2,412 research outputs found
An Electric Vehicle Simulator for Realistic Battery Signals Generation from Data-sheet and Real-world Data
Electric vehicles (EVs) have been globally recognized as a reliable alternative to fossil fuel vehicles. The core component of an electric vehicle is its rechargeable battery pack. However, there still needs to be large-scale publicly available EV data to investigate and distribute effective solutions to monitor the conditions of the EV’s battery pack. Hence, we propose an EV simulator that generates EV battery pack internal signals starting from the input driving cycle. The simulated data resemble the behavior of a multi-cell EV battery pack undergoing the user’s utilization of the EV. The simulated data include vehicle speed, voltage, current, State of Charge (SOC), and internal temperature of the battery pack. The virtual-EV model simulator, including the battery pack subsystem, has been tuned using real-world EV data-sheet information. The battery pack embeds thermal and aging models for further realism, influencing the output signals given the environmental temperature and the battery’s State of Health (SOH). The data generated by the virtual EV simulator have been validated with real EV data signals sampled by an equivalent real-world EV. The data comparison yields a minimum R2 value of 0.94 and a Root Mean Squared Error not higher than 2.74V for the battery pack’s voltage and SOC, respectively
Impact of bidirectional EV charging stations on a distribution network: a Power Hardware-In-the-Loop implementation
The need for decarbonizing the entire energy system calls for new operational approaches in different sectors, currently (almost) fully dominated by fossil fuels, such as the transports. In particular, the decarbonization of the light-duty passenger transport, based on the implementation of Battery Electric Vehicles, may have a twofold benefit, because of (i) the reduction of local and global direct emissions, and (ii) the role that the Battery Electric Vehicles can have in supporting the operation of the power system in case of large share of non-dispatchable renewable energy sources. This paper aims to investigate, through a Power Hardware-In-the-Loop laboratory setup, the impacts of the Vehicle-to-Grid and Grid-to-Vehicle paradigms on a Low Voltage grid portion serving as grid infrastructure an energy community. The results show that the Low Voltage grid losses, if not taken into account, can cause a wrong evaluation of the expected impact on the grid of the Battery Electric Vehicles. Furthermore, the harmonics of current injected into the grid by several chargers could compromise the perceived power quality. Both the analyzed aspects must be hence carefully considered for properly evaluating pros and cons that the installation of several chargers may have on the grid side. The main contributions refer to the calculation of losses and to the evaluation of the power quality aspects through a Power Hardware-In-the-Loop configuration, enabling to take into account the harmonics interaction between charging stations and power grid
Modelling battery packs of real-world electric vehicles from data sheet information
Lithium-ion batteries have emerged as the leading enabling technology in developing Electric Vehicles (EVs), But, large-scale publicly available EV data are extremely difficult to find. So it becomes difficult to research and disseminate new methods for monitoring the battery pack of an EV. In this work, we propose a Simulink-based approach to define a virtual-EV model that simulates EV battery pack signals starting from input driving sessions. The battery pack module within the virtual-EV has been fine-tuned using data gathered from real-world EV data sheets. Moreover, the battery pack module includes thermal and aging models, impacting on the output signals, considering the temperature of the surrounding environment and the initial State of Health (SOH) of the battery pack. The virtual-EV generates time series of vehicle's speed, and battery pack's current, State of Charge (SOC), voltage, and average internal temperature according to the input driving cycle. We defined two Simulink EV models emulating two distinct real-world-EVs. Then, we assessed the performances of the simulators comparing the simulated data and real EV data signals collected by the same real-world-EV models, and we obtain, for both simulated EV models, R2 values higher than 0.70 and an RMSE of at most 7V and 8% for the voltage and SOC of the battery pack, respectively
Comparative Analysis of Neural Networks Techniques for Lithium-ion Battery SOH Estimation
Li-ion batteries have become the most important technology for electric mobility. One of the most pressing challenges is the development of reliable methods for battery state-of-health (SOH) diagnosis and estimation of remaining useful life. In electric mobility scenario, battery capacity degradation prediction is crucial to ensure service availability and life duration. This research work provides a comprehensive comparative analysis of neural networks for a data-driven approach suitable for SOH estimation on single cells, stressed under laboratory conditions. For this purpose, different neural networks (i.e., LSTM, GRU, 1D-CNN, CNN-LSTM) are trained and optimized on NASA Randomized Battery Usage dataset. Experimental results demonstrate that data-driven neural networks generally performed well SOH estimation on single cells. In detail, the 1D-CNN best predicts SOH and has the lowest variance in the output. The LSTM have the highest variance in estimating SOH, while GRU and CNN-LSTM tend to overestimate and underestimate the value of SOH, respectively
INFN What Next: Ultra-relativistic Heavy-Ion Collisions
This document was prepared by the community that is active in Italy, within
INFN (Istituto Nazionale di Fisica Nucleare), in the field of
ultra-relativistic heavy-ion collisions. The experimental study of the phase
diagram of strongly-interacting matter and of the Quark-Gluon Plasma (QGP)
deconfined state will proceed, in the next 10-15 years, along two directions:
the high-energy regime at RHIC and at the LHC, and the low-energy regime at
FAIR, NICA, SPS and RHIC. The Italian community is strongly involved in the
present and future programme of the ALICE experiment, the upgrade of which will
open, in the 2020s, a new phase of high-precision characterisation of the QGP
properties at the LHC. As a complement of this main activity, there is a
growing interest in a possible future experiment at the SPS, which would target
the search for the onset of deconfinement using dimuon measurements. On a
longer timescale, the community looks with interest at the ongoing studies and
discussions on a possible fixed-target programme using the LHC ion beams and on
the Future Circular Collider.Comment: 99 pages, 56 figure
Multiplicity dependence of jet-like two-particle correlations in p-Pb collisions at = 5.02 TeV
Two-particle angular correlations between unidentified charged trigger and
associated particles are measured by the ALICE detector in p-Pb collisions at a
nucleon-nucleon centre-of-mass energy of 5.02 TeV. The transverse-momentum
range 0.7 5.0 GeV/ is examined,
to include correlations induced by jets originating from low
momen\-tum-transfer scatterings (minijets). The correlations expressed as
associated yield per trigger particle are obtained in the pseudorapidity range
. The near-side long-range pseudorapidity correlations observed in
high-multiplicity p-Pb collisions are subtracted from both near-side
short-range and away-side correlations in order to remove the non-jet-like
components. The yields in the jet-like peaks are found to be invariant with
event multiplicity with the exception of events with low multiplicity. This
invariance is consistent with the particles being produced via the incoherent
fragmentation of multiple parton--parton scatterings, while the yield related
to the previously observed ridge structures is not jet-related. The number of
uncorrelated sources of particle production is found to increase linearly with
multiplicity, suggesting no saturation of the number of multi-parton
interactions even in the highest multiplicity p-Pb collisions. Further, the
number scales in the intermediate multiplicity region with the number of binary
nucleon-nucleon collisions estimated with a Glauber Monte-Carlo simulation.Comment: 23 pages, 6 captioned figures, 1 table, authors from page 17,
published version, figures at
http://aliceinfo.cern.ch/ArtSubmission/node/161
Anisotropic flow of charged hadrons, pions and (anti-)protons measured at high transverse momentum in Pb-Pb collisions at TeV
The elliptic, , triangular, , and quadrangular, , azimuthal
anisotropic flow coefficients are measured for unidentified charged particles,
pions and (anti-)protons in Pb-Pb collisions at TeV
with the ALICE detector at the Large Hadron Collider. Results obtained with the
event plane and four-particle cumulant methods are reported for the
pseudo-rapidity range at different collision centralities and as a
function of transverse momentum, , out to GeV/.
The observed non-zero elliptic and triangular flow depends only weakly on
transverse momentum for GeV/. The small dependence
of the difference between elliptic flow results obtained from the event plane
and four-particle cumulant methods suggests a common origin of flow
fluctuations up to GeV/. The magnitude of the (anti-)proton
elliptic and triangular flow is larger than that of pions out to at least
GeV/ indicating that the particle type dependence persists out
to high .Comment: 16 pages, 5 captioned figures, authors from page 11, published
version, figures at http://aliceinfo.cern.ch/ArtSubmission/node/186
Centrality dependence of charged particle production at large transverse momentum in Pb-Pb collisions at TeV
The inclusive transverse momentum () distributions of primary
charged particles are measured in the pseudo-rapidity range as a
function of event centrality in Pb-Pb collisions at
TeV with ALICE at the LHC. The data are presented in the range
GeV/ for nine centrality intervals from 70-80% to 0-5%.
The Pb-Pb spectra are presented in terms of the nuclear modification factor
using a pp reference spectrum measured at the same collision
energy. We observe that the suppression of high- particles strongly
depends on event centrality. In central collisions (0-5%) the yield is most
suppressed with at -7 GeV/. Above
GeV/, there is a significant rise in the nuclear modification
factor, which reaches for GeV/. In
peripheral collisions (70-80%), the suppression is weaker with almost independently of . The measured nuclear
modification factors are compared to other measurements and model calculations.Comment: 17 pages, 4 captioned figures, 2 tables, authors from page 12,
published version, figures at
http://aliceinfo.cern.ch/ArtSubmission/node/284
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