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Pollution control

Systematic Evaluation and Policy Optimization for Spent Lithium Battery Recycling

Strategic Insights

— 2 min read

Research on spent lithium battery recycling and evaluation methods has been conducted to address the challenges in energy consumption efficiency, pollution control, element recovery rate, and process versatility. The study, conducted by researchers from China Jiliang University, aimed to systematically review the current status of spent lithium battery recycling and evaluate the characteristics of existing evaluation methods. The researchers analyzed the advantages and limitations of Life Cycle Assessment (LCA), Techno-Economic Assessment (TEA), Criticality Assessment (CA), Material Flow Analysis (MFA), Input-Output Analysis (IOA), Best Available Techniques Assessment (BAT), Agent-Based Modeling (ABM), and the application of multi-method coupling. The study proposed strategies to improve evaluation efficacy through dynamic optimization, coupling integration, and data-driven technologies.

Key Takeaways:

  • The recycling of spent lithium batteries faces significant challenges in terms of energy consumption efficiency, pollution control, element recovery rate, and process versatility.
  • Existing evaluation methods for spent lithium battery recycling, including LCA, TEA, CA, MFA, IOA, BAT, and ABM, each possess unique advantages and limitations.
  • The data-driven concept has enhanced evaluation research, but data scarcity and varying quality remain significant bottlenecks.
  • Machine learning and big data analysis can improve model accuracy and adaptability, but the quality and availability of data are crucial.
  • The study suggests that the government establish a unified data platform and introduce incentive policies to promote the scientific and green transformation of spent lithium battery recycling.
  • The research proposed strategies to improve evaluation efficacy through dynamic optimization, coupling integration, and data-driven technologies.
  • The study highlighted the need for a systematic evaluation and policy optimization to address the challenges in spent lithium battery recycling.

Statistics:

  • The amount of spent lithium batteries has surged sharply, with a sharp increase in recycling demands for resource circulation and environmental protection.
  • Evolving data-driven technologies and machine learning can enhance the accuracy and adaptability of evaluation models.
  • A unified data platform and incentive policies can promote the scientific and green transformation of spent lithium battery recycling.
  • The energy consumption efficiency, pollution control, element recovery rate, and process versatility of spent lithium battery recycling face significant challenges, necessitating urgent demands for systematic evaluation and policy optimization.

Sources:

  • Research On the Evaluation Method System for Recycling and Utilization of Spent Lithium Battery: Multi Method Collaboration and Data-driven Innovation Path. Journal of Energy Storage, 2025;134.
  • VerticalNews. New Information Technology Findings Reported from China Jiliang University (Research On the Evaluation Method System for Recycling and Utilization of Spent Lithium Battery: Multi Method Collaboration and Data-driven Innovation Path). Information Technology Newsweekly. November 4, 2025; p 443.

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