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A multi-agent AI framework for explainable battery system maintenance
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DOI：10.1016/j.xcrp.2026.103388.png)
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Abstract
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• Propose a multi-agent framework for explainable battery system maintenance • Multi-agent framework fuses data and knowledge for explainable decisions • Validation conducted on 8 months of field data with 3,564 cells under 444 operations • Maintenance insights cut response time and cost by over 80% versus experts
Keywords:
battery energy-storage system
operation and maintenance
multi-agent system
large language model
inconsistency evaluation
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