1,720,999 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
An Electro-Thermal Model for LFP Cells: Calibration Procedure and Validation
Full text linkLithium batteries for energy storage systems are a prominent solution for both stationary and mobile applications. Electro-thermal modelling of the cell is a useful tool for monitoring voltage and temperature in order to predict battery behaviour especially in cases of critical operative con-ditions. This paper provides a modelling approach focusing on the calibration of parameters of an electro-thermal model for large prismatic LFP lithium cells. The designed model is tuned by means of experimental tests that identify a set of parameters that are function of a cell’s state-of-charge and temperature. The model outputs are voltage, cell surface, and internal temperature profiles, which are validated against experimental data referring to realistic working conditions, even providing an intense level of thermal stress. The model accuracy is marked by a voltage mean average error lower than 1% and a mean cell surface temperature deviation lower than 1 K
Experimental analysis of LFP lithium cells aging
No full textAging of batteries is one the most significant aspects to be considered, when engaged in stationary or mobile applications. With reference to a project currently in progress, based on an accurate analysis of fast charging operations, some experimental tests have been carried out on an LFP lithium cell, to analyze its aging over time, when subjected to different solicitations of power requested. Additionally, several aging indicators have been defined, measured and analyzed, to be compared each other and to verify their correlation with the cell aging levels. Preliminary results show that part of these indicators can correctly be used as good cell aging predictors, giving a unique aging trend
Voltage-current based algorithm for the on-line estimation of equivalent internal resistance of Lithium-Cobalt-Oxide cells at different aging levels
No full textThis paper deals with the problem of the identification of lithium cell parameters to be correlated with the cell level of aging. Three identical Lithium-Cobalt-Oxide (LCO) commercial cells at three different State-of-Life (SOL) values are experimentally tested, and two parameter estimations are applied, focusing on the cell internal resistance, which appears significantly sensitive to different cell aging levels. After displaying how the single cells under study can be calibrated through an off-line procedure by means of equivalent electrical circuit approach, the development of a voltage-current based algorithm to be applied on-line and capable of estimating an 'equivalent internal resistance' to be correlated with cell SOL is proposed. The robustness and the online applicability of the algorithm is tested on different realistic scenarios, as well as different State-of-Charge levels. Results confirm the capability of the proposed algorithm to be potentially applied for the online State-of-Life estimation for lithium cells
Experimental Analysis of Ni-MH High Power Cells
No full textNowadays lithium batteries very often are considered the best choice, both for stationary and mobile applications. However, their cost remains higher than some other technologies, despite a significant decline in the last years. Additionally, for safety reasons accurate thermal management is needed, not to exceed the maximum allowed temperature. It is therefore of interest to evaluate alternative technologies. This paper shows the results of the evaluation made of a Ni-MH high-power cell, used into a funded project aimed to develop innovative solutions for automated warehouses. This cell was accurately analysed and compared with one of the most performing lithium cells on the market, showing good results
Modelling lithium battery packs from single cell electro-Thermal equivalent circuit model
No full textModelling thermal behaviour of battery packs in pure electric vehicles (BEVs) is one of the most demanding tasks in powertrain design activities. The complexity is given by the need of considering several aspects like internal geometry, cooling circuit, etc. for which the standard approach based on equivalent circuit model seems not to be adequate. The aim of this paper is instead to demonstrate how it is possible to maintain the equivalent circuit model approach, by making minimal changes and by using data from vehicle CAN network. Then, the model can be used to correctly achieve battery pack temperature under different realistic use conditions
Neural network for the estimation of LFP battery SOH cycled at different power levels
No full textThis work presents a method to quantify and estimate the degradation level of lithium-ion battery cell cycle aged at different power levels. Experimental results previously reported by the authors are analysed further, now with artificial intelligence workflows to establish a method to estimate the cells degradation rate, in term of State of Health. The neural network estimation capability is dependent on the type of input signal used for training, and the relative proportion of training vs. testing data. The development of a feedforward neural network which elaborates the information of voltage and current differences during sudden power changes significantly increased the predictive capability of the method, reaching State-of-Health estimation best-case errors lower than 1 %, in line with more complex Artificial Intelligence approaches found in literature. In addition, the results obtained with the feedforward neural network are then compared with a regression learning – based estimation function, trained and tested over the same dataset. As last test, both these two methods, trained with dataset coming from cycle aging experimental tests, are used to estimate the State of Health of a lithium cell aged due to calendar phenomena only
Experimental evaluation of aging indicators for lithium–iron–phosphate cells
Full text linkDegradation mechanism of batteries has to be carefully studied when considering their utilization in electrical power systems. This paper presents the results of an extensive experimental campaign, through which three different lithium–iron–phosphate (LFP) cells were subjected to different electrical cycling stresses. The purpose of the campaign was to evaluate the cells’ aging, as well as to try to find parameters on the cell behavior before its end of life, able to act as state-of-life (SOL) (or aging) indicators. The considered stress consists of the cyclic repetition of fixed-duration discharge steps, followed by full charge phases. The three cells under study were subjected to the very same stress pattern but with three different discharge and charge power levels: low, medium, and high. The results showed that the end-of-discharge voltage and the cell internal resistance can be used as good SOL indicators. However, both are significant functions of the cell conditions, such as the state of charge (SOC) and the cell temperature
Model Parameter Evaluation for Nickel-Manganese-Cobalt Cells: An Examination and Verification of Various Approaches
No full textLithium cells are typically modelled through equivalent electrical networks whose parameters are tuned to closely match measured data. In this way, complicated experimental procedures are often needed to correctly achieve the actual battery behavior. After the testing, simulation models are fitted on experimental data through optimization algorithms. The computational cost is high, and significant time can be required to obtain the parameters. This article analyzes and discusses these two aspects. First, it examines which tests are needed and whether their duration can be shortened. Second, it describes how to correctly perform parameter identification and explores whether generalizations can be made in their formulation. The accuracy of each proposed solution is detailed, including test durations and computational costs
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