Traditional lithium-ion battery state monitoring primarily relies on external measurements of current, voltage, and temperature conducted outside the individual cell and inside the battery module. Given that temperature variations such as gradients can significantly impact battery performance, ageing and pose challenges for conventional evaluation methods, localized temperature sensing presents an innovative approach to gain insights into the current state of individual battery cells and the temperature distribution within modules. The importance of understanding thermal gradients and their implications has grown in recent years. Moreover, this collected information can be leveraged for load and thermal management by a deployed battery management system.
In many cases, cost considerations in inserting discrete temperature sensors at the module level lead to compromises, often covering areas with sensors designed to capture only the average temperature of the cells. Our fiber-optic measurement methodology offers a distinct advantage in this regard, providing spatially resolved temperature data over several meters with centimeter-level resolution. Through targeted placement the influence of other environmental factors, such as pressure, can be effectively circumvented.
We demonstrate that this approach proves invaluable, particularly for addressing safety-critical concerns, as it enables early identification of individual anomalous cells that might otherwise go unnoticed within the whole module. In tests, data was collected on location-specific temperature events, allowing for comparison and analysis against traditional temperature monitoring. Due to the high sampling rate and low response time, the recorded measurements can potentially protect against thermal runaway or other safety-critical conditions during real-time monitoring. Our results underscore the potential of fiber-optic measurement techniques to enhance the performance and safety of batteries, particularly in terms of temperature monitoring and the early identification of operational issues. However, the integration into a battery management system remains an ongoing challenge.