journal article·2021-12-27

Beneficial Effects of Three-Dimensional Structured Electrodes for the Fast Charging of Lithium-Ion Batteries

Vittorio De Lauri, Lukas Krumbein, Simon Hein, Benedikt Prifling, Volker Schmidt, Timo Danner, Arnulf Latz

ACS Applied Energy Materials· Volume 4· Issue 12
Publisher page

Abstract

Lithium-ion batteries are the dominating electrochemical energy storage technology for battery electric vehicles. However, additional optimization is needed to meet the requirements of the automotive industry regarding energy density, cost, safety, and fast charging performance. In conventional electrode designs, there is a trade-off between energy density and rate capability. Recently, three-dimensional (3D) structuring techniques, such as laser perforation, were proposed to optimize both properties at the same time and remarkable improvements in fast-charging performance have been demonstrated. In this work, we investigate the effect of structuring techniques on the thermal properties and electrochemical performance of the battery using microstructure-resolved simulations. Particular attention will be paid to the heat evolution and lithium plating during fast charging of the batteries. According to our results, 3D structuring is able to reduce the overall cell resistance by improving the electrolyte transport. This has a positive impact on the fast charging capability of the cell and, moreover, reduces the danger of lithium plating.
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Research context

OpenAlex topics: Advanced Battery Technologies Research · Advancements in Battery Materials · Supercapacitor Materials and Fabrication

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Institute of Engineering Thermodynamics, German Aerospace Center (DLR), Pfaffenwaldring 38-40, 70 569 Stuttgart, Germany

Helmholtz-Institute Ulm for Electrochemical Energy Storage (HIU), Helmholtzstraße 11, 89 081 Ulm, Germany

University of Modena and Reggio Emilia, Via Universita 4, 41 121 Modena, Italy

Institute of Stochastics, Ulm University (UUlm), Helmholtzstraße 18, 89 081 Ulm, Germany

Institute of Electrochemistry, Ulm University (UUlm), Albert-Einstein-Allee 47, 89 081 Ulm, Germany

Funding

Bundesministerium f??r Bildung und Forschung · Deutsche Forschungsgemeinschaft

References (56)

Show source-provided references
1. 10.1016/j.ecolecon.2014.09.02110.1016/j.ecolecon.2014.09.021 ↗
2. 10.1038/s41893-019-0328-910.1038/s41893-019-0328-9 ↗
3. Longo, M.; Zaninelli, D.; Viola, F.; Romano, P.; Miceli, R. How Is the Spread of the Electric Vehicles? 1st International Forum on Research and Technologies for Society and Industry Leveraging a Better Tomorrow (RTSI), 2015; pp 439–445.10.1109/RTSI.2015.7325137 ↗
4. 10.1016/j.jpowsour.2017.06.05510.1016/j.jpowsour.2017.06.055 ↗
5. 10.1149/2.0321602jes10.1149/2.0321602jes ↗
6. 10.1002/aenm.20190016110.1002/aenm.201900161 ↗
7. 10.1038/nenergy.2016.9710.1038/nenergy.2016.97 ↗
8. 10.1016/j.jpowsour.2020.22847510.1016/j.jpowsour.2020.228475 ↗
9. 10.1002/ese3.4710.1002/ese3.47 ↗
10. 10.1515/nanoph-2017-004410.1515/nanoph-2017-0044 ↗
11. 10.1007/s10800-017-1047-410.1007/s10800-017-1047-4 ↗
12. 10.1016/j.apenergy.2014.11.05110.1016/j.apenergy.2014.11.051 ↗
13. 10.1021/acs.jpclett.8b0222910.1021/acs.jpclett.8b02229 ↗
14. 10.1016/j.jpowsour.2016.09.14310.1016/j.jpowsour.2016.09.143 ↗
15. 10.1016/j.jpowsour.2020.22894810.1016/j.jpowsour.2020.228948 ↗
16. 10.1016/j.apenergy.2021.11769310.1016/j.apenergy.2021.117693 ↗
17. 10.1149/2.0062001jes10.1149/2.0062001jes ↗
18. 10.1002/aenm.20180247210.1002/aenm.201802472 ↗
19. 10.1149/2.0151508jes10.1149/2.0151508jes ↗
20. 10.1039/b205634h10.1039/b205634h ↗
21. 10.1002/adma.20120405510.1002/adma.201204055 ↗
22. 10.1038/nenergy.2016.9910.1038/nenergy.2016.99 ↗
23. US Department of Energy. Battery500: Progress Update. 2020, https://www.energy.gov/eere/articles/battery500-progress-update.
24. 10.1149/2.1181807jes10.1149/2.1181807jes ↗
25. 10.1149/2.1241915jes10.1149/2.1241915jes ↗
26. 10.2351/7.000007810.2351/7.0000078 ↗
27. 10.1016/j.electacta.2020.13603410.1016/j.electacta.2020.136034 ↗
28. 10.1016/j.electacta.2020.13601310.1016/j.electacta.2020.136013 ↗
29. ITWM. BEST─Battery and Electrochemistry Simulation Tool. 2020, http://itwm.fraunhofer.de/best.
30. 10.1016/j.jpowsour.2010.11.08810.1016/j.jpowsour.2010.11.088 ↗
31. 10.1016/j.electacta.2013.06.04310.1016/j.electacta.2013.06.043 ↗
32. 10.3762/bjnano.6.10210.3762/bjnano.6.102 ↗
33. 10.1149/2.047304jes10.1149/2.047304jes ↗
34. 10.1149/2.0641503jes10.1149/2.0641503jes ↗
35. 10.1016/j.jpowsour.2013.12.02210.1016/j.jpowsour.2013.12.022 ↗
36. 10.1002/aenm.20150130910.1002/aenm.201501309 ↗
37. 10.1149/1.152651210.1149/1.1526512 ↗
38. 10.1016/j.jpowsour.2016.10.04910.1016/j.jpowsour.2016.10.049 ↗
39. 10.1016/j.jpowsour.2017.07.10510.1016/j.jpowsour.2017.07.105 ↗
40. 10.1149/2.1141607jes10.1149/2.1141607jes ↗
41. 10.3390/en1105103310.3390/en11051033 ↗
42. 10.1186/s10033-018-0268-810.1186/s10033-018-0268-8 ↗
43. 10.1016/j.commatsci.2018.04.06010.1016/j.commatsci.2018.04.060 ↗
44. 10.1016/j.commatsci.2015.06.02510.1016/j.commatsci.2015.06.025 ↗
45. Adler R. · 1981
46. Chiu S. · 201310.1002/9781118658222 ↗
47. 10.1002/batt.20200009810.1002/batt.202000098 ↗
48. 10.1149/1945-7111/ab6b1d10.1149/1945-7111/ab6b1d ↗
49. 10.1002/ente.20190016710.1002/ente.201900167 ↗
50. 10.1016/j.electacta.2016.01.22010.1016/j.electacta.2016.01.220 ↗
51. 10.5796/electrochemistry.75.64910.5796/electrochemistry.75.649 ↗
52. 10.1016/j.jiec.2018.10.01210.1016/j.jiec.2018.10.012 ↗
53. 10.1021/acsaem.0c0115510.1021/acsaem.0c01155 ↗
54. 10.1021/acs.nanolett.6b0475510.1021/acs.nanolett.6b04755 ↗
55. 10.1016/j.joule.2020.12.02010.1016/j.joule.2020.12.020 ↗
56. 10.1016/j.jpowsour.2020.22818710.1016/j.jpowsour.2020.228187 ↗