Lithium-Ion Battery Degradation: How to Diagnose It
0
Citation
0
Reference
10
Related Paper
Abstract:
Many different degradation mechanisms occur in lithium-ion batteries, all of which interact with one another [1]. However, there are few fewer observable consequences of degradation than there are mechanisms [2]. It is possible to measure the different degradation modes: loss of lithium inventory (LLI), loss of active material (LAM), impedance change and stoichiometric drift [3]. It is not always possible to link these observable consequences of degradation to any particular mechanism or combination of mechanisms. Many models of degradation exist [4], but these models have many parameters that cannot be measured directly. A recent modelling study [5] found the number of parameters that the model is sensitive to is greater than the number of observable degradation modes. However, the same model [5], despite including just four degradation mechanisms, found five possible degradation pathways a battery can follow. The model was built so that more mechanisms can easily be added later, so more pathways will be found. In this work, a new approach to diagnosing battery degradation is proposed, based on these pathways. Experimental data for the degradation modes can be identified as being consistent with a particular pathway. Once the correct pathway is found, the parameters that particular pathway is sensitive to can be fit to the data, feeding back into the model. [1] Jacqueline Edge et al. , Phys. Chem.: Chem. Phys. vol. 23, pp. 8200-8221, 2021. [2] Christoph Birkl et al. , Journal of Power Sources vol. 341, pp. 373-386, 2017. [3] Matthieu Dubarry et al. , J. Electrochem. En. Conv. Stor. vol. 17, pp. 044701, 2020. [4] Jorn Reniers et al. , J. Electrochem. Soc. vol. 166 pp. A3189-A3200, 2019. [5] Simon O’Kane et al. , Phys. Chem.: Chem. Phys. , submitted, 2022. https://arxiv.org/abs/2112.02037Keywords:
Degradation
Cite
Citations (1)
We introduce the concepts of dual instruments and sub-observables. We show that although a dual instruments measures a unique observable, it determines many sub-observables. We define a unique minimal extension of a sub-observable to an observable and consider sequential products and conditioning of sub-observables. Sub-observable effect algebras are characterized and studied. Moreover, the convexity of these effect algebras is considered. The sequential product of instruments is discussed. These concepts are illustrated with many examples of instruments. In particular, we discuss L\"uders, Holero and constant state instruments. Various conjectures for future research are presented.
Convexity
Cite
Citations (0)
The observability of nonlinear systems was considered in this note. First, we reviewed the definitions and relations of observable, locally observable, weakly observable, locally weakly observable, uniformly locally weakly observable and completely uniformly locally weakly observable. Then, a sufficient condition under which a multi-output nonlinear system is completely uniformly locally weakly observable was given. The sufficient condition becomes necessary and sufficient condition when the system is single-output. We also gave a canonical form of these multi-output systems. In the end, an example illustrated how to use the given sufficient conditions to determine whether a nonlinear system is completely uniformly locally weakly observable.
Observability
Cite
Citations (0)
Abstract In statistical hydrology, three different methods have been used to calculate the expected values of observable quantities in an ensemble. The first is to use an observable as a parameter to characterize the “states” of the ensemble and then to calculate the average value of the observable over all possible states; this is the expected value. The second method is to use an observable as a parameter to characterize the “states” and then to designate the most probable value of the observable as the expected value; this is known as the “minimum variance principle”. Finally, the third method is to use a parameter different from an observable to characterize the “states” and then to take the value of the observable for the most probable state as the expected value. Of all these different methods, only the first one is, in principle, physically correct. Thus, a study was made to determine the situations where methods other than the first can be used to calculate the expectation values of observables. It was found that this can be done only in those situations where all of the following conditions hold: (i) The number of parameters used to characterize the states is finite; (ii) these parameters are either the same as the observables or are explicitly related to the observables; and (iii) each of the parameters has a symmetrical and unimodal probability distribution. The cases where the minimum variance principle is valid, are thereby delineated.
Value (mathematics)
Expected value
Cite
Citations (1)
Granularity
Dilation (metric space)
Cite
Citations (6)
We examine the problem of estimating the expectation values of two observables when we have a finite number of copies of an unknown qubit state. Specifically we examine whether it is better to measure each of the observables separately on different copies or to perform a separable nonadaptive joint measurement of the observables on each copy. We find that joint measurements can sometimes provide an advantage over separate measurements, but only if we make estimates of an observable based solely on the results of measurements of that observable. If we instead use both sets of results to estimate each observable then we find that individual measurements will be better. Finally we consider estimating the expectation values of three complementary observables for an unknown qubit.
Cite
Citations (14)
Cite
Citations (24)
We present a framework for computing averages of various observables of Macdonald processes. This leads to new contour--integral formulas for averages of a large class of multilevel observables, as well as Fredholm determinants for averages of two different single level observables.
Cite
Citations (0)
Cite
Citations (1)