154 research outputs found
Unified model of lithium-ion battery and electrochemical storage system
No full textNowadays, energy storage systems are of paramount importance in sectors such as renewable energy production and sustainable mobility because of the energy crisis and climate change issues. Although there are various types of energy storage systems, electrochemical devices such as electric double layer capacitors (EDLCs), lithium-ion capacitors (LiCs), and lithium-ion batteries (LiBs) are the most common because of their high efficiency and flexibility. In particular, LiBs are broadly employed in many applications and preferred in the mobility sector, where there is a need for high energy and high power. To ensure good operating conditions for a battery and limit its degradation, it is important to have a precise model of the device. The literature contains numerous equivalent circuit models capable of predicting the electrical behavior of an LiB in the time or frequency domain. In most of them, the battery impedance is in series with a voltage source modeling the open circuit voltage of the battery for simulation in the time domain. This study demonstrated that an extension of a model composed exclusively of passive elements from the literature for EDLCs and LiCs would also be suitable for LiBs, resulting in a unified model for these types of electrochemical storage systems. This model uses the finite space Warburg impedance, which, in addition to the diffusion process of lithium\lithium ions in the electrodes\electrolyte, makes it possible to consider the main capacitance of the battery. Finally, experimental tests were performed to validate the proposed model
Open-Circuit Voltage Variation in LiCoO<sub>2</sub> Battery Cycled in Different States of Charge Regions
No full textCurrently, the urgent needs of sustainable mobility and green energy generation are driving governments and researchers to explore innovative energy storage systems. Concurrently, lithium-ion batteries are one of the most extensively employed technologies. The challenges of battery modeling and parameter estimation are crucial for building reliable battery management systems that ensure optimal battery performance. State of charge (SOC) estimation is particularly critical for predicting the available capacity in the battery. Many methods for SOC estimation rely on the knowledge of the open-circuit voltage (OCV) curve. Another significant consideration is understanding how these curves evolve with battery degradation. In the literature, the effect of cycle aging on the OCV is primarily addressed through the look-up tables and correction factors applied to the OCV curve for fresh cells. However, the variation law of the OCV curve as a function of the battery cycling is not well-characterized. Building upon a simple analytical function with five parameters proposed in the prior research to model the OCV as a function of the absolute state of discharge, this study investigates the dependency of these parameters on the moved charge, serving as an indicator of the cycling level. Specifically, the analysis focuses on the impact of cycle aging in the low-, medium-, and high-SOC regions. Three different cycle aging tests were conducted in these SOC intervals, followed by the extensive experimental verification of the proposed model. The results were promising, with mean relative errors lower than 0.2% for the low- and high-SOC cycling regions and 0.34% for the medium-SOC cycling region. Finally, capacity estimation was enabled by the model, achieving relative error values lower than 1% for all the tests
Calendar Aging Effect on the Open Circuit Voltage of Lithium-Ion Battery
No full textIn recent years, lithium-ion batteries (LiBs) have gained a lot of importance due to the increasing use of renewable energy sources and electric vehicles. To ensure that batteries work properly and limit their degradation, the battery management system needs accurate battery models capable of precisely predicting their parameters. Among them, the state of charge (SOC) estimation is one of the most important, as it enables the prediction of the battery's available energy and prevents it from operating beyond its safety limits. A common method for SOC estimation involves utilizing the relationship between the state of charge and the open circuit voltage (OCV). On the other hand, the latter changes with battery aging. In a previous work, the authors studied a simple function to model the OCV curve, which was expressed as a function of the absolute state of discharge, q, instead of SOC. They also analyzed how the parameters of such a curve changed with the cycle aging. In the present work, a similar analysis was carried out considering the calendar aging effect. Three different LiB cells were stored at three different SOC levels (low, medium, and high levels) for around 1000 days, and an analysis of the change in the OCV-q curve model parameters with the calendar aging was performed
State of Health Estimation of LiCoO2 Cells based on Impulse Response and ARMAX Identification
No full textLithium-ion batteries (LiBs) are subjected to different degradation mechanisms due to storage and operating conditions. State-of-health estimation (SOH) is crucial for proper prediction of battery aging and is usually related to the decrease in energy (capacity fade) or the increase in internal resistance (power fade). This paper evaluates the application of the Impulse Response (IR) method to LiCoO2 (LCO) battery cells for the estimation of SOH in terms of capacity fade. The IR method involves creating a precalculated table in which the cell voltage responses to input pulse currents are measured and stored for different states of charge (SOC) and SOH levels. To this aim, an LCO cell was cycled at constant current steps under fixed-temperature conditions. After a certain number of aging cycles, its voltage response to a current impulse was recorded at different levels of SOC. The same procedure was performed for different SOH levels to train multiple linear auto-regressive identification models. To validate the methodology and assess its precision, the trained models were used to predict the actual SOH level of the cell
Successful aortic valve repair for severe aortic insufficiency caused by radiofrequency ablation
No full textNo Abstract availabl
A technique for separating the impact of cycle aging and temperature on Li-ion battery capacity
No full textReduction of battery capacity is a well-known symptom of aging, making it a universally accepted indicator of the state of health. Capacity also significantly depends on temperature, therefore, separating the effect of temperature from that due to aging has utmost important for a proper state of health assessment. However, according to the latest literature, there is a lack of information about how the temperature dependency of capacity changes with battery aging. In this respect, the study presented in this paper is based on an experimental campaign aimed at measuring battery capacity at different temperatures and cycling levels. Starting from the obtained results, an analytical model describing how the variation law of battery capacity with temperature is affected by cycling was proposed and validated. The achieved accuracy is better than 0.6 % for all the considered operating conditions
Which trial do we need? Combination regimen for individuals exposed to multidrug-resistant Mycobacterium tuberculosis
No full textTuberculosis in migrants: epidemiology, resistance and outcome in Milan, Italy
No full textBackground: Human migration and the ever-changing geopolitical scenarios are redefining the epidemiology and the management of tuberculosis (TB), especially in low-TB burden countries welcoming high rates of people from high-TB burden countries. Methods: We conducted an observational retrospective mono-centric study in a Northern-Italy TB reference centre from 1 January 1990 to 31 December 2019, focusing on the differences in epidemiology, resistance patterns and treatment outcomes between Italians and migrants with active TB. Data were collected from medical records. Results: A total of 10555 patients were included, 4614 Italians and 5941 migrants. Among migrants, higher rates of rifampin-resistant (RR) or multidrug-resistant (MDR) TB were reported, as well as higher rates of loss to follow-up. Among Italians, higher mortality rates and a higher number of extrapulmonary TB cases were found. Conclusion: Our study describes one of the largest cohorts of patients with active TB in Italy, highlighting the need for tailored approaches in native and migrant populations
Evaluating the efficacy of whole genome sequencing in predicting susceptibility profiles for first-line antituberculosis drugs
No full textObjectives: This study aimed to examine the efficacy of whole genome sequencing (WGS) in accurately predicting susceptibility profiles, potentially eliminating the need for conventional phenotypic drug susceptibility testing (pDST) for first-line antituberculosis drugs in routine tuberculosis diagnosis. Methods: Over the period of 2017 to 2020, 1114 Mycobacterium tuberculosis complex isolates were collected with drug susceptibility testing conducted using the MGIT960 system and WGS performed for predicting drug resistance profiles. In addition, we implemented a new algorithm with an updated WGS workflow, omitting pan-susceptible strains from pDST. Results: Results showed that out of 1075 analysed isolates, WGS-based genotypic sensitivity predictions for isoniazid, rifampicin, ethambutol, and pyrazinamide were 100% (95% CI, 99.6-100%), 100% (95% CI, 99.62-100%), 99.8% (95% CI, 99.26-99.94%), and 100% (95% CI, 99.63-100%), respectively. In contrast, the WGS-based genotypic resistance prediction, was 98.85% (95% CI, 93.77-99.79%) for isoniazid, 94.74% (95% CI, 82.71-98.54%) for rifampicin, 86.96% (95% CI, 67.87-95.46%) for ethambutol, and 75.7% (95% CI, 59.9-86.63%) for pyrazinamide. Moreover, WGS enabled the implementation of a new testing algorithm that made it unnecessary to perform pDST in 954 of all 1075 samples (88.7%) and in 890 of 901 pan-susceptible samples (98.8%). Discussion: Integrating WGS into tuberculosis management offers significant potential to replace phenotypic drug susceptibility testing, especially for problematic drugs like pyrazinamide and ethambutol, potentially improving treatment outcomes
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