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Embedded Fiber Optic Sensors in Li-Ion Pouch Cell for In Situ and In-Operando Diagnostics of Internal Strain and Temperature
Conferences & Talks

Proceeding for Material Research Society Fall Meeting 2014

2 December 2014



Under the ARPA-E AMPED program for advanced battery management systems (BMS), PARC and LG Chem Power are developing SENSOR (Smart Embedded Network of Sensors with an Optical Readout), an optically based smart monitoring system prototype targeting batteries for hybrid and electric vehicles (EVs). The system will use fiber optic (FO) sensors embedded within Lithium (Li)-ion batteries to measure parameters indicative of cell state in conjunction with PARC's low-cost, compact wavelength-shift detection technology and intelligent algorithms to enable effective real-time performance management and optimized battery design. FO sensors are lightweight and thin, immune to electrostatic discharge, electromagnetic interference, can be protected with suitable coatings to withstand harsh environments, and can measure multiple parameters with high sensitivity, such as strain, temperature, pressure, and chemical composition in multiplexed configurations. All of these characteristics make them very attractive candidates for embedding as sensors in batteries. This paper will give an overview of the project, the underlying enabling technologies, and then cover some promising initial experimental results. We have successfully fabricated initial functional prototypes of small format Li-ion pouch cells with embedded fiber optic sensors. Preliminary data indicates comparable performance and seal integrity of these cells to un-instrumented cells. We will present initial internal strain and temperature data recorded over charge-discharge cycles for various C-rates and operating conditions. The analysis of the measured strain data clearly exhibits a number of distinct characteristic features that provide information on Li-ion transport and intercalation stages. Our data clearly proves that fiber optic sensors provide a new in-situ and in-operando diagnostics tool that provide time-dependent information on Li-ion transport, stress and strain, and microstructural properties.

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