Special Issue "Performance Test and Thermo-Mechanical Modeling of Lithium Batteries"

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "Advanced Energy Materials".

Deadline for manuscript submissions: 30 November 2021.

Special Issue Editor

Prof. Dr. Aurelio Somà
E-Mail Website
Guest Editor
Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy
Interests: machine design; multiphysics FEM modeling; MEMS and microsystems; battery modeling and testing; electric and hybrid vehciles

Special Issue Information

Dear Colleagues,

Lithium-ion batteries are increasingly used in many vehicle applications and will play a decisive role in achieving a more sustainable and green transportation system. In new battery devices, higher capacity and reliability requires accurate modeling and improved testing capabilities. Considering different physical domains, including electrochemical and mechanical stress and thermomechanical dynamics, this research field includes a strong multidisciplinary approach to multiphysics simulation. Identification and validation of simulation results require performance battery testing with attention to microstructure studies and sensor technologies.

The main objective of this Special Issue is to display recent research efforts contributing to advances in Li-Ion battery performance with particular attention to coupled domain simulation and testing.

Authors are invited to submit original manuscripts for review and for publication in this Special Issue. Original research and practical contributions as well as state-of-the-art reviews are welcome.

Prof. Dr. Aurelio Somà
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Multiphysics modeling
  • Testing and sensor integration
  • Themomechanical battery modeling
  • Mechanical battery failure modeling
  • Mechanical–electrochemical battery model
  • Battery dynamic testing

Published Papers (3 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Article
Generalized Peukert Equations Use for Finding the Remaining Capacity of Lithium-Ion Cells of Any Format
Energies 2021, 14(16), 5009; https://doi.org/10.3390/en14165009 - 15 Aug 2021
Viewed by 345
Abstract
In many studies, for predicting the remaining capacity of batteries belonging to different electrochemical systems, various analytical models based on the Peukert equation are used. This paper evaluates the advantages and disadvantages of the most famous generalized Peukert equations. For lithium-ion batteries, the [...] Read more.
In many studies, for predicting the remaining capacity of batteries belonging to different electrochemical systems, various analytical models based on the Peukert equation are used. This paper evaluates the advantages and disadvantages of the most famous generalized Peukert equations. For lithium-ion batteries, the Peukert equation cannot be used for estimation of their remaining capacity over the entire range of discharge currents. However, this paper proves that the generalized Peukert equations enable estimation of the capacity released by lithium-ion batteries with high accuracy. Special attention is paid to two generalized Peukert equations: C = Cm/(1 + (i/i0)n) and C = Cmerfc((i-i0)/n))/erfc(-i0/n). It is shown that they correspond to the experimental data the best. Full article
(This article belongs to the Special Issue Performance Test and Thermo-Mechanical Modeling of Lithium Batteries)
Show Figures

Figure 1

Article
State-of-Charge Estimation of Lithium-Ion Batteries in the Battery Degradation Process Based on Recurrent Neural Network
Energies 2021, 14(2), 306; https://doi.org/10.3390/en14020306 - 08 Jan 2021
Cited by 4 | Viewed by 671
Abstract
Due to the rapidly increasing energy demand and the more serious environmental pollution problems, lithium-ion battery is more and more widely used as high-efficiency clean energy. State of Charge (SOC) representing the physical quantity of battery remaining energy is the most critical factor [...] Read more.
Due to the rapidly increasing energy demand and the more serious environmental pollution problems, lithium-ion battery is more and more widely used as high-efficiency clean energy. State of Charge (SOC) representing the physical quantity of battery remaining energy is the most critical factor to ensure the stability and safety of lithium-ion battery. The novelty SOC estimation model, which is two recurrent neural networks with gated recurrent units combined with Coulomb counting method is proposed in this paper. The estimation model not only takes voltage, current, and temperature as input feature but also takes into account the influence of battery degradation process, including charging and discharging times, as well as the last discharge charge. The SOC of the battery is estimated by the network under three different working conditions, and the results show that the average error of the proposed neural network is less than 3%. Compared with other neural network structures, the proposed network estimation results are more stable and accurate. Full article
(This article belongs to the Special Issue Performance Test and Thermo-Mechanical Modeling of Lithium Batteries)
Show Figures

Figure 1

Article
Shape Influence of Active Material Micro-Structure on Diffusion and Contact Stress in Lithium-Ion Batteries
Energies 2021, 14(1), 134; https://doi.org/10.3390/en14010134 - 29 Dec 2020
Cited by 1 | Viewed by 681
Abstract
Electrochemical-mechanical modelling is a key issue to estimate the damage of active material, as direct measurements cannot be performed due to the particles nanoscale. The aim of this paper is to overcome the common assumptions of spherical and standalone particle, proposing a general [...] Read more.
Electrochemical-mechanical modelling is a key issue to estimate the damage of active material, as direct measurements cannot be performed due to the particles nanoscale. The aim of this paper is to overcome the common assumptions of spherical and standalone particle, proposing a general approach that considers a parametrized particle shape and studying its influence on the mechanical stresses which arise in active material particles during battery operation. The shape considered is a set of ellipsoids with variable aspect ratio (elongation), which aims to approximate real active material particles. Active material particle is divided in two domains: non-contact domain and contact domain, whether contact with neighbouring particles affects stress distribution or not. Non-contact areas are affected by diffusion stress, caused by lithium concentration gradient inside particles. Contact areas are affected simultaneously by diffusion stress and contact stress, caused by contact with neighbouring particles as a result of particle expansion due to lithium insertion. A finite element model is developed in Ansys™APDL to perform the multi-physics computation in non-spherical domain. The finite element model is validated in the spherical case by analytical models of diffusion and contact available for simple geometry. Then, the shape factor is derived to describe how particle shape affects mechanical stress in non-contact and contact domains. Full article
(This article belongs to the Special Issue Performance Test and Thermo-Mechanical Modeling of Lithium Batteries)
Show Figures

Graphical abstract

Back to TopTop