Systematic derivation and validation of a reduced thermal-electrochemical model for lithium-ion batteries using asymptotic methods

Planella, Ferran Brosa; Sheikh, Muhammad Aman; Widanage, Widanalage Dhammika

doi:10.1016/j.electacta.2021.138524

Cited by 27 publications

(33 citation statements)

References 30 publications

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“…While some authors take an ad hoc approach, posing the model directly from a list of simplifying assumptions [11,46,47,58,85], others (particularly in the mathematical modelling community) use formal asymptotic methods to systematically derive the reduced order models directly from the DFN model. Over the past few years, several authors have applied asymptotic methods to the DFN model to derive reduced order battery models [13,81,86,109,111]. The exact form of the model that results from this process depends upon the underlying assumptions on which the asymptotic analysis is based.…”

Section: Doyle-fuller-newman Model To Single Particle Modelmentioning

confidence: 99%

“…There are further simplifications that can be applied to these models, such as fast lithium transport in the electrode particles, see e.g. [86,109], but we do not discuss these here, and instead refer the reader to [13].…”

Section: Doyle-fuller-newman Model To Single Particle Modelmentioning

confidence: 99%

“…In the uniform electrodes problem we can use the explicit expressions shown in Table 2, and the details on the derivation follow very similarly to the analysis in [13]. In the graded electrode case, we need to solve (30) numerically.…”

Section: Accepted Manuscriptmentioning

confidence: 99%

“…The main advantage of this model is that it retains most of the simplicity of the SPM, in the sense that it is still one-dimensional in space (albeit that three decoupled one-dimensional problems must be solved), but provides a significant improvement in performance. Recall that, as explained at the beginning of Section 3, the SPMe refers to a family of models (of which [13,81,111] are particular instances) so the points discussed here apply to all the particular examples of SPMe.…”

Section: Single Particle Models With Electrolyte Dynamics (Spme)mentioning

confidence: 99%

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A continuum of physics-based lithium-ion battery models reviewed

Planella

Boyce

et al. 2022

Prog. Energy

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Physics-based electrochemical battery models derived from porous electrode theory are a very powerful tool for understanding lithium-ion batteries, as well as for improving their design and management. Different model fidelity, and thus model complexity, is needed for different applications. For example, in battery design we can afford longer computational times and the use of powerful computers, while for real-time battery control (e.g. in electric vehicles) we need to perform very fast calculations using simple devices. For this reason, simplified models that retain most of the features at a lower computational cost are widely used. Even though in the literature we often find these simplified models posed independently, leading to inconsistencies between models, they can actually be derived from more complicated models using a unified and systematic framework. In this review, we showcase this reductive framework, starting from a high-fidelity microscale model and reducing it all the way down to the Single Particle Model (SPM), deriving in the process other common models, such as the Doyle-Fuller-Newman (DFN) model. We also provide a critical discussion on the advantages and shortcomings of each of the models, which can aid model selection for a particular application. Finally, we provide an overview of possible extensions to the models, with a special focus on thermal models. Any of these extensions could be incorporated into the microscale model and the reductive framework re-applied to lead to a new generation of simplified, multi-physics models.

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Section: Doyle-fuller-newman Model To Single Particle Modelmentioning

confidence: 99%

Section: Doyle-fuller-newman Model To Single Particle Modelmentioning

confidence: 99%

Section: Accepted Manuscriptmentioning

confidence: 99%

Section: Single Particle Models With Electrolyte Dynamics (Spme)mentioning

confidence: 99%

See 2 more Smart Citations

A continuum of physics-based lithium-ion battery models reviewed

Planella

Boyce

et al. 2022

Prog. Energy

Self Cite

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show abstract

“…Once published, we suggest that the filled-out checklist be a part of the Supporting Information and provide the necessary background to the readers. To give examples of filled-out checklists for different theoretical studies, each author populated a checklist for at least one of their published articles. ,,,− We aimed to cover many different types of battery modeling paradigms in the author-populated checklists. It also serves as a good starting reference for battery modeling best practices and shortcomings.…”

mentioning

confidence: 99%