Analysis of current density in the electrode and electrolyte of lithium‐ion cells for ageing estimation applications. Issue 2 (11th March 2021)

• Record Type: Journal Article
• Authors: Javadipour, Mehrnaz; Mehran, Kamyar
• Is Part Of: IET smart grid. Volume 4:Issue 2(2021)
• Page Start: 176
• Page End: 189
• Publication Date: 2021-03-11
• Subjects: Smart power grids -- Periodicals; Computer science -- Periodicals; Energy industries -- Periodicals; Broadcasting -- Periodicals; 333.79110285
• DOI: 10.1049/stg2.12018
• Languages: English
• ISSNs: 2515-2947

Abstract

Abstract: Lithium‐ion battery is the commonly used energy storage technology in electric vehicles (EVs) because of its inexpensive manufacturing cost and high energy capacity. For optimal utilization of its capacity and lifetime, reliable state of health (SoH) monitoring solutions have to be included in the battery management system (BMS). SoH of a cell is affected by several reasons such as internal degradation or external damages that need to be estimated. This article analyses the current density in electrode and electrolyte of an EV lithium‐ion cell using a simulation assisted method that leads to improvement in SoH estimation accuracy. The experimental results are analysed through the fusion of the magnetic field images captured by quantum fluxgate magnetometers, installed on the surface of the cell, together with the real‐time simulation of the multi‐physics model of the cell. The magnetic field sensors measure the magnetic field intensity with an accuracy of ±2 mT. The real‐time simulation input data is updated from the measurements of both the magnetic field sensors and the battery cycler. The multi‐physics model of the cell is developed in COMSOL modelling software, and real‐time data fusion process is implemented on dSPACE Microlabbox real‐time simulator. Results confirm that the proposed monitoring solution provides useful insight that can be employed in ageing estimation of EV batteries.