SENSOR: embedded fiber optic sensing for accurate state estimation in advanced battery management systems

Abstract

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. Towards the end project goal of automotive-grade cell modules that incorporate this technology, the team has fabricated initial functional prototypes of small format FO-embedded Li-ion pouch cells. Preliminary data indicates comparable performance and seal integrity of these cells to un-instrumented cells. Analysis of sensor data from these cells recorded over charge-discharge cycles have shown a number of interesting features that hold promise to aid accurate cell state estimation algorithms. In parallel, experiments to explore the potential of high sensitivity skin strain and temperature monitoring with FO sensors mounted externally on the cell are also ongoing. These experiments have also yielded notable results in terms of detecting cell state features that can be monitored with PARCs sensitive FO readout and are not detectable with the voltage and current signals monitored during typical usage by present-day BMS. The paper will examine these results and compare internal versus external cell sensing with FO sensors. Finally, the use of these monitored internal cell state features for state estimation algorithms and suitable BMS control strategies for safe, optimal utilization of true battery capacity will be discussed, which can reduce conservative design and use practices of batteries for various applications.