A Reduced-Order Physics-based Model Of Lithium-Ion Batteries With Blended Electrodes: Systematic Derivation And Comparison With Experiment #

Benyamin Ebrahimpour, Jamie M Foster, Smita Sahu

Poster session

Abstract #

Li-ion batteries (LIBs) are expected to be one of the key technologies used to store electrical energy over the coming years. These batteries are already produced in large quantities due to their high energy storage, high cell voltage, and slow charge reduction when not in use. Their popularity is expected to continue growing with the increasing demand for electric vehicles (EVs) and other devices. Therefore, it is important to also focus on improving their performance in terms of their life, safety, and capacity. LIBs are made up of many electrodes coupled together, and it is the microscopic details of how these electrodes are designed (particularly the active material(s)) that have arguably the biggest impact on device-scale performance. Blended electrodes, i.e. those which contain more than one type of active material, may help to improve the performance of LIBs, especially in fast (dis)charging applications. The basic idea is to combine two materials that offer different advantages (i.e. rate capability, or high capacity) and by combining them, we end up with a device that offers the best of both simultaneously. The Doyle Fuller-Newman (DFN) model is the ubiquitous physics-based model for LIBs and is made up of complicated non-linear partial differential equations. It is computationally expensive, especially for LIBs with blended electrodes. This motivates us to systematically simplify a DFN-based model for blended electrodes using asymptotic approximations; thereby yielding a reduced-order model that we term the simplified blended electrode model (SBEM). The SBEM is significantly cheaper to solve than the DFN, yet it is able to accurately replicate much of its behaviour. In this presentation, we will outline our asymptotic simplification, compare simulation results from SBEM to the DFN and discuss some practical cases where we expect the SBEM to be useful.