Causal Discovery of Battery Lifespan and Related Issues

With the development of green energy fields such as electric vehicles, batteries related technologies are receiving increasing attention from people. Among them, how to extend the lifespan of batteries has always been a challenge. Previous algorithms were mostly based on correlation, which cannot accurately describe the causal relationship between various factors and leads to errors. To conquer this issue, this paper uses conclusions of causal inference to study which factors can prolong battery lifespan the most by constructing a structural causal model, as well as their mutual influence when people intervene in these factors and how this influence will change battery lifespan. This paper will provide more reliable support for existing theories on extending battery lifespan, and help those who need to improve battery lifespan by pointing out the factors that can most extend life. As a result, the paper promises to be a useful guidance for people who want to study the battery lifespan.