scholarly journals Smart Core and Surface Temperature Estimation Techniques for Health-conscious Lithium-ion Battery Management Systems: A Model-to-Model Comparison

2021 ◽  
Author(s):  
Sumukh Surya ◽  
Akash Samanta ◽  
Sheldon Williamson
Keyword(s):  
Surface Temperature ◽  
Computational Cost ◽  
Lithium Ion ◽  
Second Order ◽  
Battery Management ◽  
Order Model ◽  
Temperature Estimation ◽  
Thermal Models ◽  
First Order ◽  
Estimation Scheme

Estimation of core and surface temperature is one of the crucial functionalities of the lithium-ion Battery Management System (BMS) towards providing effective thermal management, fault detection and operational safety. While, it is impractical to measure core temperature using physical sensors, implementing a complex estimation strategy in on-board low-cost BMS is challenging due to high computational cost and the cost of implementation. Typically, a temperature estimation scheme consists of a heat generation model and a heat transfer model. Several researchers have already proposed ranges of thermal models having different levels of accuracy and complexity. Broadly, there are first-order and second-order heat capacitor-resistor-based thermal models of lithium-ion batteries (LIBs) for core and surface temperature estimation. This paper deals with a detailed comparative study between these two models using extensive laboratory test data and simulation study to access suitability in online prediction and onboard BMS. The aim is to guide whether it’s worth investing towards developing a second-order model instead of a first-order model with respect to prediction accuracy considering modelling complexity, experiments required and the computational cost. Both the thermal models along with the parameter estimation scheme are modelled and simulated using MATLAB/Simulink environment. Models are validated using laboratory test data of a cylindrical 18650 LIB cell. Further, a Kalman Filter with appropriate process and measurement noise levels are used to estimate the core temperature in terms of measured surface and ambient temperatures. Results from the first-order model and second-order models are analyzed for comparison purposes.

scholarly journals A Comprehensive Review of Lithium-Ion Cell Temperature Estimation Techniques Applicable to Health-Conscious Fast Charging and Smart Battery Management Systems

Energies ◽  
2021 ◽  
Vol 14 (18) ◽  
pp. 5960
Author(s):  
Akash Samanta ◽  
Sheldon S. Williamson
Keyword(s):  
Computational Cost ◽  
Lithium Ion ◽  
Accurate Estimation ◽  
Battery Management System ◽  
Battery Management ◽  
Cell Temperature ◽  
Temperature Estimation ◽  
Estimation Strategy ◽  
Highly Nonlinear ◽  
Fast Charging

Highly nonlinear characteristics of lithium-ion batteries (LIBs) are significantly influenced by the external and internal temperature of the LIB cell. Moreover, a cell temperature beyond the manufacturer’s specified safe operating limit could lead to thermal runaway and even fire hazards and safety concerns to operating personnel. Therefore, accurate information of cell internal and surface temperature of LIB is highly crucial for effective thermal management and proper operation of a battery management system (BMS). Accurate temperature information is also essential to BMS for the accurate estimation of various important states of LIB, such as state of charge, state of health and so on. High-capacity LIB packs, used in electric vehicles and grid-tied stationary energy storage system essentially consist of thousands of individual LIB cells. Therefore, installing a physical sensor at each cell, especially at the cell core, is not practically feasible from the solution cost, space and weight point of view. A solution is to develop a suitable estimation strategy which led scholars to propose different temperature estimation schemes aiming to establish a balance among accuracy, adaptability, modelling complexity and computational cost. This article presented an exhaustive review of these estimation strategies covering recent developments, current issues, major challenges, and future research recommendations. The prime intention is to provide a detailed guideline to researchers and industries towards developing a highly accurate, intelligent, adaptive, easy-to-implement and computationally efficient online temperature estimation strategy applicable to health-conscious fast charging and smart onboard BMS.

scholarly journals A Comprehensive Review of Lithium-ion Cell Temperature Estimation Techniques Applicable to Health-Conscious Fast Charging and Smart Battery Management Systems

2021 ◽  
Author(s):  
Akash Samanta ◽  
Sheldon S. Williamson
Keyword(s):  
Computational Cost ◽  
Lithium Ion ◽  
Accurate Estimation ◽  
Battery Management System ◽  
Battery Management ◽  
Cell Temperature ◽  
Temperature Estimation ◽  
Estimation Strategy ◽  
Highly Nonlinear ◽  
Fast Charging

Highly nonlinear characteristics of lithium-ion batteries (LIBs) are significantly influenced by the external and internal temperature of the LIB cell. Moreover, cell temperature beyond the manufacturer’s specified safe operating limit could lead to thermal runaway and even fire hazards and safety concerns to operating personnel. Therefore, accurate information of cell internal and surface temperature of LIB is highly crucial for effective thermal management and proper operation of a battery management system (BMS). Accurate temperature information is also essential to BMS for the accurate estimation of various important states of LIB such as state of charge, state of health and so on. High capacity LIB pack, used in electric vehicles and grid-tied stationary energy storage system essentially consists of thousands of individual LIB cells. Therefore, installing a physical sensor at each cell especially at the cell core is not practically feasible from the solution cost, space and weight point of view. A solution is to develop a suitable estimation strategy which led scholars to propose different temperature estimation schemes aiming to establish a balance among accuracy, adaptability, modelling complexity and computational cost. This article presented an exhaustive review of these estimation strategies covering recent developments, current issues, major challenges, and future research recommendations. The prime intention is to provide a detailed guideline to the researchers and industries towards developing a highly accurate, intelligent, adaptive, easy to implement and compute efficient online temperature estimation strategy applicable to health-conscious fast charging and smart onboard BMS.

scholarly journals Examining the Impostor-Profile—Is There a General Impostor Characteristic?

2021 ◽  
Vol 12 ◽  
Author(s):  
Fabio Ibrahim ◽  
Johann-Christoph Münscher ◽  
Philipp Yorck Herzberg
Keyword(s):  
Convergent Validity ◽  
Factor Model ◽  
Second Order ◽  
Model Fit ◽  
Impostor Phenomenon ◽  
General Factor ◽  
Order Model ◽  
First Order ◽  
Order Factor ◽  
Best Fit

The Impostor-Profile (IPP) is a six-dimensional questionnaire measuring the Impostor Phenomenon facets. This study aims to test (a) the appropriateness of a total score, (b) measurement invariance (MI) between gender, (c) the reliability of the IPP, and (d) the convergent validity of the IPP subscales. The sample consisted of N = 482 individuals (64% female). To identify whether the scales of the IPP form a total score, we compared four models: (1) six correlating subscales, (2) a general factor model, (3) a second-order model with one second-order factor and six first-order factors, and (4) a bifactorial model with six group factors. The bifactorial model obtained the best fit. This supports the assumption of a total impostor score. The inspection of structural validity between gender subgroups showed configural, metric, and partial scalar MI. Factor mean comparisons supported the assumption that females and males differ in latent means of the Impostor Phenomenon expressions. The omega coefficients showed sufficient reliability (≥0.71), except for the subscale Need for Sympathy. Overall, the findings of the bifactor model fit and construct validity support the assumption that the measurement through total expression is meaningful in addition to the theoretically formulated multidimensionality of the Impostor Phenomenon.

Transient changes in muscle high-energy phosphates during moderate exercise

1993 ◽  
Vol 75 (2) ◽  
pp. 648-656 ◽  
Author(s):  
G. D. Marsh ◽  
D. H. Paterson ◽  
J. J. Potwarka ◽  
R. T. Thompson
Keyword(s):  
Oxygen Consumption ◽  
Steady State ◽  
Recovery Period ◽  
High Energy ◽  
Second Order ◽  
Moderate Intensity ◽  
High Energy Phosphates ◽  
Order Model ◽  
Time Constants ◽  
First Order

The purpose of this study was to use 31P-nuclear magnetic resonance spectroscopy to examine changes in wrist flexor muscle metabolism during the transitions from rest to steady-state exercise (on-transient) and back to rest (off-transient). Five healthy young males (mean age 25 +/- 2 yr) performed a series of square-wave exercise tests, each consisting of 5 min of moderate-intensity work followed by a 5-min recovery period. The subjects repeated this protocol six times, and each individual's results were pooled before analysis. ATP and intracellular pH did not change significantly during exercise or recovery. Phosphocreatine (PCr) declined progressively at the onset of exercise, reaching a plateau after approximately 2 min. A reciprocal increase in Pi occurred during the onset of exercise. During the recovery period PCr was resynthesized, whereas Pi returned to resting levels. The data were plotted as a function of time and fit with both first- and second-order exponential growth or decay models; however, the second-order model did not significantly improve the fit of the data. Time constants for the first-order model of the on- and off-transient responses for both PCr and Pi were approximately 30 s. These values are nearly identical to the time constants for oxygen consumption during submaximal exercise that have been reported previously by several authors. The results of this study show that the metabolism of muscle PCr during steady-state exercise and recovery can be accurately described by a monoexponential model and, further, suggest that a first-order proportionality exists between metabolic substrate utilization and oxygen consumption.

scholarly journals Influence of Sampling Delay on the Estimation of Lithium-Ion Battery Parameters and an Optimized Estimation Method

Energies ◽  
2019 ◽  
Vol 12 (10) ◽  
pp. 1878
Author(s):  
Bing Jiang ◽  
Zeqi Chen ◽  
Feifan Chen
Keyword(s):  
Estimation Method ◽  
Equivalent Circuit Model ◽  
Lithium Ion ◽  
Test System ◽  
Recursive Least Squares ◽  
Battery Management System ◽  
Battery Management ◽  
First Order ◽  
The Mathematical Model ◽  
Synchronization Accuracy

The equivalent-circuit model (ECM) is widely used in online estimating the parameters and states of lithium-ion batteries. However, the sampling delay between the voltage and current of a battery is generally overlooked, which is unavoidable in a modular battery management system (BMS) and would lead to wrong results in the estimation of battery parameters and states. In this paper, with the first-order resistor–capacitor (RC) model as our battery model, we analyze the influence mechanism of sampling delay and then propose an optimized method for online estimating battery parameters. The mathematical model derived from the first-order RC model and the approximation method of first-order derivative are optimized. The recursive least squares (RLS) algorithm is used for identifying the parameters of the model. In order to verify the proposed method, a modular battery test system with high sampling frequency and high synchronization accuracy is developed. The experiment results indicate that the sampling delay would cause the estimation process to fluctuate, and the optimized method effectively improves the tolerance range of sampling delay.

Second-Order Correlation of Klinkenberg-Corrected Permeability and its Experimental Verification on Heterogeneously-Stressed Gas Shale

2020 ◽  
Author(s):  
Yufei Chen ◽  
Changbao Jiang ◽  
Juliana Y. Leung ◽  
Andrew K. Wojtanowicz ◽  
Dongming Zhang ◽  
...  
Keyword(s):  
Experimental Data ◽  
Second Order ◽  
Gas Shale ◽  
Order Model ◽  
First Order ◽  
Gas Slippage ◽  
Steady State Method ◽  
Slippage Effect ◽  
Stress Heterogeneity ◽  
Second Order Model

Abstract Shale is an extremely tight and fine-grained sedimentary rock with nanometer-scale pore sizes. The nanopore structure within a shale system contributes not only to the low to ultra-low permeability coefficients (10−18 to 10−22 m2), but also to the significant gas slippage effect. The Klinkenberg equation, a first-order correlation, offers a satisfying solution to describe this particular phenomenon for decades. However, in recent years, several scholars and engineers have found that the linear relation from the Klinkenberg equation is invalid for most gas shale reservoirs, and a need for a second-order model is, therefore, proceeding apace. In this regard, the purpose of this study was to develop a second-order approach with experimental verifications. The study involved a derivation of a second-order correlation of the Klinkenberg-corrected permeability, followed by experimental verifications on a cubic shale sample sourced from the Sichuan Basin in southwestern China. We utilized a newly developed multi-functional true triaxial geophysical (TTG) apparatus to carry out permeability measurements with the steady-state method in the presence of heterogeneous stresses. Also discussed were the effects of two gas slippage factors, Klinkenberg-corrected permeability, and heterogeneous stress. Finally, based on the second-order slip theory, we analyzed the deviation of permeability from Darcy flux. The results showed that the apparent permeability increased more rapidly as the pore pressure declined when the pore pressures are relatively low, which is a strong evidence of the gas slippage effect. The second-order model could reasonably match the experimental data, resulting in a lower Klinkenberg-corrected permeability compared with that from the linear Klinkenberg equation. That is, the second-order approach improves the intrinsic permeability estimation of gas shales with the result being closer to the liquid permeability compared with the Klinkenberg approach. Analysis of the experimental data reported that both the first-order slippage factor A and the second-order slippage factor B increased with increasing stress heterogeneity, and that A was likely to be more sensitive to stress heterogeneity compared with B. Interestingly, both A and B first slightly increased and then significantly as the permeability declined. It is recommended that when the shale permeability is below 10−18 m2, the second-order approach should be taken into account. Darcy’s law starts to deviate when Kn > 0.01 and is invalid at high Knudsen numbers. The second-order approach seems to alleviate the problem of overestimation compared with the Klinkenberg approach and is more accurate in permeability evolution.

scholarly journals Kinetics Study of UASB and HUASB System in Treating Municipal Wastewater

2015 ◽  
Vol 773-774 ◽  
pp. 1173-1177
Author(s):  
Mohd Afindy Abd Kadir ◽  
Ab Aziz Abdul Latiff ◽  
Zawawi Daud
Keyword(s):  
Municipal Wastewater ◽  
Kinetic Constant ◽  
Combined Treatment ◽  
Second Order ◽  
Kinetics Study ◽  
Order Method ◽  
Order Model ◽  
First Order ◽  
Working Volume ◽  
First Order Method

. A combined laboratory-scale system UASB-DFAF and HUASB-DFAF was operated for treating Municipal wastewater at six hydraulic retention times (HRT) of 45.08, 30.06, 22.54, 18.03, 15.03, 12.88 h. COD removal efficiency in range from 72% to 82% in UASB, while in HUASB range from 84 to 89% with decrease of HRT. There are several method have been developed to represent biodegration of municipal sewerage in a combined treatment system. The Monod, Grou second-order and first order model have been used to analyze this studies. The combined of HUASB reactor, 5.41 L working volume, followed by DFAF reactor, having a working volume 2.67L were analyzed. The kinetic parameters were determined through line regression using experimental data. The predicted COD concentration was calculated using the kinetic constant. The kinetic models applied for this study were Grou second-order, followed by first order method and Monod method.

Removal of hazardous pharmaceutical dyes by adsorption onto papaya seeds

2014 ◽  
Vol 70 (1) ◽  
pp. 102-107 ◽  
Author(s):  
Caroline Trevisan Weber ◽  
Gabriela Carvalho Collazzo ◽  
Marcio Antonio Mazutti ◽  
Edson Luiz Foletto ◽  
Guilherme Luiz Dotto
Keyword(s):  
Aqueous Solutions ◽  
Second Order ◽  
Isotherm Models ◽  
Order Model ◽  
Application Range ◽  
First Order ◽  
Adsorption Capacities ◽  
Effects Of Ph ◽  
Pseudo Second Order ◽  
Papaya Seeds

Papaya (Carica papaya L.) seeds were used as adsorbent to remove toxic pharmaceutical dyes (tartrazine and amaranth) from aqueous solutions, in order to extend application range. The effects of pH, initial dye concentration, contact time and temperature were investigated. The kinetic data were evaluated by the pseudo first-order, pseudo second-order and Elovich models. The equilibrium was evaluated by the Langmuir, Freundlich and Temkin isotherm models. It was found that adsorption favored a pH of 2.5, temperature of 298 K and equilibrium was attained at 180–200 min. The adsorption kinetics followed the pseudo second-order model, and the equilibrium was well represented by the Langmuir model. The maximum adsorption capacities were 51.0 and 37.4 mg g−1 for tartrazine and amaranth, respectively. These results revealed that papaya seeds can be used as an alternative adsorbent to remove pharmaceutical dyes from aqueous solutions.

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