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<p>This study addresses the critical challenge of selecting thermally stable and safe cathode materials for lithium-ion batteries, which is necessary to enhance battery reliability and to prevent thermal runaway in advanced energy storage systems. To resolve this issue, a novel hybrid multi-criteria decision-making framework combining the ordinal priority approach in an intuitionistic fuzzy environment (OPA-IF) and grey relational analysis (GRA) is proposed in this work. The OPA-IF method is employed to obtain uncertainty-aware criterion weights, while GRA is used to evaluate and rank alternative materials based on multiple thermal and electrochemical parameters. The results indicate that the proposed framework provides consistent and robust ranking outcomes, with the top-ranked cathode materials (i.e., NMC111, NMC-811, LFP, NCA, LCO, and LMO) exhibiting superior performance across key criteria such as heat produced by parasitic reaction, internal resistance, electrical energy required during charging, volumetric capacity, and thermal conductivity. The ranking consistency is validated using Spearman’s correlation coefficients (ρ &gt; 0.94), indicating strong agreement with comparative methods such as GRA, AHP-GRA, BWM-GRA, and FUCOM-GRA. Furthermore, sensitivity analysis confirms the stability of rankings across variations in criterion weights, with no significant rank reversal observed. The obtained results are further validated by COMSOL-based simulation, which shows favorable cycling performance for the graphite-NCA configuration, with about 86% capacity retention even after 2000 charge–discharge cycles under the adopted 1D isothermal model. Overall, the proposed OPA-IF-GRA framework provides a practical and reliable decision-support tool for screening cathode materials toward safer, more stable, and high-performance LIB systems.</p>

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Multi-Criteria Decision-Making for LIB Cathode Selection: An OPA-IF-GRA Approach with Simulation Validation

  • 期刊论文

  • 发表日期：

    2026年6月26日

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  • Tushar Kanti Das,
  • Anup Kumar Sharma,
  • Munmun Khanra,
  • Priyanka Majumder

摘要

This study addresses the critical challenge of selecting thermally stable and safe cathode materials for lithium-ion batteries, which is necessary to enhance battery reliability and to prevent thermal runaway in advanced energy storage systems. To resolve this issue, a novel hybrid multi-criteria decision-making framework combining the ordinal priority approach in an intuitionistic fuzzy environment (OPA-IF) and grey relational analysis (GRA) is proposed in this work. The OPA-IF method is employed to obtain uncertainty-aware criterion weights, while GRA is used to evaluate and rank alternative materials based on multiple thermal and electrochemical parameters. The results indicate that the proposed framework provides consistent and robust ranking outcomes, with the top-ranked cathode materials (i.e., NMC111, NMC-811, LFP, NCA, LCO, and LMO) exhibiting superior performance across key criteria such as heat produced by parasitic reaction, internal resistance, electrical energy required during charging, volumetric capacity, and thermal conductivity. The ranking consistency is validated using Spearman’s correlation coefficients (ρ > 0.94), indicating strong agreement with comparative methods such as GRA, AHP-GRA, BWM-GRA, and FUCOM-GRA. Furthermore, sensitivity analysis confirms the stability of rankings across variations in criterion weights, with no significant rank reversal observed. The obtained results are further validated by COMSOL-based simulation, which shows favorable cycling performance for the graphite-NCA configuration, with about 86% capacity retention even after 2000 charge–discharge cycles under the adopted 1D isothermal model. Overall, the proposed OPA-IF-GRA framework provides a practical and reliable decision-support tool for screening cathode materials toward safer, more stable, and high-performance LIB systems.