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Predicting Lithium-ion Battery Resistance Degradation using a Log-Linear Model

机译:使用对数线性模型预测锂离子电池电阻劣化

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The resistance is one of the parameters that describes the performance of Lithium-ion (Li-ion) batteries, as it offers information about the battery efficiency and its power capability. However, similar to other performance parameters of Li-ion batteries, the resistance is dependent on the operating conditions and increases while the battery is aging. Traditionally, to capture these dependencies, Li-ion cells are aged at different conditions using synthetic mission profiles and periodically the aging tests are stopped in order to measure the resistance at standard conditions. Most of the times, even though accurate information about the resistance behavior is obtained, they do not reflect the behavior from real-life applications. Thus, in this work we propose a method for extracting, modelling, and predicting the resistance directly from the battery dynamic mission profile. While the extraction mainly relied on data manipulation and bookkeeping, the modelling and subsequent prediction of the resistance used a log-linear model.
机译:电阻是描述锂离子(锂离子)电池性能的参数之一,因为它提供了有关电池效率及其功率能力的信息。然而,类似于锂离子电池的其他性能参数,电阻取决于操作条件并在电池老化时增加。传统上,为了捕获这些依赖性,锂离子电池在使用合成任务型材的不同条件下老化,并且定期停止老化试验以测量标准条件下的电阻。大多数时候,即使获得了有关电阻行为的准确信息,它们也不会反映现实生活中的行为。因此,在这项工作中,我们提出了一种用于直接从电池动态任务配置文件提取,建模和预测阻力的方法。虽然提取主要依赖于数据操纵和簿记,但对电阻的建模和随后预测使用了对数线性模型。

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