Enhanced Safety and Reliability of Lithium-Ion Battery Storage Using On-Board Diagnostic System

Operational reliability and safety are of paramount importance in lithium-ion battery systems, especially when it involves large energy densities and high storage capacities as is true for Electric Vehicles (EV) and Grid-Scale Energy Storage Systems (ESS). A major cause of thermal runaway events is internal electrochemical shorts during battery charging. Strategies for detecting the onset of thermal runway are based on monitoring temperature, current and voltage, and cell bulging using strain gages. Battery Management Systems (BMS) can also be programmed with advanced analytics to estimate internal electrical parameters. These estimates could lead to an advanced safety warning outcome. IFOS is leveraging advanced Distributed Fiber-Optic Sensing (DFOS) to provide measurement of both temperature and strain in battery cells. A single fiber can robustly and reliably measure both parameters up to several kilometers along its length, and this can be used for real-time condition monitoring of every cell in the battery system. The proposed DFOS system provides numerous sensing points (typically from 10’s to well over 100 multi-functional sensors, and thousands of multiplexable fiber-optic sensors along multiple optical fibers, connected to a single optical interrogator. The electrically passive DFOS system can be integrated with the lithium-ion battery system using a single fiber strand or multiple strands of fibers having numerous micro-optic sensors centered at different wavelengths. The remote optical interrogator measures the temperature and strain at every micro-sensor location in real-time using spectral multiplexing. An abnormal read-out in any cell can be detected and used to trigger corrective action to prevent catastrophic issues such as fires and explosions. IFOS plans to employ a miniaturized optical interrogator based on Photonic Integrated Circuit (PIC) engine. The IFOS technology will enable a Prognostics and Health Management (PHM) system to predict and prevent unsafe conditions in the rapidly expanding utility-scale and commercial electric vehicle markets.