My project is a novel approach to estimating the state of charge (battery percentage) of lithium-ion polymer batteries. Although your phone does it seemingly effortlessly, the number displayed in the upper right corner of your device is extremely inaccurate. Using an equivalent theoretical electrical circuit model, MATLAB, and a Dual Extended Kalman Filter (DEKF), I was able to create an algorithm that can estimate the battery percentage within 2% (of a 1% on a 0-100% scale). This is extremely important for both industry and consumers as it will allow our devices to become more efficient- since analysis of current draw can be used to verify what the optimal load on the battery is. This means that the entire lithium-ion polymer powered world (electric cars, phones, houses, etc.) can be much more efficient. Even disregarding efficiency in real-time load, my model allows systems to squeeze out the final bits of energy in the battery while remaining safe. This means that your phone can last for much longer without risking damaging the sensitive, dangerous lithium-ion polymer batteries.


What inspired me/us?

When reading literature surrounding the topic, I noticed a hole in the studies. Most focused on large systems that included hundreds of cells- for use in electric cars. For some reason, the scientific community chose not to focus on the simpler systems that are much more prevalent in industry and the consumer market. Thus, I filled this gap with my study and application of the DEKF for use in estimating SoC in LiPo batteries.