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The article presents a multi-agent simulation utilizing fuzzy logic to explore battery recharging management for Autonomous Industrial Vehicles (AIVs). This approach offers adaptability and resilience through a distributed system, accommodating variations in AIV battery capacity. Results highlight the efficacy of adaptive fuzzy multi-agent models in optimizing recharging strategies, enhancing operational efficiency, and curbing energy consumption. Dynamic factors like workload variations and AIV-infrastructure communication are considered in the form of heuristics, emphasizing the significance of flexible, collaborative approaches in autonomous systems. Notably, infrastructure capable of optimizing recharging based on energy tariffs can significantly reduce consumption during peak hours, emphasizing the importance of such strategies in dynamic environments. Overall, the study underscores the potential of incorporating adaptive fuzzy multi- agent models for AIV energy management to drive efficiency and sustainability in industrial operations.