云控电池管理平台内短路、异常发热安全预警算法数据集

本任务基于研制的长寿命、高能量密度的全气候快充电池系统，针对电池使用过程中的热失控、内短路等安全风险，开发云控BMS管理终端、云控电池管理平台及高精度电池内短路模型，并通过系列实验验证内短路特性与模型准确性；最终构建电池全生命周期动态安全监控体系，实现对电池状态的实时监测、风险预警与精准管控。数据内容包括预警算法设计文档、内短路/异常发热案例数据和第三方测试报告/数据，研究成果为换电重卡行业突破核心技术瓶颈、提升安全运营水平提供重要技术支撑，对推动重卡行业低碳转型与可持续发展具有重要实践意义。数据量200MB。

This task is based on the developed all-climate fast-charging battery system with long service life and high energy density. Aiming at the safety risks such as thermal runaway and internal short circuit during battery operation, we developed a cloud-controlled BMS management terminal, a cloud-controlled battery management platform, and a high-precision battery internal short circuit model, and verified the internal short circuit characteristics and the accuracy of the model through a series of experiments. Finally, a dynamic safety monitoring system for the entire lifecycle of batteries was constructed, enabling real-time monitoring, risk early warning and precise control of battery status. The data includes early warning algorithm design documents, internal short circuit/abnormal heating case data, and third-party test reports and related data. The research results provide important technical support for the battery-swapping heavy truck industry to break through core technical bottlenecks and improve safe operation levels, and have significant practical significance for promoting the low-carbon transformation and sustainable development of the heavy truck industry. The total data volume is 200 MB.

搜集汇总

背景与挑战

背景概述

该数据集针对电池热失控和内短路等安全风险，基于云控电池管理平台开发了预警算法和内短路模型，并通过实验验证。数据包含算法文档、案例及测试报告，旨在为换电重卡行业提供安全监控技术支撑，推动低碳可持续发展。