosis studies. It recommends a framework of four basic prognosis research types, pioneered by the PROGRESS group, and provides explicit guidance on the conduct, analysis, and reporting of prognosis studies for each type. Key topics are overall prognosis in clinically relevant populations; prognostic factors associated with changes in prognosis across individuals; prognostic models for individual outcome risk prediction; and predictors of treatment effects. Examples are given of the impact of prognosis research across a broad range of healthcare topics, and the book also signals the latest developments in prognosis research, including systematic reviews and meta-analysis of prognosis studies, and the use of electronic health records and machine learning in prognosis research.
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Pierre, Samuel. "Security Issues Concerning Mobile Commerce." In Mobile Computing, 2653–59. IGI Global, 2009. http://dx.doi.org/10.4018/978-1-60566-054-7.ch201.
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Electronic commerce or e-commerce can be briefly defined as a financial transaction or commercial information between two parties based on data transmitted over communication networks (Soriano & Ponce, 2002). It relies upon users’ interventions to initiate a transaction and select the main steps of the process. Users’ actions stem from a succession of virtual decisions. Indeed, when shopping with a virtual catalog, customers can select products which meet their needs, tastes, and respect their price range. Such decisions consistently require the users’ input, thus costing them both time and money. These costs are even more exorbitant when a search is launched for an order that includes a variety of products from different sources which have different characteristics (price range, delivery dates, etc.). When transactions involve users who are moving or take place over mobile networks, this is referred to as mobile electronic commerce, a specific type of e-commerce. Mobile electronic commerce (or m-commerce) refers to an ability to carry out wireless commercial transactions using mobile applications within mobile devices, such as mobile phones and personal digital assistants (PDAs). It is generally defined as the set of transactions or processes which can be carried out over a wireless mobile network. According to this definition, m-commerce constitutes a subset of all electronic commercial transactions (electronic commerce or e-commerce) from business to consumer (B2C) or business to business (B2B). Thus, short personal messages such as those from SMS (short messaging system) sent between two individuals do not fall into the category of m-commerce, whereas messages from a service provider to a salesperson or a consumer, or vice versa, do fit this very definition. M-commerce appears as an emerging manifestation of Internet electronic commerce which meshes together concepts such as the Internet, mobile computing, and wireless telecommunications in order to provide an array of sophisticated services (m-services) to mobile users (Varshney, Vetter, & Kalakota, 2000; Veijalainen, Terziyan, & Tirri, 2003). E-commerce includes an initial step where consumers search for a product they wish to purchase by virtually visiting several merchants. Once the product is found, negotiations can take place between the customer and the merchant (electronic negotiation or e-negotiation) (Paurobally, Turner, & Jennings, 2003). If an agreement is reached, the next step is the payment phase. At each step of the process, some problems arise, such as transaction security, confidence in the payment protocol, bandwidth limitations, quality of service, shipping delays, and so forth (Younas, Chao, & Anane, 2003; Zhang, Yuan, & Archer, 2002). The peak withdrawal periods have always presented a major challenge for certain types of distributed applications. The advent of m-commerce further highlights this problem. Indeed, in spite of rather optimistic predictions, m-commerce is plagued by several handicaps which hinder its commercial development, security being the main one.
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Mado, Ismit. "Electric Load Forecasting an Application of Cluster Models Based on Double Seasonal Pattern Time Series Analysis." In Forecasting in Mathematics - Recent Advances, New Perspectives and Applications [Working Title]. IntechOpen, 2020. http://dx.doi.org/10.5772/intechopen.93493.
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Electricity consumption always changes according to need. This pattern deserves serious attention. Where the electric power generation must be balanced with the demand for electric power on the load side. It is necessary to predict and classify loads to maintain reliable power generation stability. This research proposes a method of forecasting electric loads with double seasonal patterns and classifies electric loads as a cluster group. Double seasonal pattern forecasting fits perfectly with fluctuating loads. Meanwhile, the load cluster pattern is intended to classify seasonal trends in a certain period. The first objective of this research is to propose DSARIMA to predict electric load. Furthermore, the results of the load prediction are used as electrical load clustering data through a descriptive analytical approach. The best model DSARIMA forecasting is ([1, 2, 5, 6, 7, 11, 16, 18, 35, 46], 1, [1, 3, 13, 21, 27, 46]) (1, 1, 1)48 (0, 0, 1)336 with a MAPE of 1.56 percent. The cluster pattern consists of four groups with a range of intervals between the minimum and maximum data values divided by the quartile. The presentation of this research data is based on data on the consumption of electricity loads every half hour at the Generating Unit, the National Electricity Company in Gresik City, Indonesia.
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Kim, Steven. "Attributes of Creativity." In Essence of Creativity. Oxford University Press, 1990. http://dx.doi.org/10.1093/oso/9780195060171.003.0005.
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As discussed in the previous chapter, the term problem is used in a general sense to refer to any task that requires resolution. These tasks may range from solving a mathematical problem to formulating a business strategy, from generating an engineering prototype to conceiving an artistic design. A problem is called easy if the identification of an acceptable solution is straightforward. The label of easiness refers to the generation of the solution rather than its implementation. According to this view, finding the average value of a thousand numbers is as easy as calculating the mean of two values, since the procedure is equally straightforward. In contrast, a hard or difficult problem is one whose resolution is not readily discernable. A common source of difficulty lies in the fact that the ultimate objective is not known a priori. This situation is reminiscent of the fictional detective rummaging through a ransacked house. “What are you looking for?” asks his companion. “I don't know—but I'll know it when I find it!” In a more sedate context, the same situation applies to an investigator who wants to develop a science of manufacturing but cannot specify beforehand the nature of such a discipline. Manufacturing is one arena which until recently was regarded as a domain so complex that it would remain only an art rather than a science. A second and perhaps more prevalent difficulty in resolving a problem relates to the route rather than the destination: the desired objective may be known, but not its means of attainment. This situation occurs when an automotive engineer must design an electric car that can travel over 1000 kilometers between battery recharges. It also occurs when a federal committee must develop a policy to contain the outbreak of a new epidemic: it is not clear to what extent emphasis should be placed on public education, medical research, governmental regulation, or other mechanisms for prevention and redress. The resolution of such difficult problems requires a creative approach. In fact, we can summarize the preceding discussion in the following definitions.
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Crane, Hewitt, Edwin Kinderman, and Ripudaman Malhotra. "Our Energy Inheritance: Fossil Fuels." In A Cubic Mile of Oil. Oxford University Press, 2010. http://dx.doi.org/10.1093/oso/9780195325546.003.0014.
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The use of fossil fuels—petroleum, natural gas, and coal—is ubiquitous today and has made possible the advances of modern civilization. These fuels are capable of providing energy for a variety of applications—from very small to very large—and touch our lives in many ways. A small gas-fired heater uses about 50,000 Btu/hr (1 standard cubic foot [scf] of gas/min) and keeps our homes warm. A 200-horsepower gasoline engine in a family car consumes around 2 gal/hr of oil and can carry a load of five passengers a distance of 60 miles on a level highway. An 1,800-ton/hr cement plant consumes 900 MBtu/hr (about 0.9 million scf gas/hr) when in full operation and produces the building material widely used for constructing homes, offices, industries, roads, and bridges. A large, coal-fired electric power station (1,000 MW rating) requires between 300 and 500 tons of coal per hour and produces enough electricity to power half a million homes. The range of power that fossil fuels, particularly oil, can deliver is truly amazing: the same basic fuel that powers jet aircraft also powers children’s model aircraft engines. It is unlikely that aircraft will ever be powered by solar panels mounted on the wings or by on-board nuclear reactors. The importance of fossil fuels in our lives cannot be overemphasized. It took millions of years to accumulate them, and their potential exhaustion in just a few centuries should seriously concern all of us. In this chapter, we briefly review the circumstances that led to formation of our fossil fuels and then discuss how much of each of them is available. This discussion requires clarifying the special meanings ascribed to such terms as reserves and resources. For all three fuels, we look at the global distribution of our resources. We also present estimates of possible resource lifetimes under varying conditions of use and indicate the nominal equipment and infrastructure requirements for producing these inherited resources at a rate of 1 CMO/yr. As we shall see, our conventional reserves are somewhat limited, but our resource base is large, and unconventional oil and gas resources offer a substantially greater potential. Nonetheless, exploiting unconventional resources is certain to be more expensive and, in most cases, potentially more damaging to the environment.
Conference papers on the topic "Electric car range prediction"
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Liauw, Yuhanes D. S., Mehdi Roozegar, Ting Zou, Alexei Morozov, and Jorge Angeles. "Range Model of Electric Vehicles With Multi-Speed Transmissions." In ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/detc2018-85119.
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Range-prediction models of electric vehicles (EVs) are essential for vehicle designers because range is still a major problem in EVs. Most range models are only available for EVs with fixed gearing. However, recent developments in EVs incorporate multi-speed transmissions (MSTs). Furthermore, transmissions are modeled only with a constant efficiency in most EV range-prediction simulation results available in the literature. For this reason, a simple and accurate range model for EVs with MSTs is proposed in this paper. In order to predict the range of EVs with MSTs accurately, the transmission efficiency is estimated by means of the transmission mathematical model. The efficiency results are verified with a comprehensive model that has been validated experimentally. A case study pertaining to the GM EV1 with a two-speed novel modular transmission is provided. Moreover, simulation results under constant efficiency are included to show the advantages of the proposed model in range-prediction. Our simulation results show that a more accurate range-prediction can be obtained by means of the proposed model.
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Ryu, Keun, and Augustine Cavagnaro. "Predictions of Rotordynamic Performance for Electric Turbocompound." In ASME Turbo Expo 2012: Turbine Technical Conference and Exposition. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/gt2012-69114.
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An electric turbocompound (ETC) system for heavy duty diesel engines offers significant system level benefits, such as improved fuel efficiency and reduced NOx emissions with a lower CO2 footprint. Presently, a high speed switched reluctance type motor/generator is integrated into a turbocharger shaft between the turbine and compressor wheels. The motor assists rapid acceleration of the turbocharger shaft, thereby rendering faster transient response. At steady or over-boost operating conditions, the generator provides electric power which can be used directly or stored in an on-board storage device. ETCs operate at high rotational speeds and, if equipped with fluid film bearings, use pressurized engine oil to lubricate the bearings (journal and thrust). This paper presents comprehensive predictions of the linear and nonlinear shaft motions of an ETC supported on floating ring bearings. A rotor structural finite element model integrates the floating ring bearing model for prediction of the rotor-bearing system (RBS) linear and nonlinear forced responses under actual operating conditions. Predictions show a complex rotordynamic behavior of the RBS with large amplitude subsynchronous motions over a wide speed range. However, the subsynchronous whirl motions reach a limit cycle enabling continuous operation without system failure. Most importantly, stiffness of the lamination stack mounted on the shaft has a significant effect on the amplitude and frequency content of the shaft motion. The present analysis effectively aids to accelerate ETC prototype development with increased reliability and product troubleshooting.
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Gebhard, Lukas, Lukasz Golab, S. Keshav, and Hermann de Meer. "Range prediction for electric bicycles." In e-Energy'16: The Seventh International Conference on Future Energy Systems. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2934328.2934349.
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Schneider, Michael, Jens Dickhoff, Karsten Kusterer, and Wilfried Visser. "Life Cycle Analysis for a Powertrain in a Concept for Electric Power Generation in a Hybrid Electric Aircraft." In ASME Turbo Expo 2020: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/gt2020-15518.
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Abstract In the recent decades, civil aviation was growing 4.7% per annum. In order to reduce emissions promoting the global warming process, alternative propulsion systems are needed. Full-electric propulsion systems in aviation might have the potential for emission-free flights using renewable energy. However, several research efforts indicate electric propulsion only seems feasible for small aircraft. Especially due to the low energy density of batteries compared to fossil fuels. For this reason, hybrid propulsion systems came into focus, combining the benefits of all-electric and conventional propulsion system concepts. It is also considered as bridging technology, system test and basis for component development — and therewith paves the way towards CO2 free aviation. In the ‘HyFly’ project (supported by the German Luftfahrtforschungsprogramm LuFo V-3), the potential of a hybrid electric concept for a short/mid-range 19 PAX aircraft is assessed — not only on system but also on single component basis. In a recent study, the propulsion architecture and the operating mode of the gas turbine and the electric components have been defined [1]. In this paper, the advantages of the hybrid propulsion architecture and a qualitative assessment of component life are presented. Methods for life time prediction for the aircraft engine, the electric motor, the reluctance generator and the battery are discussed. The impact of turbine inlet temperature on life consumption is analyzed. The life cycle of the aircraft engine and the electric components including gradual component deterioration and consequent performance degradation is simulated by using an in-house gas turbine simulation tool (GTPsim). Therefore, various effects on electric propulsion system can be predicted for the entire drivetrain system in less than one hour.
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Koutsothanasis, George M., Anestis I. Kalfas, and Georgios Doulgeris. "Marine Gas Turbine Performance Model for More Electric Ships." In ASME 2011 Turbo Expo: Turbine Technical Conference and Exposition. ASMEDC, 2011. http://dx.doi.org/10.1115/gt2011-46101.
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This paper presents the benefits of the more electric vessels powered by hybrid engines and investigates the suitability of a particular prime-mover for a specific ship type using a simulation environment which can approach the actual operating conditions. The performance of a mega yacht (70m), powered by two 4.5MW recuperated gas turbines is examined in different voyage scenarios. The analysis is accomplished for a variety of weather and hull fouling conditions using a marine gas turbine performance software which is constituted by six modules based on analytical methods. In the present study, the marine simulation model is used to predict the fuel consumption and emission levels for various conditions of sea state, ambient and sea temperatures and hull fouling profiles. In addition, using the aforementioned parameters, the variation of engine and propeller efficiency can be estimated. Finally, the software is coupled to a creep life prediction tool, able to calculate the consumption of creep life of the high pressure turbine blading for the predefined missions. The results of the performance analysis show that a mega yacht powered by gas turbines can have comparable fuel consumption with the same vessel powered by high speed Diesel engines in the range of 10MW. In such Integrated Full Electric Propulsion (IFEP) environment the gas turbine provides a comprehensive candidate as a prime mover, mainly due to its compactness being highly valued in such application and its eco-friendly operation. The simulation of different voyage cases shows that cleaning the hull of the vessel, the fuel consumption reduces up to 16%. The benefit of the clean hull becomes even greater when adverse weather condition is considered. Additionally, the specific mega yacht when powered by two 4.2MW Diesel engines has a cruising speed of 15 knots with an average fuel consumption of 10.5 [tonne/day]. The same ship powered by two 4.5MW gas turbines has a cruising speed of 22 knots which means that a journey can be completed 31.8% faster, which reduces impressively the total steaming time. However the gas turbine powered yacht consumes 9 [tonne/day] more fuel. Considering the above, Gas Turbine looks to be the only solution which fulfills the next generation sophisticated high powered ship engine requirements.
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Ferreira, Joao C., Vitor Monteiro, and Joao L. Afonso. "Dynamic range prediction for an electric vehicle." In 2013 World Electric Vehicle Symposium and Exhibition (EVS27). IEEE, 2013. http://dx.doi.org/10.1109/evs.2013.6914832.
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Deepak, S., Aswathy Amarnath, Gopala Krishnan U., and Sreeja Kochuvila. "Survey on Range Prediction of Electric Vehicles." In 2019 Innovations in Power and Advanced Computing Technologies (i-PACT). IEEE, 2019. http://dx.doi.org/10.1109/i-pact44901.2019.8960179.
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Dowell, Peter G., Richard D. Burke, and Sam Akehurst. "Accuracy of Diesel Engine Combustion Metrics Over the Full Range of Engine Operating Conditions." In ASME 2018 Internal Combustion Engine Division Fall Technical Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/icef2018-9507.
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Measuring and analyzing combustion is a critical part of the development of high efficiency and low emitting engines. Faced with changes in legislation such as Real Driving Emissions and the fundamental change in the role of the combustion engine with the introduction of hybrid-electric powertrains, it is essential that combustion analysis can be conducted accurately across the full range of operating conditions. In this work, the sensitivity of five key combustion metrics is investigated with respect to eight necessary assumptions used for single zone Diesel Combustion analysis. The sensitivity was evaluated over the complete operating range of the engine using a combination of experimental and modelling techniques. This provides a holistic understanding of combustion measurement accuracy. For several metrics, it was found that the sensitivity at the mid speed/load condition was not representative of sensitivity across the full operating range, in particular at low speeds and loads. Peak heat release rate and indicated mean effective pressure were found to be most sensitive to the determination of top dead center (TDC) and the assumption of in-cylinder gas properties. An error of 0.5° in the location of TDC would cause on average a 4.2% error in peak heat release rate. The ratio of specific heats had a strong impact on peak heat release with an error of 8% for using the assumption of a constant value. A novel method for determining TDC was proposed which combined a filling and emptying simulation with measured data obtained experimentally from an advanced engine test rig with external boosting system. This approach improved the robustness of the prediction of TDC which will allow engineers to measure accurate combustion data in operating conditions representative of in-service applications.
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Small, Evan, Sadegh M. Sadeghipour, and Mehdi Asheghi. "Numerical Modeling of Heat Transfer and Phase Transition in Programming the Ovonic Unified Memory Cells." In ASME 2005 Pacific Rim Technical Conference and Exhibition on Integration and Packaging of MEMS, NEMS, and Electronic Systems collocated with the ASME 2005 Heat Transfer Summer Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/ipack2005-73188.
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An Ovonic Unified Memory (OUM) cell is a semiconductor device that stores data by a thermally induced phase transition between polycrystalline (set) and amorphous (reset) states in a thin film of chalcogenide alloy. The small volume of active media acts as a programmable resistor switching between a high (amorphous) and low (crystalline) resistance state. The change in the film resistivity (>40X dynamic range) caused by this rapid, reversible structural change is measured to detect the state of the cell (set or reset) for read out. OUM can benefit from a simulator capable of predicting the electrical, thermal, and crystallization behavior for design and optimization, particularly at the present stage of the development. This paper reports on the efforts being made to prepare such a numerical simulator, using an existing finite element computer code as the source for thermal and electrical modeling, and a custom crystallization code for phase prediction. Heat generation in the device is by Joule heating and is achieved by passage of the electric current, which is obtained from the electrical simulation. This result appears in the heat source term of the heat transfer equation that is solved for thermal modeling. As the first attempt the Ohmic current-voltage relation was implemented successfully to simulate set and reset in a two dimensional model of OUM. Solution of the drift-diffusion equation is now underway to capture the semiconductor behavior of the I-V curve. A good progress is made however, still more works needs to be done to fully implement the drift diffusion equation.
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Higley, Megan, Mustafa Hadj-Nacer, and Miles Greiner. "Temperature Prediction of a TN-32 Used Nuclear Fuel Canister Subjected to Vacuum Drying Conditions." In ASME 2018 Pressure Vessels and Piping Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/pvp2018-84844.
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In this work, a geometrically-accurate two-dimensional (2D) computational fluid dynamic (CFD) model of a used nuclear fuel cask, that can contain up to 32 pressurized water reactor (PWR) used nuclear fuel (UNF) assemblies, is constructed. This model is similar to the TN-32 cask employed in the ongoing high-burnup (HBU) Spent Fuel Data Project lead by the Electric Power Research Institute (EPRI). This model is used to predict the peak cladding temperature under vacuum drying conditions. Due to the symmetry of the cask, only one-eighth of the cross-section is modeled. Steady-state simulations that include the temperature-jump boundary conditions at the gas-solid interfaces are performed for different heat generation rates in the fuel regions and a range of dry helium pressures, from ∼105 to 100 Pa. These simulations include conduction within solid-gas regions and surface-to-surface radiation across all gas regions. The peak cladding temperatures are reported for various heat generation rates and rarefaction conditions, along with the maximum allowable heat generation that brings the cladding temperatures to the radial hydride formation limit. The results showed that the decrease of helium pressure significantly increased the temperature of the cladding material compared to the atmospheric pressure condition.
Reports on the topic "Electric car range prediction"
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Muelaner, Jody Emlyn. Unsettled Issues in Electrical Demand for Automotive Electrification Pathways. SAE International, January 2021. http://dx.doi.org/10.4271/epr2021004.
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With the current state of automotive electrification, predicting which electrification pathway is likely to be the most economical over a 10- to 30-year outlook is wrought with uncertainty. The development of a range of technologies should continue, including statically charged battery electric vehicles (BEVs), fuel cell electric vehicles (FCEVs), plug-in hybrid electric vehicles (PHEVs), and EVs designed for a combination of plug-in and electric road system (ERS) supply. The most significant uncertainties are for the costs related to hydrogen supply, electrical supply, and battery life. This greatly is dependent on electrolyzers, fuel-cell costs, life spans and efficiencies, distribution and storage, and the price of renewable electricity. Green hydrogen will also be required as an industrial feedstock for difficult-to-decarbonize areas such as aviation and steel production, and for seasonal energy buffering in the grid. For ERSs, it is critical to understand how battery life will be affected by frequent cycling and the extent to which battery technology from hybrid vehicles can be applied. Unsettled Issues in Electrical Demand for Automotive Electrification Pathways dives into the most critical issues the mobility industry is facing.