Lithium battery disassembly process intelligent optimization method based on knowledge graph
By employing a knowledge graph-based intelligent optimization method for lithium battery dismantling processes, utilizing Monte Carlo tree search and fast random simulation, the efficient, safe, and adaptive optimization of the lithium battery dismantling process is achieved, solving the problem of low efficiency in existing technologies.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHANGSHENG XINLIAN ECOLOGICAL IND DEVELOPMENT CO LTD
- Filing Date
- 2026-05-25
- Publication Date
- 2026-07-17
AI Technical Summary
Existing lithium battery dismantling methods are inefficient, struggle to search for the globally optimal sequence in a complex solution space with intertwined high-dimensional constraints, and require global re-searching when faced with sudden anomalies, resulting in low dismantling efficiency and insufficient safety.
A knowledge graph-based intelligent optimization method for lithium battery dismantling processes is adopted. By acquiring quality indicators of lithium battery dismantling sequences and monitoring constraint satisfaction, combined with Monte Carlo tree search iteration and fast random simulation, dynamic adjustment and local repair are achieved, avoiding global re-search.
It improves the efficiency and safety of lithium battery disassembly, reduces computational overhead, enhances adaptability and anomaly diagnosis accuracy, and ensures the continuity and efficiency of the disassembly process.
Smart Images
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