Multi-criteria decision making (MCDM) for the selection of Li-ion batteries used in electric vehicles (EVs)

Abstract Battery-operated electrical vehicles are gradually replacing combustion engine-based vehicles. However, this is happening at a very slow pace as the development of better performing batteries are still underway. Rapid charging, long range driving, longest battery life and low cost are the stringent requirements to be met in developing battery technology. The most widely used Lithium-ion (Li-ion) batteries have managed to deliver a reasonable performance, but with high cost and shorter life span. The materials used for electrodes play a vital role in deciding the battery performance, cost, and life. The Li-ion batteries, which are currently in use, are classified based on the material used in making electrodes. The practical issue is that the EV manufacturers do find it difficult to select a best Li-ion battery, in order to strike a trade-off between performance, cost, and life. In this paper, an MCDM based methodology for the selection of Li-ion batteries that are categories based on cathode/ anode material, is proposed. The method is useful for the EV OEMs (Original Equipment Manufacturers) in selection of the best battery, and to optimize the cost, and the performance of the EVs.

[1]  Umang Soni,et al.  Green supplier selection using multi-criterion decision making under fuzzy environment: A case study in automotive industry , 2019, Comput. Ind. Eng..

[2]  Annette von Jouanne,et al.  Current Li-Ion Battery Technologies in Electric Vehicles and Opportunities for Advancements , 2019, Energies.

[3]  Zhitao Liu,et al.  A reliability-based design concept for lithium-ion battery pack in electric vehicles , 2015, Reliab. Eng. Syst. Saf..

[4]  Masayuki Morimoto,et al.  Which is the First Electric Vehicle? , 2015 .

[5]  S. Rajesham,et al.  Determination of LDR in deep drawing using reduced number of blanks , 2018 .

[6]  Evangelos Triantaphyllou,et al.  Multi-criteria Decision Making Methods: A Comparative Study , 2000 .

[7]  Jan Erik Vinnem,et al.  Decisions and decision support for major accident prevention in the process industries , 2015 .

[8]  Ajith Tom James,et al.  Development of methodology for the disassemblability index of automobile systems using a structural approach , 2017 .

[9]  J. M. Tarascon The Li-Ion Battery: 25 Years of Exciting and Enriching Experiences , 2016 .

[10]  Xiaoqing Zhu,et al.  Overcharge investigation of large format lithium-ion pouch cells with Li(Ni0.6Co0.2Mn0.2)O2 cathode for electric vehicles: Thermal runaway features and safety management method , 2019, Energy.

[11]  Jun Luo,et al.  Advanced Matrixes for Binder‐Free Nanostructured Electrodes in Lithium‐Ion Batteries , 2020, Advanced materials.

[12]  S. G. Deshmukh,et al.  Fault diagnosis of automobile systems using fault tree based on digraph modeling , 2018, Int. J. Syst. Assur. Eng. Manag..

[13]  Doron Aurbach,et al.  Review—Recent Advances and Remaining Challenges for Lithium Ion Battery Cathodes I. Nickel-Rich, LiNixCoyMnzO2 , 2017 .

[14]  Sean Parkin,et al.  A fast, inexpensive method for predicting overcharge performance in lithium-ion batteries , 2014 .

[15]  Mk Loganathan,et al.  Functional cause analysis of complex manufacturing systems using structure , 2015 .

[16]  ChangKyoo Yoo,et al.  Multi-scale smart management of integrated energy systems, Part 2: Weighted multi-objective optimization, multi-criteria decision making, and multi-scale management (3M) methodology , 2019, Energy Conversion and Management.

[17]  Mallikarjuna N. Nadagouda,et al.  Electrode materials for lithium-ion batteries , 2018, Materials Science for Energy Technologies.

[18]  R. Venkata Rao,et al.  Decision Making in Manufacturing Environment Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods , 2013 .

[19]  Jun Yang,et al.  Classification and Review of the Charging Strategies for Commercial Lithium-Ion Batteries , 2019, IEEE Access.

[20]  Athanasios G. Konstandopoulos,et al.  Synthesis and characterization of LNMO cathode materials for lithium-ion batteries , 2018 .

[21]  Yi Cui,et al.  Challenges and opportunities towards fast-charging battery materials , 2019, Nature Energy.

[22]  J. Goodenough,et al.  Monodisperse porous LiFePO4 microspheres for a high power Li-ion battery cathode. , 2011, Journal of the American Chemical Society.

[23]  John B. Goodenough,et al.  Lithium insertion into manganese spinels , 1983 .

[24]  Xuning Feng,et al.  Influence of aging paths on the thermal runaway features of lithium-ion batteries in accelerating rate calorimetry tests , 2019, International Journal of Electrochemical Science.