高功率离子电池特征数据集用于随机电池建模
Muhammad Aadil Khan1, Sai Thatipamula1, Luigi Tresca1
1Department of Energy Science & Engineering, Stanford University, 367 Panama St., Stanford, 94305, CA, USA.
Scientific data
|August 28, 2025
概括
本研究提供了各种条件下的高功率离子电池 (LIB) 性能的新数据集. 这些数据捕获了电池变化,这对于开发电动汽车和飞机的精确电池模型至关重要.
科学领域:
- 材料科学
- 电化学
- 能量储存
背景情况:
- 高功率的离子电池 (LIB) 对电动汽车和eVTOL至关重要.
- 电池的降解 (例如涂层,颗粒裂变) 由高C率,温度和放电深度 (DOD) 加速.
- 有限的公共数据集用于高功率LIB的表征.
研究的目的:
- 为高功率LIB提供一个全面的特征数据集.
- 有助于开发先进的电池模型.
- 为了研究细胞间的变化及其对电池性能的影响.
主要方法:
- 12个高功率和 (NMC) 电池的特征.
- 进行容量测试,高C率脉冲测试和阻抗测试.
- 在受控温度下测试:5°C,25°C和40°C.
主要成果:
- 详细的数据集,包括各种条件下的性能指标.
- 在高功率NMC细胞中量化细胞对细胞的变化.
- 适用于开发随机电池模型的数据.
结论:
- 这一数据集解决了高功率LIB数据的短缺问题.
- 允许更准确的电池行为建模,考虑到不确定性.
- 支持电池管理系统的进步,
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