Electrochemical Impedance Modeling and Optimization of Li-Ion Battery Utility using Active Battery Management System (ActiveBMS)

Lithium ion batteries (LIBs) are considered the top candidates among electrochemical energy storage systems (ESS) due to their high energy density which has triggered the growth market of popular devices such as cell phones, computers, electric vehicles (EV) etc. As ESS, LIBs are continuously charged and discharged during their utility. The charge/discharge cycle is known to contribute towards their degradation depending on the charging protocol and operating conditions. In response to this challenge, advanced battery management systems (BMS) have been developed to ensure the largest usable capacity, longest life, faster charging speed, and to lower the cost. However, currently there is no efficient BMS due to poor understanding of the complex degradation mechanism of LIBs. Besides, the protocols to measure capacity fade are inadequate and labor intensive. This project aims to enhance GBatteries active BMS (ActiveBMS), which is a set of hardware and software providing a real-time self-learning control system handling LIBs during the charge, idle, and discharge. The project is expected to fill the knowledge gaps via correlation studies between impedance values and capacity fading. The correlations will be developed into a model for predicting LIBs degradation and allow the BMS to send a signal to mitigate the degradation.

Faculty Supervisor:

Elena Baranova

Student:

Evans Monyoncho

Partner:

University of Ottawa

Discipline:

Engineering - chemical / biological

Sector:

Energy

University:

Program: