Simulation Assisted Current Density Monitoring for Lithium-ion Batteries in Electric Vehicles

Abstract

During the transformation of electrical energy in a grid-scale network, using an optimal energy storage system for balancing the power utilization and generation is an important challenge. Using batteries for this purpose in grid-level systems are highly recommended due to the flexibility in installation, modularization and fast response. Comparing to the other types, Lithium-ion batteries (LIBs) are a more common choice in industry because of their higher energy efficiency and density, inexpensive manufacturing cost and long life cycle. To use the batteries optimally, reliable state of health (SoH) monitoring solutions are required to be included in the battery management system (BMS). This paper proposes a simulation assisted electrode and electrolyte current density monitoring for lithium-ion batteries that can considerably increase the SoH estimation accuracy. The proposed method is realized through the fusion of the information from the magnetic field sensors together with the online simulation of the battery dynamic model, in real-time. The battery model of an electric vehicle is developed in COMSOL modelling software and the data fusion is implemented on dSPACE Microlabbox real-time simulator. The results confirm that the proposed monitoring solution can be potentially used to provide a highly accurate estimation system for a Lithium-ion cell.