In our last post we reviewed the basics of battery data (link). Here we’ll start to delve deeper into the valuable insight hidden in raw time-series data — vital information that usually gets overlooked. The first approach we’ll look at is differential capacity analysis (dQ/dV).

While there’s some exciting work being done in academia on differential capacity analysis — check out Prof. Jeff Dahn’s work, and Dr. Matthieu Dubarry’s work — this technique is rarely used in industry due to the difficulty of efficiently extracting these advanced parameters from raw data,

Differential capacity (dQ/dV) analysis allows you to observe what is happening in a battery (including degradation, failure mechanisms, changes in chemistry) in much greater detail than can be observed using aggregate statistics like capacity, energy and efficiency per cycle. Conceptually, dQ/dV describes the incremental capacity going into our out of a device over a given voltage increment (some also prefer to use the inverse, differential voltage, dV/dQ). Differential capacity can be derived from raw time series current and voltage data , or accessed directly using a Battery Intelligence platform such as Voltaiq.