Real-Time Battery Health Tracking Using Fiber-Optic Sensors

AI-driven sensors detect irregularities in electric vehicle systems © panu101-chronicles-stock.adobe.com

The widespread adoption of lithium-ion (Li-ion) batteries in hybrid and electric vehicles (xEVs) hinges on accurate battery management to ensure performance, longevity, and safety. Traditional battery management systems (BMS) rely on external measurements such as voltage and current, which often lead to conservative designs and inefficient capacity utilization. Researchers from Palo Alto Research Center (PARC, a Xerox Company) and LG Chem Power have now introduced an advanced approach: embedded fiber-optic (FO) sensors capable of internally monitoring battery cells. Their findings, published in the Journal of Power Sources, detail how these sensors provide precise internal cell data, enabling improved SOC and SOH battery estimation while offering early failure detection (1,2).

A New Approach to Battery State Estimation

Conventional methods for SOC estimation include Coulomb counting, open circuit voltage (OCV) measurements, and dynamic modeling. However, these techniques have inherent limitations, such as drift errors in current sensors, the need for extended rest periods, and accuracy trade-offs in model-based approaches. The new FO sensor technology addresses these challenges by directly monitoring strain and temperature within battery cells. These internal signals provide real-time insights into battery function, allowing for more accurate estimations and reducing reliance on external monitoring (1,2).

How Fiber-Optic Sensors Improve Battery Monitoring

FO sensors, specifically fiber Bragg grating (FBG) sensors, are embedded within the battery cells to measure strain and temperature shifts. The research team successfully fabricated large-format Li-ion pouch cells with integrated FO sensors and evaluated them under real-world xEV operating conditions. The sensors monitor intercalation-induced strain—a direct consequence of lithium-ion movement within the electrodes—which correlates with SOC. A sophisticated algorithm combining dynamic time warping and Kalman filtering processes the FO sensor data to estimate SOC with high precision (1,2).

The study also introduces an innovative strain-temperature separation method, ensuring that temperature fluctuations do not interfere with strain-based SOC estimation. By isolating these parameters, the researchers achieve a more robust and reliable battery monitoring system (1,2).

Aging, Capacity Degradation, and SOH Estimation

Beyond SOC estimation, FO sensors prove valuable for predicting battery health and degradation. To test SOH estimation capabilities, the researchers subjected a battery module to aggressive charge-discharge cycling over 100 cycles. The FO sensor data was used to track gradual capacity loss and predict future degradation up to 10 cycles ahead. This predictive capability is crucial for battery management in electric vehicles, where unexpected failures can have significant performance and safety implications (1,2).

Implications for Electric Vehicles and Beyond

The introduction of embedded FO sensors represents a major advancement in battery management technology. Unlike traditional external monitoring methods, FO sensors provide a direct window into the battery’s internal state, enabling more efficient and safer battery utilization. This could lead to enhanced battery longevity, reduced costs, and improved reliability for electric vehicles and other applications dependent on lithium-ion energy storage.

The ability to predict SOH with high accuracy also opens the door to proactive battery maintenance strategies, reducing premature replacements and minimizing environmental waste. Additionally, the research suggests that the integration of FO sensors does not compromise battery performance, ensuring compatibility with current manufacturing and operational standards (1,2).

This two-part study highlights the potential of FO sensors as a transformative tool for battery monitoring. In the first part, the researchers demonstrated the feasibility of embedding FO sensors in large-format pouch cells without affecting their integrity or performance. The second part delves into the signals captured by these sensors and their utility in high-accuracy SOC and SOH estimation (1,2).

Moving forward, further studies will focus on refining the technology for commercial implementation, optimizing sensor placement within cells, and expanding the dataset across different battery chemistries and form factors. As FO sensing technology continues to evolve, it may become a standard feature in next-generation battery management systems, paving the way for safer and more efficient energy storage solutions.

References

(1) Raghavan, A.; Kiesel, P.; Sommer, L. W.; Schwartz, J.; Lochbaum, A.; Hegyi, A.; Schuh, A.; Arakaki, K.; Saha, B.; Ganguli, A.; Kim, K. H. Embedded Fiber-Optic Sensing for Accurate Internal Monitoring of Cell State in Advanced Battery Management Systems. Part 1: Cell Embedding Method and Performance. J. Power Sources 2017, 341, 466–473. DOI: DOI: 10.1016/j.jpowsour.2016.11.104

(2) Ganguli, A.; Saha, B.; Raghavan, A.; Kiesel, P.; Arakaki, K.; Schuh, A.; Schwartz, J.; Hegyi, A.; Sommer, L. W.; Lochbaum, A.; Sahu, S. Embedded Fiber-Optic Sensing for Accurate Internal Monitoring of Cell State in Advanced Battery Management Systems. Part 2: Internal Cell Signals and Utility for State Estimation. J. Power Sources 2017, 341, 474–482. DOI: 10.1016/j.jpowsour.2016.11.103