储能系统热失控预警专识数据集

本数据集聚焦电化学储能系统热失控前兆特征与预警建模，覆盖磷酸铁锂、三元锂、钛酸锂等主流电池体系及过充电、短路、高温等典型诱因。数据内容包括电池元数据、时间与环境参数、电学特征（电压、电流、内阻）、热特征（温度、温升速率）、特征气体浓度（CO、H₂、TVOC）及热失控风险标签（预警等级、实际热失控时间、预警提前量）。适用于热失控预警模型训练、阈值优化、故障演化分析及储能安全大模型开发等场景。This dataset focuses on the precursor feature extraction and early warning modeling of thermal runaway for electrochemical energy storage systems. It covers mainstream battery systems including lithium iron phosphate (LFP), ternary lithium-ion, and lithium titanate (LTO), as well as typical triggers such as overcharging, short-circuiting, and high-temperature exposure. The dataset contains battery metadata, temporal and environmental parameters, electrical characteristics (voltage, current, internal resistance), thermal characteristics (temperature, temperature rise rate), characteristic gas concentrations (CO, H₂, TVOC), and thermal runaway risk labels (early warning level, actual thermal runaway time, early warning lead time). It is suitable for scenarios including thermal runaway early warning model training, threshold optimization, fault evolution analysis, and development of energy storage safety large language models.

搜集汇总

背景与挑战

背景概述

该数据集专注于电化学储能系统的热失控预警，涵盖磷酸铁锂、三元锂等主流电池体系在过充电、短路等诱因下的多维度数据，包括电学、热学和气体特征，并标注了预警等级与热失控标签。它适用于热失控预警模型训练、阈值优化及储能安全大模型开发等应用场景。