Lithium-Ion Diagnostics: The First Quantitative In-Operando Technique for Diagnosing Lithium Ion Battery Degradation Modes under Load with Realistic Thermal Boundary Conditions
Lithium-Ion Diagnostics: The First Quantitative In-Operando Technique for Diagnosing Lithium Ion Battery Degradation Modes under Load with Realistic Thermal Boundary Conditions
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DOI：
10.1149/1945-7111/abed28
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发表时间：
2021-03
影响因子：
3.9
通讯作者：
R. Prosser;G. Offer;Yatish Patel
中科院分区：
文献类型：
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作者：
R. Prosser;G. Offer;Yatish Patel
首次提出了一种能够定量估计运行中的退化模式的诊断技术，包括锂库存损失和活性材料损失，其在具有现实热边界条件的充电和放电负载下运行。该技术使用零维发热模型，仅需要估计三个参数，简单的传热模型，并且每个电池仅需要三个温度测量值，电压和电流。该技术已被证明适用于具有翼片冷却和恒定冷却剂温度的袋状电池，以及C/2、1C和2C的充电和放电速率。与最先进的开路电压（OCV）模型方法相比，该技术预测新电池的电极容量和偏移，精度分别为3%和6%。此外，该技术已被证明预测锂的损失和活性材料的损失，在正极和负极的准确度分别为0.18%，0.22%和1.99%。因此，该技术可以提供与当前最先进技术相同质量的信息，但是在应用相关条件下工作，并且由于其简单性，适合于在电池管理系统（BMS）中在线实现。
A diagnostic technique capable of quantitatively estimating degradation modes in-operando, including loss of lithium inventory and loss of active material, which operates under charge and discharge loads with realistic thermal boundary conditions is presented for the first time. The technique uses a zero-dimensional heat generation model with only three parameters requiring estimation, a simple heat transfer model, and requires just three temperature measurements per cell, voltage and current. The technique has been demonstrated to work for pouch cells with tab cooling and a constant coolant temperature and for charge and discharge rates of C/2, 1C and 2C. Compared to state-of-the-art open circuit voltage (OCV) model methods, the technique predicts electrode capacities and offset of a fresh cell with accuracies of 3% and 6% respectively. Further the technique has been shown to predict loss of lithium and loss of active material in the positive and negative electrodes with accuracies of 0.18%, 0.22% and 1.99% respectively. The technique can therefore provide information of the same quality as the current state-of-the-art techniques but works under application relevant conditions and due to its simplicity is suitable for implementation on-line in a battery management system (BMS).