储能电池“历史存量+实时增量”数据库
收藏国家基础学科公共科学数据中心2026-02-14 收录
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https://nbsdc.cn/general/dataDetail?id=698ca791195d267dc0b416f4&type=1
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资源简介:
本数据集由北京理工大学储能课题组与宁德时代新能源科技股份有限公司联合构建,旨在支持电池状态分析、性能评估、老化机理研究及故障诊断。数据集内容包含三部分:1. 常规循环数据:200块锂离子电池在实验室环境下的CC-CV充电循环运行数据(2023.9-2024.3),时间精度1s;2. 老化特性数据:9块宁德280Ah电池在不同放电深度(DOD 100%、60%、20%)及25℃恒温下的循环寿命测试数据(2022.12-2023.5);3. 真实工况数据:霞浦储能电站单柜单日的真实静态运行监测数据(2024.1.1)。数据涵盖电流、电压、功率、能量、温度、BMS状态及PCS参数等关键变量,格式统一,物理意义明确,能够全面表征储能电池在不同工况下的电化学响应与老化演化规律。
This dataset was jointly constructed by the Energy Storage Research Group of Beijing Institute of Technology and CATL (Contemporary Amperex Technology Co., Limited), aiming to support battery state analysis, performance evaluation, aging mechanism research and fault diagnosis. The dataset includes three parts:
1. Routine cycle data: Operational data of CC-CV charging cycles for 200 lithium-ion batteries in a laboratory environment (September 2023 to March 2024), with a time accuracy of 1 second;
2. Aging characteristic data: Cycle life test data of 9 CATL 280Ah lithium-ion batteries under different depths of discharge (DOD 100%, 60%, 20%) and constant 25°C temperature (December 2022 to May 2023);
3. Real working condition data: Real static operation monitoring data of a single cabinet of the Xiapu Energy Storage Power Station for one day (January 1, 2024).
The dataset covers key variables including current, voltage, power, energy, temperature, BMS (Battery Management System) status and PCS (Power Conversion System) parameters, with unified format and clear physical meanings. It can comprehensively characterize the electrochemical response and aging evolution laws of energy storage batteries under different working conditions.
提供机构:
北京理工大学
搜集汇总
数据集介绍

背景与挑战
背景概述
该数据集由北京理工大学与宁德时代联合构建,包含锂离子电池的常规循环、老化特性和真实工况三部分数据,时间跨度从2022年12月至2024年3月,涵盖电流、电压、温度等关键变量,旨在支持电池状态分析、性能评估和老化机理研究。数据总量为10.75GB,格式统一,能够全面表征储能电池在不同工况下的电化学响应与老化演化规律。
以上内容由遇见数据集搜集并总结生成



