Mac Geoffrey Ajaereh

Ultrasound Non-destructive Evaluation for Lithium-ion Battery Packs

Lithium-ion batteries are pivotal in powering electric vehicles (EVs), significantly contributing to the electrification of transportation and reducing greenhouse gas emissions. These batteries are favored for their high energy and power density, efficiency, longevity, and durability. A critical aspect of ensuring their safe and reliable operation is the management of the State of Charge (SoC), a key parameter indicating the remaining battery capacity.

There are various methods to measure SoC, including Coulomb counting, Open Circuit Voltage (OCV), and Kalman filtering. Coulomb counting calculates SoC by integrating the current flowing in or out of the battery over time, relative to its total capacity. However, it suffers from cumulative errors, particularly from inaccuracies in current measurement and changes in battery capacity. The OCV method, based on the relationship between SoC and the battery's open-circuit voltage, is simple and accurate but impractical in continuous-use applications due to its need for the battery to reach a steady state. Kalman filtering, a sophisticated approach, combines a battery system model with real-time measurements to estimate SoC, adjusting estimates based on incoming data. While providing dynamic and accurate readings, it requires a detailed battery model and is computationally intensive.

An innovative approach in this realm is Ultrasound Non-Destructive Testing (NDT), particularly for lithium-ion batteries in high-demand applications like EVs. Ultrasound NDT is a non-invasive technique that doesn't require disassembling the battery, crucial for maintaining its integrity in practical applications. This method is safe, reducing the risk of damage or unsafe conditions during testing. It can detect internal structural changes in battery cells correlated with SoC and overall health. For instance, electrode expansion and contraction during charging and discharging cycles can be monitored with ultrasound techniques, potentially identifying internal faults or degradation early. Ultrasound NDT can potentially offer real-time or near-real-time SoC monitoring, integrating into Battery Management Systems (BMS) to enhance battery performance and longevity. This method can complement traditional SoC estimation methods, providing a different data type that can validate or complement electrical measurements.

Mac Geoffrey's PhD project focuses on using ultrasound NDT for lithium-ion battery modules in EVs. The main aim is to apply ultrasound NDT to these battery modules, finding practical solutions to encourage automotive manufacturers to include this technology in their BMS for accurate SoC tracking. Specific objectives include examining SoC non-uniformity across a single cell, comparing traditional SoC estimation methods against acoustic Time of Flight (ToF) measurements, studying ToF behaviour under temperature variations, investigating spatial acoustic changes under different charging/discharging speeds and relaxation periods, assessing the acoustic response of a battery module, and exploring battery module responses during cell balancing with various conditions. This project aims to enhance the accuracy and reliability of SoC estimations in lithium-ion battery modules for EVs, exploring the potential of ultrasound NDT as a practical and efficient method for integration into existing BMS technologies.