Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Engineering with Computers
Erschienen in: Engineering with Computers 1/2019

31.01.2018 | Original Article

Crash analysis of lithium-ion batteries using finite element based neural search analytical models

verfasst von: V. Vijayaraghavan, Li Shui, Akhil Garg, Xiongbin Peng, Vikas Pratap Singh

Erschienen in: Engineering with Computers | Ausgabe 1/2019

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

The electric operated road vehicles are frequently powered by lithium ion batteries due to its low cost and ease of manufacturing. However, unforeseen impacts in road conditions can lead to fire hazard due to short circuiting of the battery pack. The impact strength of the battery pack can hence provide a key design input for manufacturing next generation batteries with a durable safe limit. In this work, a finite element based neural search approach is proposed for determining the effects of various uncertain phenomena on the strength of the battery. The approach combines the actual impact mechanics of battery as determined by the finite element model along with the high accuracy and robustness provided by neural search algorithm. The derived model is able to satisfactorily predict the variances in the mechanical strength even with slightest uncertainties in the phenomena which can affect the strength of the battery pack. It is anticipated that the proposed model will be of utmost importance in design of next generation safe and durable lithium ion battery packs.
Vorheriger Artikel Solving viscoelastic problems with cyclic symmetry via a temporally adaptive EFG-SB partitioning algorithm
Nächster Artikel A new fast convergent iteration regularization method

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Literatur
1.
Arora S, Shen W, Kapoor A (2016) Review of mechanical design and strategic placement technique of a robust battery pack for electric vehicles. Renew Sustain Energy Rev 60:1319–1331CrossRef
2.
Brown S, Pyke D, Steenhof P (2010) Electric vehicles: The role and importance of standards in an emerging market. Energy Policy 38(7):3797–806CrossRef
3.
Chen SC, Wan CC, Wang YY (2005) Thermal analysis of lithium-ion batteries. J Power Sour 140(1):111–24CrossRef
4.
Cuma MU, Koroglu T (2015) A comprehensive review on estimation strategies used in hybrid and battery electric vehicles. Renew Sustain Energy Rev 42:517–31CrossRef
5.
Dai Y, Luo Y, Chu W, Li K (2014) Optimum tyre force distribution for four-wheel-independent drive electric vehicle with active front steering. Int J Veh Des 65(4):336–59CrossRef
6.
Dinger A, Martin R, Mosquet X, Rabl M, Rizoulis D, Russo M, Sticher G (2010) Batteries for electric cars: challenges, opportunities, and the outlook to 2020. Boston Consulting Group, San Francisco, USA
7.
8.
Dubarry M, Vuillaume N, Liaw BY (2008) From Li-ion single cell model to battery pack simulation. In control applications, 2008. CCA 2008. IEEE international conference on 2008 Sep 3. IEEE pp 708–713
9.
Fotouhi A, Auger DJ, Propp K, Longo S, Wild M (2016) A review on electric vehicle battery modelling: from lithium-ion toward lithium–sulphur. Renew Sustain Energy Rev 56:1008–1021CrossRef
10.
Gallardo-Lozano J, Romero-Cadaval E, Milanes-Montero MI, Guerrero-Martinez MA (2014) Battery equalization active methods. J Power Sour 246:934–49CrossRef
11.
Gong X, Xiong R, Mi CC (2015 Mar) Study of the characteristics of battery packs in electric vehicles with parallel-connected lithium-ion battery cells. IEEE Trans Ind Appl 51(2):1872–1879CrossRef
12.
Hanifah RA, Toha SF, Ahmad S (2015) Electric vehicle battery modelling and performance comparison in relation to range anxiety. Procedia Comput Sci 76:250–256CrossRef
13.
14.
Huo H, Zhang Q, Wang MQ, Streets DG, He K (2010) Environmental implication of electric vehicles in China. Environ Sci Technol 24(13):4856–4861 44(CrossRef
15.
Jaguemont J, Boulon L, Dubé Y (2016) A comprehensive review of lithium-ion batteries used in hybrid and electric vehicles at cold temperatures. Appl Energy 164:99–114CrossRef
16.
Barillas JK, Li J, Günther C, Danzer MA (2015) A comparative study and validation of state estimation algorithms for Li-ion batteries in battery management systems. Appl Energy 155:455–462CrossRef
17.
Nykvist B, Nilsson M (2015) Rapidly falling costs of battery packs for electric vehicles. Nat Clim Change 5(4):329–32CrossRef
18.
Sun F, Xiong R, He H (2016) A systematic state-of-charge estimation framework for multi-cell battery pack in electric vehicles using bias correction technique. Appl Energy 162:1399–1409CrossRef
19.
Sahraei E, Hill R, Wierzbicki T (2012) Calibration and finite element simulation of pouch lithium-ion batteries for mechanical integrity. J Power Sour 201:307–321CrossRef
20.
Sahraei E, Meier J, Wierzbicki T (2014) Characterizing and modeling mechanical properties and onset of short circuit for three types of lithium-ion pouch cells. J Power Sour 247:503–516CrossRef
21.
Tie SF, Tan CW (2013) A review of energy sources and energy management system in electric vehicles. Renew Sustain Energy Rev 20:82–102CrossRef
22.
Xiong R, Sun F, Gong X, Gao C (2014) A data-driven based adaptive state of charge estimator of lithium-ion polymer battery used in electric vehicles. Appl Energy 113:1421–1433CrossRef
23.
Wang XL, Han WQ, Chen H, Bai J, Tyson TA, Yu XQ, Wang XJ, Yang XQ (2011) Amorphous hierarchical porous GeO x as high-capacity anodes for Li ion batteries with very long cycling life. J Am Chem Soc 133(51):20692–20695CrossRef
24.
Wang H, Fu L, Bi J (2011) CO2 and pollutant emissions from passenger cars in China. Energy Policy 39(5):3005–3011CrossRef
25.
Wen X, Xiao C (2011) Electric vehicle key technology research in China. In: 2011 international aegean conference on electrical machines and power electronics and 2011 electromotion joint conference (ACEMP), 8 Sep 2011. IEEE, Istanbul, Turkey, pp 308–314. https://​doi.​org/​10.​1109/​ACEMP.​2011.​6490616
26.
Wierzbicki T, Sahraei E (2013) Homogenized mechanical properties for the jellyroll of cylindrical Lithium-ion cells. J Power Sour 241:467–476CrossRef
27.
Yarime M, Shiroyama H, Kuroki Y (2008) The strategies of the Japanese auto industry in developing hybrid and fuel cell vehicles. Making choices about hydrogen: transport issues for developing countries. United Nations University Press, USA, p 193
28.
Dufo-López R, Lujano-Rojas JM, Bernal-Agustín JL (2014) Comparison of different lead–acid battery lifetime prediction models for use in simulation of stand-alone photovoltaic systems. Appl Energy 115:242–253CrossRef
29.
Young K, Wang C, Wang LY, Strunz K (2013) Electric vehicle battery technologies. In: Electric vehicle integration into modern power networks. Springer, New York pp 15–56CrossRef
30.
Vijayaraghavan V, Garg A, Gao L, Vijayaraghavan R, Lu G (2016) A finite element based data analytics approach for modeling turning process of Inconel 718 alloys. J Clean Prod 137:1619–1627CrossRef
31.
Vijayaraghavan V, Garg A, Gao L, Vijayaraghavan R (2017) Finite element based physical chemical modeling of corrosion in magnesium alloys. Metals 7(3):83CrossRef
32.
Vijayaraghavan V, Garg A, Gao L (2018) Fracture mechanics modelling of lithium-ion batteries under pinch torsion test. Measurement 114:382–389CrossRef
33.
Huang Y, Gao L, Yi Z, Tai K, Kalita P, Prapainainar P, Garg A (2018) An application of evolutionary system identification algorithm in modelling of energy production system. Measurement 114:122–131CrossRef
34.
Garg A, Vijayaraghavan V, Zhang J, Li S, Liang X (2017) Design of robust battery capacity model for electric vehicle by incorporation of uncertainties. Int J Energy Res 41(10):1436–1451CrossRef
35.
36.
Garg A, Li J, Hou J, Berretta C, Garg A (2017) A new computational approach for estimation of wilting point for green infrastructure. Measurement 111:351–358CrossRef
Metadaten
Titel
Crash analysis of lithium-ion batteries using finite element based neural search analytical models
verfasst von
V. Vijayaraghavan
Li Shui
Akhil Garg
Xiongbin Peng
Vikas Pratap Singh
Publikationsdatum
31.01.2018
Verlag
Springer London
Erschienen in
Engineering with Computers / Ausgabe 1/2019
Print ISSN: 0177-0667
Elektronische ISSN: 1435-5663
DOI
https://doi.org/10.1007/s00366-018-0587-5

Weitere Artikel der Ausgabe 1/2019

Engineering with Computers 1/2019 Zur Ausgabe

Original Article

The effect of ICA and PSO on ANN results in approximating elasticity modulus of rock material

Original Article

Designing a fuzzy cognitive map to evaluate drilling and blasting problems of the tunneling projects in Iran

Original Article

Adaptive analysis of plates and laminates using natural neighbor Galerkin meshless method

Original Article

Parts internal structure definition using non-uniform patterned lattice optimization for mass reduction in additive manufacturing

Original Article

ARTMe: a new array-based algorithm for Adaptive Refinement of Triangle Meshes

Original Article

Numerical solution of a time-fractional PDE in the electroanalytical chemistry by a local meshless method

Neuer Inhalt

    Bildnachweise