可回充式鋰電池 (Rechargeable lithium-ion battery) 在電子產品扮演極為重要的電源供應器角色。為了能快速提供消費者有關電池壽命資訊，如何安排適當的加速壽命實驗 (或加速衰變實驗) 來準確地推估產品壽命是製造商十分重要的研究課題。唯電池的充電或放電機制何者可以當作壽命實驗之加速變數 (accelerating variable)，一直是極具爭議的課題。為了能有效地解決此問題，本研究在不同充、放電應力的組合下，首先安排雙因子的實驗配置來收集電池的放電電容值及其放電溫度之衰變資料; 其次，本文提出如何利用電池的放電溫度資料來修正放電電容值; 進而可建構出兩種有雙加速變數的 trend renewal process (TRP) 模型。最後，利用最大概似估計法 (MLE) 來估計模型中的未知參數，並配合反應曲面方法 (response surface methodology) 及有母數的拔靴法 (parametric bootstrap)，可推估在正常使用條件下之電池平均壽命 (end of performance) 及其 95% 信賴區間。本研究的主要貢獻是提供鋰電池平均壽命之預測推論方法; 此外，它對後續安排更經濟的逐步應力加速衰變試驗 (step-stress accelerated degradation test) 將有頗有助益。

Rechargeable lithium-ion battery plays a key role in power supply of electronics. To provide timely battery lifetime information to the potential consumers, the manufacturers have the important task to conduct an efficient accelerated degradation test (ADT) for predicting the battery lifetime. However, whether charge or discharge current of the battery should be considered an accelerating variable in the ADT is still being debated. To address this problem, we conduct a two-factor experiment under various combinations of charge and discharge currents to collect the degradation data of the discharge capacity of batteries together with their temperature data. We then propose a suitable procedure to calibrate the discharge capacity of batteries by using the temperature information. Finally, we propose two accelerated trend renewal process (aTRP) models to describe the degradation paths of the capacity of batteries. Based on these models, we can successfully predict the end of performance (EOP) of battery under normal use conditions and its 95% confidence interval. The results of this study should be valuable for the subsequent design of more economical step-stress accelerated degradation test (SSADT).

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