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From accelerated aging tests to a lifetime prediction model: Analyzing lithium-ion batteries

机译:从加速老化测试到寿命预测模型:分析锂离子电池

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As lithium-ion batteries play an important role for the electrification of mobility due to their high power and energy density, battery lifetime prediction is a fundamental aspect for successful market introduction. This work shows the development of a lifetime prediction model based on accelerated aging tests. To investigate the impact of different voltages and temperatures on capacity loss and resistance increase, calendar life tests were performed. Additionally, several cycle aging tests were performed using different cycle depths and mean SOC. Both the calendar and the cycle test data were analyzed to find mathematical equations that describe the aging dependence on the varied parameters. Using these functions an aging model coupled to an impedance-based electrical-thermal model was built. The lifetime prognosis model allows analyzing and optimizing different drive cycles and battery management strategies. The cells modeled in this work were thoroughly tested taking into account a wide range of influence factors. As validation tests on realistic driving profiles show, a robust foundation for simulation results is granted. Together with the option of using temperature profiles changing over the seasons, this tool is able to simulate battery aging in various applications.
机译:由于锂离子电池具有高功率和高能量密度,因此在电动化电动化方面起着重要作用,因此,电池寿命的预测是成功引入市场的基础。这项工作显示了基于加速老化测试的寿命预测模型的开发。为了研究不同电压和温度对容量损失和电阻增加的影响,进行了日历寿命测试。此外,使用不同的循环深度和平均SOC进行了几次循环老化测试。日历和周期测试数据均经过分析,以找到描述方程式对各种参数的老化依赖性的数学方程式。利用这些功能,建立了老化模型和基于阻抗的电热模型。寿命预测模型可以分析和优化不同的驾驶周期和电池管理策略。考虑到广泛的影响因素,对这项工作中建模的细胞进行了全面测试。正如在现实驾驶情况下的验证测试所示,为仿真结果奠定了坚实的基础。结合使用随季节变化的温度曲线的选项,该工具能够模拟各种应用中的电池老化。

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