# Evaluation of Present Accelerated Temperature Testing and Modeling of Batteries
## 4 Conclusions and Recommendations  
Accelerated temperature testing of batteries is often conducted to predict battery performance and product lifetime in the targeted operating temperature conditions, in a timely and cost-effective manner. However, there are significant problems when battery manufacturers and device companies use the Arrhenius model and the decade rule to design the test plan and make predictions.  
First, not all failure and performance degradation mechanisms in a battery can be accelerated by increasing the temperature. For example, failure mechanisms at cold temperatures such as lithium dendrite growth of lithium-ion batteries are not accelerated or even precipitated by increasing the temperature. In this way, only decreasing temperature below a certain level can accelerate lithium dendrite growth. Therefore, the temperature range within which a failure mechanism dominates and the manner at which temperature affects the failure mechanisms should be clarified first.  
Second, there is a limit to the amount of acceleration one can gain by increasing temperature without causing unique failure mechanisms that do not occur in normal operation. In other words, the testing temperature of batteries should generally not change the failure mechanisms that one has developed a model for.  
Third, the Arrhenius model is often not accurate for modeling the effect of temperature. For example, as shown in case study 2, the logarithm of capacity loss and reciprocal of temperature is not linear. The activation energy in this model is also shown to change over cycles. However, these counter examples do not suggest that the Arrhenius model can never model the effect of temperature on battery degradation, but rather underscore the importance of verification.  
Fourth, the commonly accepted 10 \({}^{\circ}\)C decade rule states that the useful life doubles for every 10 \({}^{\circ}\)C decrease of temperature, or that the aging rate doubles for every 10 \({}^{\circ}\)C increase. This represents a gross over-simplification of the Arrhenius model for thermally activated processes and is thus inaccurate. Even for processes that are accurately described using the Arrhenius model, it has been shown that this rule only holds true at one combination of temperature and activation energy. This decade rule thus should not be used to obtain an AF or estimation of life, since it does not correctly represent the variation of rate with temperature.  
A proper approach for reliability prediction of batteries requires designing appropriate testing plans and correctly modeling the effect of stress factors. The testing plan should be based on the desired failure mechanisms to be accelerated. In the modeling process, the actual relationship between degradation and stress factors should be determined based on the testing data. It is best not to assume an empirical model and the valid working range of the model needs to be specified.  
Conceptualization, M.P.; Methodology, W.D., S.S. and Y.X.; Writing-Original Draft Preparation, W.D.; Writing-Review and Editing, M.P.  
This research received no external funding.  
The authors would like to thank the more than 150 companies and organizations that support research activities at the Center for Advanced Life Cycle Engineering (CALCE) at the University of Maryland annually.  
The authors declare no conflict of interest.