基于任务剖面的电动汽车充电模块铝电解电容器寿命预测与可靠性分析

IF 1.9 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC Frontiers in electronics Pub Date : 2023-08-16 DOI:10.3389/felec.2023.1226006
Hongpeng Liu, Jiahui Qiu, Wei Zhang, Mengyuan Zhang, Z. Dou, Liangliang Chen
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引用次数: 0

摘要

电动汽车的充电模块总是在复杂多变的状态下运行。作为充电模块可靠运行的薄弱环节,准确预测铝电解电容器的寿命对后期的维护和可靠性设计具有重要意义。热点温度计算方法和寿命模型限制了铝电解电容器寿命预测方法的准确性,无法满足日益增长的可靠性要求。为了解决上述问题,本文提出了一种基于具有频率特性的纹波电流以及电容器发热和导热的冷却条件的热点温度计算方法。此外,利用三维表面拟合工具箱建立了参考电压下的电容器寿命模型,描述了恒压条件下电容器寿命随环境温度和热点温度的变化趋势。考虑到电压的变化,建立了具有电压校正系数的电容器多寿命模型。利用该方法,可以实现在纹波电流、散热条件、环境温度和工作电压等多种工况下电容器寿命的实时预测。最后,通过30kW电动汽车充电模块的年剖面验证了该方法的有效性。
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Lifetime prediction and reliability analysis for aluminum electrolytic capacitors in EV charging module based on mission profiles
The charging modules of Electric vehicles (EVs) always run in a complex and variable state. As the weakness in the reliable operation of charging modules, the accurate lifetime prediction of aluminum electrolytic capacitors (Al-caps) is important for the later maintenance and reliability design. The hotspot temperature calculation method and lifetime model limit the accuracy of aluminum electrolytic capacitors lifetime prediction methods, which cannot meet the increasing requirements for reliability. In order to solve the problems above, this paper has proposed a hotspot temperature calculation method based on the ripple current with frequency characteristics and the cooling conditions on the heat generation and thermal conductivity of the capacitors. Furthermore, the lifetime model under reference voltage has been constructed with 3D surface fitting toolbox, which describes the trends of capacitor lifetime with ambient temperature and hotspot temperature under the constant voltage condition. Considering the variation of voltage, the multiple lifetime model of capacitor is established with a voltage correction coefficient. With the proposed method, it can be realized about the real-time lifetime prediction of capacitors under multiple operating profiles such as ripple current, thermal dissipation conditions, ambient temperature and operating voltage. Finally, the effectiveness of the proposed method is verified with the annual profiles of a 30 kW EV charging module.
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