Real-time estimation of battery internal temperature based on a simplified thermoelectric model

Li-ion batteries have been widely used in the EVs, and the battery thermal management is a key but challenging part of the battery management system. For EV batteries, only the battery surface temperature can be measured in real-time. However, it is the battery internal temperature that directly affects the battery performance, and large temperature difference may exist between surface and internal temperatures, especially in high power demand applications. In this paper, an online battery internal temperature estimation method is proposed based on a novel simplified thermoelectric model. The battery thermal behaviour is first described by a simplified thermal model, and battery electrical behaviour by an electric model. Then, these two models are interrelated to capture the interactions between battery thermal and electrical behaviours, thus offer a comprehensive description of the battery behaviour that is useful for battery management. Finally, based on the developed model, the battery internal temperature is estimated using an extended Kalman filter. The experimental results confirm the efficacy of the proposed method, and it can be used for online internal temperature estimation which is a key indicator for better real-time battery thermal management.

Constructing networks of continuous-time velocity-based models

A conventional local model (LM) network consists of a set of affine local models blended together using appropriate weighting functions. Such networks have poor interpretability since the dynamics of the blended network are only weakly related to the underlying local models. In contrast, velocity-based LM networks employ strictly linear local models to provide a transparent framework for nonlinear modelling in which the global dynamics are a simple linear combination of the local model dynamics. A novel approach for constructing continuous-time velocity-based networks from plant data is presented. Key issues including continuous-time parameter estimation, correct realisation of the velocity-based local models and avoidance of the input derivative are all addressed. Application results are reported for the highly nonlinear simulated continuous stirred tank reactor process.

CoMFA and homology-based models of the glycine binding site of N-methyl-D-aspartate receptor

Homology modeling was used to build 3D models of the N-methyl-D-aspartate (NMDA) receptor glycine binding site on the basis of an X-ray structure of the water-soluble AMPA-sensitive receptor. The docking of agonists and antagonists to these models was used to reveal binding modes of ligands and to explain known structure-activity relationships. Two types of quantitative models, 3D-QSAR/CoMFA and a regression model based on docking energies, were built for antagonists (derivatives of 4-hydroxy-2-quinolone, quinoxaline-2,3-dione, and related compounds). The CoMFA steric and electrostatic maps were superimposed on the homology-based model, and a close correspondence was marked. The derived computational models have permitted the evaluation of the structural features crucial for high glycine binding site affinity and are important for the design of new ligands.

Chloride ingress into marine exposed concrete: A comparison of empirical- and physically- based models

In establishing the reliability of performance-related design methods for concrete – which are relevant for resistance against chloride-induced corrosion - long-term experience of local materials and practices and detailed knowledge of the ambient and local micro-climate are critical. Furthermore, in the development of analytical models for performance-based design, calibration against test data representative of actual conditions in practice is required. To this end, the current study presents results from full-scale, concrete pier-stems under long-term exposure to a marine environment with work focussing on XS2 (below mid-tide level) in which the concrete is regarded as fully saturated and XS3 (tidal, splash and spray) in which the concrete is in an unsaturated condition. These exposures represent zones where concrete structures are most susceptible to ionic ingress and deterioration. Chloride profiles and chloride transport behaviour are studied using both an empirical model (erfc function) and a physical model (ClinConc). The time dependency of surface chloride concentration (Cs) and apparent diffusivity (Da) were established for the empirical model whereas, in the ClinConc model (originally based on saturated concrete), two new environmental factors were introduced for the XS3 environmental exposure zone. Although the XS3 is considered as one environmental exposure zone according to BS EN 206-1:2013, the work has highlighted that even within this zone, significant changes in chloride ingress are evident. This study aims to update the parameters of both models for predicting the long term transport behaviour of concrete subjected to environmental exposure classes XS2 and XS3.

A simultaneous voltammetric temperature and humidity sensor

We report the simultaneous measurement of temperature and humidity by analysing square wave voltammetric responses of two ferrocene derivatives, decamethylferrocene (DmFc) and 1,2-diferrocenylethylene (bisferrocene, BisFc) in 1-(2-methoxyethyl)-1-methyl-pyrrolidinium tris(pentafluoroethyl) trifluorophosphate ([Moepyrr][FAP]). These two molecules produce three peaks in square wave voltammetry. Through study of the peak potentials of BisFc/BisFc(+) (vs. DmFc/DmFc(+)) and BisFc(+)/BisFc(2+) (vs. DmFc/DmFc(+)) over a temperature range of 298 K to 318 K and humidity range of 1% to 50% using square wave voltammetry, the temperature and humidity dependences of the relative peak potentials were investigated. A reliable method to calculate the humidity and temperature based on the voltammetric experiment is characterised and demonstrated.

Deep eutectic solvents based on N-methylacetamide and a lithium salt as suitable electrolytes for lithium-ion batteries

In this work, we present a study on the physical and electrochemical properties of three new Deep Eutectic Solvents (DESs) based on N-methylacetamide (MAc) and a lithium salt (LiX, with X = bis[(trifluoromethyl)sulfonyl]imide, TFSI; hexafluorophosphate, PF; or nitrate, NO). Based on DSC measurements, it appears that these systems are liquid at room temperature for a lithium salt mole fraction ranging from 0.10 to 0.35. The temperature dependences of the ionic conductivity and the viscosity of these DESs are correctly described by using the Vogel-Tammann-Fulcher (VTF) type fitting equation, due to the strong interactions between Li, X and MAc in solution. Furthermore, these electrolytes possess quite large electrochemical stability windows up to 4.7-5 V on Pt, and demonstrate also a passivating behavior toward the aluminum collector at room temperature. Based on these interesting electrochemical properties, these selected DESs can be classified as potential and promising electrolytes for lithium-ion batteries (LIBs). For this purpose, a test cell was then constructed and tested at 25 °C, 60 °C and 80 °C by using each selected DES as an electrolyte and LiFePO (LFP) material as a cathode. The results show a good compatibility between each DES and LFP electrode material. A capacity of up to 160 mA h g with a good efficiency (99%) is observed in the DES based on the LiNO salt at 60 °C despite the presence of residual water in the electrolyte. Finally preliminary tests using a LFP/DES/LTO (lithium titanate) full cell at room temperature clearly show that LiTFSI-based DES can be successfully introduced into LIBs. Considering the beneficial properties, especially, the cost of these electrolytes, such introduction could represent an important contribution for the realization of safer and environmentally friendly LIBs. © 2013 the Owner Societies.

Simulating reinforced concrete members. Part 2: displacement-based analyses

A companion paper described the partial-interaction localised properties that require the development of pseudo properties. If the quantification through experimental testing of these pseudo properties could be removed by the use of mechanics-based models, which is the subject of this paper, then this would: (a) substantially reduce the cost of developing new reinforced concrete products by reducing the amount of testing; (b) increase the accuracy of designing existing and novel reinforced concrete members and structures, bearing in mind that experimentally derived pseudo properties are only applicable within the range of the testing from which they were derived; and (c) reduce the cost and increase the accuracy of developing reinforced concrete design rules. This paper deals with the development of pseudo properties and behaviours directly through mechanics, as opposed to experimental testing, and their incorporation into member global simulations. It also addresses the need for a fundamental shift to displacement-based analyses as opposed to strain-based analyses.

Unfunded pension liabilities and sponsoring firm credit risk: an international analysis of corporate bond spreads

This paper tests empirically whether pension information derived by corporate pension accounting disclosures is priced in corporate bond spreads. The model represents a hybrid of more traditional accounting ratio-based models of credit risk and structural models of bond spreads initiated by Merton (1974). The model is fitted to 5 years of data from 2002 to 2006 featuring companies from the US and Europe. The paper finds that while unfunded pension liabilities are priced in the overall sample, they are not priced as aggressively as traditional leverage. Furthermore, an extended model shows that the pension–credit risk relation is most evident in the US and Germany, where unfunded pension liabilities are priced more aggressively than traditional forms of leverage. No pension–credit risk relation is found in the other countries sampled, notably the UK, Netherlands and France.

Random Regret Minimization: Exploration of a New Choice Model for Environmental and Resource Economics

This paper introduces the discrete choice model-paradigm of Random Regret Minimization (RRM) to the field of environmental and resource economics. The RRM-approach has been very recently developed in the context of travel demand modelling and presents a tractable, regret-based alternative to the dominant choice-modelling paradigm based on Random Utility Maximization-theory (RUM-theory). We highlight how RRM-based models provide closed form, logit-type formulations for choice probabilities that allow for capturing semi-compensatory behaviour and choice set-composition effects while being equally parsimonious as their utilitarian counterparts. Using data from a Stated Choice-experiment aimed at identifying valuations of characteristics of nature parks, we compare RRM-based models and RUM-based models in terms of parameter estimates, goodness of fit, elasticities and consequential policy implications.

Structural basis for understanding structure-activity relationships for the glutamate binding site of the NMDA receptor

We present new homology-based models of the glutamate binding site (in closed and open forms) of the NMDA receptor NR2B subunit derived from X-ray structures of the water soluble AMPA sensitive glutamate receptor. The models were used for revealing binding modes of agonists and competitive antagonists, as well as for rationalizing known experimental facts concerning structure-activity relationships: (i) the switching between the agonist and the antagonist modes of action upon lengthening the chain between the distal acidic group and the amino acid moiety, (ii) the preference for the methyl group attached to the a-amino group of ligands, (iii) the preference for the D-configuration of agonists and antagonists, and (iv) the existence of "superacidic" agonists.

Incorporating uncertainty in predictive species distribution modelling

Motivated by the need to solve ecological problems (climate change, habitat fragmentation and biological invasions), there has been increasing interest in species distribution models (SDMs). Predictions from these models inform conservation policy, invasive species management and disease-control measures. However, predictions are subject to uncertainty, the degree and source of which is often unrecognized. Here, we review the SDM literature in the context of uncertainty, focusing on three main classes of SDM: niche-based models, demographic models and process-based models. We identify sources of uncertainty for each class and discuss how uncertainty can be minimized or included in the modelling process to give realistic measures of confidence around predictions. Because this has typically not been performed, we conclude that uncertainty in SDMs has often been underestimated and a false precision assigned to predictions of geographical distribution. We identify areas where development of new statistical tools will improve predictions from distribution models, notably the development of hierarchical models that link different types of distribution model and their attendant uncertainties across spatial scales. Finally, we discuss the need to develop more defensible methods for assessing predictive performance, quantifying model goodness-of-fit and for assessing the significance of model covariates.

Quality Management and Managerialism in Healthcare:: A Critical Historical Survey

Quality Management and Managerialism in Healthcare creates a comprehensive and systematic international survey of various perspectives on healthcare quality management together with some of their most pertinent critiques. Chapter one starts with a general discussion of the factors that drove the introduction of management paradigms into public sector and health management contexts in the mid to late 1980s. Chapter two explores the rise of risk awareness in medicine; which, prior to the 1980s, stood largely in isolation to the implementation of managerial performance targets. Chapter three investigates the widespread adoption of performance management and clinical governance frameworks during the 1980s and 1990s. This is followed by Chapters four and five which examine systems based models of patient safety and the evidence-based medicine movement as exemplars of managerial perspectives on healthcare quality. Chapter six discusses potential future avenues for the development of alternative perspectives on quality of care which emphasise workforce involvement. The book concludes by reviewing the factors which have underpinned the managerialist trajectory of healthcare management over the past decades and explores the potential impact of nascent technologies such as 'connected health' and 'telehealth' on future developments.

The feasibility of using near infrared and Raman spectroscopic techniques to detect fraudulent adulteration of chili powders with Sudan dye

Chili powder is a globally traded commodity which has been found to be adulterated with Sudan dyes from 2003 onwards. In this study, chili powders were adulterated with varying quantities of Sudan I dye (0.1-5%) and spectra were generated using near infrared reflectance spectroscopy (NIRS) and Raman
spectroscopy (on a spectrometer with a sample compartment modified as part of the study). Chemometrics were applied to the spectral data to produce quantitative and qualitative calibration models and prediction statistics. For the quantitative models coefficients of determination (R2) were found to be
0.891-0.994 depending on which spectral data (NIRS/Raman) was processed, the mathematical algorithm used and the data pre-processing applied. The corresponding values for the root mean square error of calibration (RMSEC) and root mean square error of prediction (RMSEP) were found to be 0.208-0.851%
and 0.141-0.831% respectively, once again depending on the spectral data and the chemometric treatment applied to the data. Indications are that the NIR spectroscopy based models are superior to the models produced from Raman spectral data based on a comparison of the values of the chemometric
parameters. The limit of detection (LOD) based on analysis of 20 blank chili powders against each calibration model gave 0.25% and 0.88% for the NIR and Raman data, respectively. In addition, adopting a qualitative approach with the spectral data and applying PCA or PLS-DA, it was possible to discriminate
between adulterated chili powders from non-adulterated chili powders.