156 research outputs found
Metrology support for enhanced energy efficiency in DC transportation systems
No full textThis paper describes a new EU-co-funded project on metrology support for enhanced energy efficiency in DC transportation systems (e-TRENY). The project involves 5 national metrology institutes, 3 universities, 1 metro operator, and 1 consulting group. Research focuses on the following topics: i) new calibration facilities for DC transducers (up to 3 kV, 1 kA) under dynamic conditions, ii) accurate on-site losses of the converter group (power transformer - AC/DC bidirectional converter, DC/DC converter) operating in DC substations, iii) energy saving performance of transportation systems with non-conventional DC substations.</p
Member, IAENG, Prasanth G Rao, Abhilash VR, P. Deepa Shenoy, Venugopal KR and LM Patnaik. A Data Mining Approach for Data Generation and Analysis for Digital Forensic Application
Full text linkWith the rapid advancements in information and
communication technology in the world, crimes committed are
becoming technically intensive. When crimes committed use
digital devices, forensic examiners have to adopt practical
frameworks and methods to recover data for analysis which can
pose as evidence. Data Generation, Data Warehousing and Data
Mining, are the three essential features involved in the
investigation process. This paper proposes a unique way of
generating, storing and analyzing data, retrieved from digital
devices which pose as evidence in forensic analysis. A statistical
approach is used in validating the reliability of the
pre-processed data. This work proposes a practical framework
for digital forensics on flash drive
Future of Electric Vehicle Charging
No full textCharging infrastructure for electric vehicles (EV) will be the key factor for ensuring a smooth transition to e-mobility. This paper focuses on five technologies that will play a fundamental role in this regard: smart charging, vehicle-to-grid (V2G), charging of EVs from photovoltaic panels (PV), contactless charging and on-road charging of EVs. Smart charging of EVs is expected to enable larger penetration of EVs and renewable energy, lower the charging cost and offer better utilization of the grid infrastructure. Bidirectional EV chargers will pave the way for V2G technology where the EV can be used for energy arbitrage and demand-side management. Solar charging of EV will result in sustainable transportation and use of the EV battery as PV storage. On the other hand, stationary contactless charging and on-road inductive charging of EV will remove the necessity for any cables, eliminate range anxiety issues and pave the way for automated driving. The electromagnetic and power converter design for contactless power transfer systems for future highways is reviewed in this paper.Accepted Author ManuscriptDC systems, Energy conversion & Storag
Impact of Discharge Current Profiles on Li-ion Battery Pack Degradation
Full text linkIncreasing the life cycle of battery packs is one of the most valuable endeavors in modern Li-ion battery technologies, especially for light electric vehicles whose material costs are often significantly determined by the costs of the battery pack. The main aim of the present study is to help manufactureres of LEV's to circumvent the type of discharge profiles that substantially degrade the LEV's battery pack. To this end, this paper describes a measurement setup in which various discharge patterns from light electric vehicles, acquired during actual use of the vehicles, are simulated in a lab environment in order to assess their influence on the degradation of the Li-ion battery packs. The results of these measurements can be used to optimize discharge profiles and improve battery management systems with the aim to extend the Li-ion battery life time
Green energy based inductive Self-Healing highways of the future
No full textThis paper deals with a green energy highway in the Netherlands. Here, the development of electric mobility and self-driving cars is introduced. The ideas of wireless power integration with green energy technologies - solar and wind is considered. In case of wind energy, conventional turbines and bladeless vortex are considered as options. Solaroads along the emergency lanes are also investigated. A Dutch highway A12 is considered as a case study and sizing of these energy sources for electric mobility is considered. A grid power demand profile is considered and number of EVs that can be charged hourly is calculated. A preliminary investigation of the combination of IPT and Self-Healing roads is considered in this study.Accepted Author ManuscriptDC systems, Energy conversion & StorageApplied Ergonomics and Desig
A Review of Lithium-ion Batteries Diagnostics and Prognostics Challenges
Full text linkBattery technology besides its importance and exceptional characteristics is not still a mature technology and there is a real need for research and innovation in their lifetime, charging rate, second use, etc. The dependency of our daily lives on batteries is irrefutable and they are becoming growingly ubiquitous in our daily lives. Battery performance is degrades with battery aging and therefore a battery diagnostics and prognostics tool to enhance the effective use of the battery system is necessary. This paper deals with some challenges that remain unsolved in battery diagnostic and prognostic techniques. A review of recent battery diagnostic approaches for battery state estimation is performed and their relative advantages and disadvantages are emphasized while comparing the available methods to predict the battery end of life (EOL) or remaining useful life (RUL) as a key tool in battery prognostic
Economic Viability Study of an On-Road Wireless Charging System with a Generic Driving Range Estimation Method
No full textThe economic viability of on-road wireless charging of electric vehicles (EVs) strongly depends on the choice of the inductive power transfer (IPT) system configuration (static or dynamic charging), charging power level and the percentage of road coverage of dynamic charging. In this paper, a case study is carried out to determine the expected investment costs involved in installing the on-road charging infrastructure for an electric bus fleet. Firstly, a generic methodology is described to determine the driving range of any EV (including electric buses) with any gross mass and frontal area. A dynamic power consumption model is developed for the EV, taking into account the rolling friction, acceleration, deceleration, aerodynamic drag, regenerative braking and Li-ion battery behavior. Based on the simulation results, the linear dependence of the battery state of charge (SoC) on the distance traveled is proven. Further, the impact of different IPT system parameters on driving range is incorporated. Economic implications of a combination of different IPT system parameters are explored for achieving the required driving range of 400 km, and the cost optimized solution is presented for the case study of an electric bus fleet. It is shown that the choice of charging power level and road coverage are interrelated in the economic context. The economic viability of reducing the capacity of the on-board battery as a trade-off between higher transport efficiency and larger on-road charging infrastructure is presented. Finally, important considerations, like the number of average running buses, scheduled stoppage time and on-board battery size, that make on-road charging an attractive option are explored. The cost break-up of various system components of the on-road charging scheme is estimated, and the final project cost and parameters are summarized. The specific cost of the wireless on-road charging system is found to be more expensive than the conventional trolley system at this point in time. With decreasing battery costs and a higher number of running buses, a more economically-viable system can be realized.Electrical Sustainable EnergyElectrical Engineering, Mathematics and Computer Scienc
Pilot based frameworks for weather research forecasting
No full textThe Weather Research Forecasting (WRF) domain consists of complex workflows that demand the use of Distributed Computing Infrastructure (DCI). Weather forecasting requires that weather researchers use different set of initial conditions and one or a combination of physics models on the same set of input data. For these type of simulations an ensemble based computing approach becomes imperative. Most DCIs have local job-schedulers that have no smart way of dealing with the execution of an ensemble type of computational problem as the job-schedulers are built to cater to the bare essentials of resource allocation. This means the weather scientists have to submit multiple jobs to the job-scheduler. In this dissertation we use Pilot-Job based tools to decouple work-load submission and resource allocation therefore streamlining the complex workflows in Weather Research and Forecasting domain and reduce their overall time to completion. We also achieve location independent job execution, data movement, placement and processing. Next, we create the necessary enablers to run an ensemble of tasks bearing the capability to run on multiple heterogeneous distributed computing resources there by creating the opportunity to minimize the overall time consumed in running the models. Our experiments show that the tools developed exhibit very good, strong and weak scaling characteristics. These results bear the potential to change the way weather researchers are submitting traditional WRF jobs to the DCIs by giving them a powerful weapon in their arsenal that can exploit the combined power of various heterogeneous DCIs that could otherwise be difficult to harness owing to interoperability issues.M.S.Includes bibliographical referencesby Dinesh Prasanth Ganapath
Data-driven spatial modeling of historic and future land change at global scale
Full text linkAssessing the historic and future impacts of land-use and land-cover change (LULCC) on climate requires spatially and temporally explicit data sets on LULCC spanning several decades to centuries, because climate change is a long-term problem. Though remote sensing data provides a globally consistent picture of land cover, these data are only available from the past four decades. Therefore, existing LULCC reconstructions are modeled estimates that combine remote sensing data with relatively coarser-resolution inventory statistics that covers longer historical period. The uncertainties in modeling assumptions, and limited availability and inconsistencies across inventory datasets among other reasons introduce uncertainties in LULCC reconstructions. These uncertainties not only limit our ability to model future LULCC, but also translate as uncertainties in both historic and future environmental assessments.
The objectives of my PhD work are as follows: (1) systematically investigate the causes of uncertainties in existing historical LULCC datasets, (2) test the sensitivity of LULCC quantification uncertainty in estimating CO2 emissions from LULCC (historic and future) using a process-based land-surface model, the Integrated Science Assessment Model (ISAM), (3) compare the relative uncertainties from various drivers (e.g. LULCC datasets, model processes e.g. nitrogen cycle, environmental factors such as climate) in estimating historic and future LULCC emissions, and (4) explore statistical techniques to model future LULCC that takes into account the uncertainties in quantifying the spatial and temporal patterns of LULCC, and (5) as a case-study, identify a key regional hotspot of historic LULCC quantification uncertainty (here, India), and reduce uncertainty through improved understanding of the dynamics and drivers of land change in the case-study region. I address the above goals by integrating land-surface modeling (ISAM), remote sensing and GIS, data collected through ground transects, and geospatial data on socioeconomics.
ISAM simulations show that the estimated net global emissions from LULCC (mean and range) across three different historical LULCC reconstructions are 1.88 (1.7 to 2.21) GtC/yr for the 1980’s, 1.66 (1.48 to 1.83) GtC/yr for the 1990's, and 1.44 (1.22 to 1.65) for the 2000's. The estimates are higher than other published estimates that range from 0.80 to 1.5 GtC/yr for the 1990’s and 1.1 GtC/yr for the 2000’s. These results are higher than other published estimates because they include the effects of nitrogen limitation on regrowth of forests following wood harvest and agricultural abandonment. The estimated LULUC emissions for the tropics are 0.79±0.25 for the 1980’s, 0.78±0.29 for the 1990’s and 0.71±0.33 GtC/yr for the 2000’s, and for the non-tropics regions are 1.08±0.52, 0.90±0.19 and 0.69±0.12 GtC/yr for the three decades. The model results indicate that failing to account for the nitrogen cycle underestimates LULCC emissions by about 40% globally (0.66 GtC/yr), 10% in the tropics (0.07 GtC/yr) and 70% in the non-tropics (0.59 GtC/yr). If LULCC emissions are higher than assessed, it means fossil fuel emissions would have to be even lower to meet the same mitigation target.
Extending ISAM simulations to the 21st century resulted in two key insights. First, nitrogen limitation of CO2 uptake is substantial and sensitive to nitrogen inputs. In ISAM, excluding nitrogen limitation underestimated global total LULUC emissions by 34-52 PgC (~21-29%) during the 20th century and by 128-187 PgC (90-150%) during the 21st century. The difference increases with time because nitrogen limitation will progressively down-regulate the magnitude of CO2 fertilization effect on regrowing forests, due to decreasing supply of plant-usable mineral nitrogen. Second, historically, the indirect effects of anthropogenic activity through environmental changes in land experiencing LULCC (indirect emissions) are small compared to direct effects of anthropogenic LULCC activity (direct emissions). As a result, including or excluding indirect emissions had a minor influence on the estimated total LULUC emissions historically. In contrast, the indirect LULCC emissions for the 21st century are a much larger source to the atmosphere, in simulations with nitrogen limitation. This is because of the gradual weakening of the photosynthetic response to elevated (CO2) caused by nitrogen limitation. Therefore, what fluxes are including in LULCC emissions across different models is a crucial source of uncertainty in future LULCC emissions estimates.
A detailed investigation of the sensitivity of different global-scale LULCC modeling techniques show that land use allocation approaches based solely on previous land use history (but disregarding the impact of driving factor), or those based on mechanistically fitting models for the spatial processes of land use change do not reproduce well long-term historical land use patterns. With an example application to the terrestrial carbon cycle, I show that such inaccuracies in land use allocation can translate into significant implications for global environmental assessments. In contrast to previous approaches, I present a statistical land use downscaling model and show that the model can reproduce the broad spatial features of the past 100 years of evolution of cropland and pastureland patterns. Therefore, the modeling approach and its evaluation provide an example that can be useful to the land use, Integrated Assessment, and the Earth system modeling communities.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2018-05-01The student, Prasanth Meiyappan, accepted the attached license on 2016-04-13 at 20:33.The student, Prasanth Meiyappan, submitted this Dissertation for approval on 2016-04-13 at 20:39.This Dissertation was approved for publication on 2016-04-18 at 14:23.DSpace SAF Submission Ingestion Package generated from Vireo submission #9216 on 2016-07-07 at 14:16:41Made available in DSpace on 2016-07-07T21:14:41Z (GMT). No. of bitstreams: 3
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