Identifiability and parameter estimation of the single particle lithium-ion battery model

This paper investigates the identifiability and estimation of the parameters of the single particle model (SPM) for lithium-ion battery simulation. Identifiability is addressed both in principle and in practice. The approach begins by grouping parameters and partially non-dimensionalising the SPM to determine the maximum expected degrees of freedom in the problem. We discover that, excluding open circuit voltage, there are only six independent parameters. We then examine the structural identifiability by considering whether the transfer function of the linearised SPM is unique. It is found that the model is unique provided that the electrode open circuit voltage functions have a known non-zero gradient, the parameters are ordered, and the electrode kinetics are lumped into a single charge transfer resistance parameter. We then demonstrate the practical estimation of model parameters from measured frequency-domain experimental electrochemical impedance spectroscopy (EIS) data, and show additionally that the parametrised model provides good predictive capabilities in the time domain, exhibiting a maximum voltage error of 20 mV between model and experiment over a 10 minute dynamic discharge.Comment: 16 pages, 9 figures, pre-print submitted to the IEEE Transactions on Control Systems Technolog

Spatial prediction of species’ distributions from occurrence-only records: combining point pattern analysis, ENFA and regression-kriging

A computational framework to map species’ distributions (realized density) using occurrence-only data and environmental predictors is presented and illustrated using a textbook example and two case studies: distribution of root vole (Microtes oeconomus) in the Netherlands, and distribution of white-tailed eagle nests (Haliaeetus albicilla) in Croatia. The framework combines strengths of point pattern analysis (kernel smoothing), Ecological Niche Factor Analysis (ENFA) and geostatistics (logistic regression-kriging), as implemented in the spatstat, adehabitat and gstat packages of the R environment for statistical computing. A procedure to generate pseudo-absences is proposed. It uses Habitat Suitability Index (HSI, derived through ENFA) and distance from observations as weight maps to allocate pseudo-absence points. This design ensures that the simulated pseudo-absences fall further away from the occurrence points in both feature and geographical spaces. The simulated pseudo-absences can then be combined with occurrence locations and used to build regression-kriging prediction models. The output of prediction are either probabilitiesy of species’ occurrence or density measures. Addition of the pseudo-absence locations has proven effective — the adjusted R-square increased from 0.71 to 0.80 for root vole (562 records), and from 0.69 to 0.83 for white-tailed eagle (135 records) respectively; pseudo-absences improve spreading of the points in feature space and ensure consistent mapping over the whole area of interest. Results of cross validation (leave-one-out method) for these two species showed that the model explains 98% of the total variability in the density values for the root vole, and 94% of the total variability for the white-tailed eagle. The framework could be further extended to Generalized multivariate Linear Geostatistical Models and spatial prediction of multiple species. A copy of the R script and step-by-step instructions to run such analysis are available via contact author’s website

Monitoring of the primary drying of a lyophilization process in vials

An innovative and modular system (LyoMonitor) for monitoring the primary drying of a lyophilization process in vials is illustrated: it integrates some commercial devices (pressure gauges, moisture sensor and mass spectrometer), an innovative balance and a manometric temperature measurement system based on an improved algorithm (DPE) to estimate sublimating interface temperature and position, product temperature profile, heat and mass transfer coefficients. A soft-sensor using a multipoint wireless thermometer can also estimate the previous parameters in a large number of vials. The performances of the previous devices for the determination of the end of the primary drying are compared. Finally, all these sensors can be used for control purposes and for the optimization of the process recipe; the use of DPE in a control loop will be shown as an exampl

Social Networks, Job Search Methods and Reservation Wages: Evidence for Germany

In this paper we analyze the relationship between social networks and the job search behavior of unemployed individuals. It is believed that networks convey useful information in the job search process such that individuals with larger networks should experience a higher productivity of informal search. Hence, job search theory suggests that individuals with larger networks use informal search channels more often and substitute from formal to informal search. Due to the increase in search productivity, it is also likely that individuals set higher reservation wages. We analyze these relations using a novel data set of unemployed individuals in Germany containing extensive information on job search behavior and direct measures for the social network of individuals. Our findings confirm theoretical expectations. Individuals with larger networks use informal search channels more often and shift from formal to informal search. We find that informal search is mainly considered a substitute for passive, less cost intensive search channels. In addition to that, we find evidence for a positive relationship between the network size and reservation wages.job search behavior, unemployment, social networks

Data-based fault detection in chemical processes: Managing records with operator intervention and uncertain labels

Developing data-driven fault detection systems for chemical plants requires managing uncertain data labels and dynamic attributes due to operator-process interactions. Mislabeled data is a known problem in computer science that has received scarce attention from the process systems community. This work introduces and examines the effects of operator actions in records and labels, and the consequences in the development of detection models. Using a state space model, this work proposes an iterative relabeling scheme for retraining classifiers that continuously refines dynamic attributes and labels. Three case studies are presented: a reactor as a motivating example, flooding in a simulated de-Butanizer column, as a complex case, and foaming in an absorber as an industrial challenge. For the first case, detection accuracy is shown to increase by 14% while operating costs are reduced by 20%. Moreover, regarding the de-Butanizer column, the performance of the proposed strategy is shown to be 10% higher than the filtering strategy. Promising results are finally reported in regard of efficient strategies to deal with the presented problemPeer ReviewedPostprint (author's final draft

Social Networks, Job Search Methods and Reservation Wages: Evidence for Germany

In this paper we analyze the relationship between social networks and the job search behavior of unemployed individuals. It is believed that networks convey useful information in the job search process such that individuals with larger networks should experience a higher productivity of informal search. Hence, job search theory suggests that individuals with larger networks use informal search channels more often and substitute from formal to informal search. Due to the increase in search productivity, it is also likely that individuals set higher reservation wages. We analyze these relations using a novel data set of unemployed individuals in Germany containing extensive information on job search behavior and direct measures for the social network of individuals. Our findings confirm theoretical expectations. Individuals with larger networks use informal search channels more often and shift from formal to informal search. We find that informal search is mainly considered a substitute for passive, less cost intensive search channels. In addition to that, we find evidence for a positive relationship between the network size and reservation wages.job search behavior, unemployment, social networks

Relaxation Tribometry: A Generic Method to Identify the Nature of Contact Forces

Recent years have witnessed the development of so-called relaxation tribometers, the free oscillation of which is altered by the presence of frictional stresses within the contact. So far, analysis of such oscillations has been restricted to the shape of their decaying envelope, to identify in particular solid or viscous friction components. Here, we present a more general expression of the forces possibly acting within the contact , and retain six possible, physically relevant terms. Two of them, which had never been proposed in the context of relaxation tribometry, only affect the oscillation frequency, not the amplitude of the signal. We demonstrate that each of those six terms has a unique signature in the time-evolution of the oscillation, which allows efficient identification of their respective weights in any experimental signal. We illustrate our methodology on a PDMS sphere/glass plate torsional contact

Correlating low energy impact damage with changes in modal parameters: diagnosis tools and FE validation

This paper presents a basic experimental technique and simplified FE based models for the detection, localization and quantification of impact damage in composite beams around the BVID level. Detection of damage is carried out by shift in modal parameters. Localization of damage is done by a topology optimization tool which showed that correct damage locations can be found rather efficiently for low-level damage. The novelty of this paper is that we develop an All In One (AIO) package dedicated to impact identification by modal analysis. The damaged zones in the FE models are updated by reducing the most sensitive material property in order to improve the experimental/numerical correlation of the frequency response functions. These approximate damage models(in term of equivalent rigidity) give us a simple degradation factor that can serve as a warning regarding structure safety

Learning and Designing Stochastic Processes from Logical Constraints

Stochastic processes offer a flexible mathematical formalism to model and reason about systems. Most analysis tools, however, start from the premises that models are fully specified, so that any parameters controlling the system's dynamics must be known exactly. As this is seldom the case, many methods have been devised over the last decade to infer (learn) such parameters from observations of the state of the system. In this paper, we depart from this approach by assuming that our observations are {\it qualitative} properties encoded as satisfaction of linear temporal logic formulae, as opposed to quantitative observations of the state of the system. An important feature of this approach is that it unifies naturally the system identification and the system design problems, where the properties, instead of observations, represent requirements to be satisfied. We develop a principled statistical estimation procedure based on maximising the likelihood of the system's parameters, using recent ideas from statistical machine learning. We demonstrate the efficacy and broad applicability of our method on a range of simple but non-trivial examples, including rumour spreading in social networks and hybrid models of gene regulation