# Evaluation of Present Accelerated Temperature Testing and Modeling of Batteries
## 3 Case Studies
### Recommended Approach for Reliability Testing and Modeling  
The analysis above shows that comprehensive understanding of failure mechanisms is essential to develop an efficient accelerated life testing plan and an accurate model. Thus, failure modes, mechanisms, and effects analysis (FMMEA) should be conducted first based on the literature, experience, and battery applications. FMMEA is \"a systematic methodology to identify potential failure mechanisms and models for all potential failure modes, and to prioritize failure mechanisms\" [36].  
Second, a preliminary testing plan involving all possible stress factors should be established. The testing data can help determine the boundaries of major stress factors, that is, within these boundaries, failure mechanisms are consistent with those occurring under normal usage conditions. The major stress factors can be identified by ranking corresponding failure mechanisms. One ranking method is to compare the overall risk prioritization number (RPN) of each failure mechanism, which is a product of likelihood of occurrence, severity of occurrence, and ease of detection [37].  
Third, a design of experiment (DOE) should be prepared and conducted to investigate the effects of each stress factor as well as their interactions. Quantitative analysis of the DOE data then leads to an accelerated degradation model.  
A final accelerated testing plan with reduced size can be built to quickly predict the reliability of batteries based on the developed model. This produces a great savings of time for the device company to examine every batch of product dispatched from battery manufacturers.  
In the final testing plan, the overall testing time is a key factor for determining stress levels of different stress factors. Taking the accelerated cycle life testing of lithium-ion batteries as an example, major stress factors involve ambient temperature, SOC operation range and charge/discharge C-rate as mentioned in Section 1. On one hand, some stress factors may be able to accelerate the degradation with respect to cycles without influencing the testing time of each cycle, such as the ambient temperature in case study 2. The charge C-rate and discharge C-rate can shorten the testing time of each cycle, regardless of whether they present significant effects on battery degradation with cycles or not. These are favorable stress factors to be incorporated in the final testing plan, and C-rate will be set as the highest possible level if it shows no effect. On the other hand, increasing the stress levels of SOC operation range may accelerate battery degradation with cycles; however, the testing time of each cycle will be prolonged. Thus, the testing process may not be accelerated at all by elevating the stress levels of such factors.  
In the modeling process, the actual relationship between degradation and stress factors should be determined based on the testing data. There is no need to assume any empirical model, e.g.,the Arrhenius model for temperature dependence, and applying any empirical model requires strict verification.