A smart Li-ion battery with self-sensing capabilities for enhanced life and safety

Highlights

• This paper presents a new type of Li-ion smart battery prototype.

• This paper proposes a new Multi-Parameter FBG (MP-FBG) sensor.

• The MP-FBG sensor has the advantages of multi-function and strong stability.

• The Li-ion smart battery helps improve battery quality, reliability and life features.

Abstract

Accurate monitoring and prediction of the operating status of Li-ion batteries (LiBs) are essential for enhancing the longevity and safety of LiB-powered applications. In contrast to conventional battery management strategies that rely solely on voltage, current, and temperature at module level, we present a smart Li-ion cell with an integrated fiber Bragg grating (FBG) optical fiber sensor that enables simultaneous measurement of temperature, force, and displacement at the cell level with a simple beam structure. The Li-ion smart battery sensor scheme realizes the synchronous monitoring of battery mechanical, electrical and thermal multi-physics parameters. We demonstrate that monitoring force is beneficial for enhancing cell life and safety. Specifically, the evolution of peak force upon cycling correlates linearly with the capacity fade, making the force signal a useful state-of-health indicator. Further, the change in cell force is tens of seconds earlier than the change in cell temperature under nail penetration and thermal abuse tests, exhibiting enormous potential for early detection of battery safety incidents, using the Li-ion smart battery scheme, we realize the quantitative description of the evolution of battery structure. By the Li-ion smart battery, it has the ability to improve the quality, reliability and service life of the battery.

Introduction

The past few years have witnessed an unprecedented increase in our dependence on Li-ion batteries (LiBs) with the rapid market penetration of electric vehicles (EVs) and energy storage systems (ESSs). Durability and safety are two essential battery requirements. EVs require at least a 10-year lifespan [1], and ESSs demand ≥20 years [2]. To that end, the lifetime of LiBs is typically the bottleneck. Also, the frequently reported battery safety incidents have pressed regulators to enforce more strict safety standards. For instance, China has implemented mandatory standards to require all EVs sold in China to inhibit any fire or explosion for at least 5 min after a battery thermal runaway incident occurs [3,4].

Understanding the health and safety status of LiBs is vital for developing a robust battery management system (BMS). For real-world battery packs, only current (I), voltage (V), and temperature (T) are typically accessible [5,6], and they are usually measured at the module level for the sake of cost [7]. As such, it is challenging to accurately predict the operating status of each cell, nor is it able to access the cells’ internal states (the spatial distributions of temperature, state of charge (SOC), state of health (SOH), etc.) [[8], [9], [10], [11]].

Our increasing dependence on batteries demands disruptive technologies for sensing and diagnostics of LiBs. In its recently published Battery 2030 + Roadmap [12], the European Union has proposed an ambitious goal to develop so-called smart batteries with embedded sensing technologies and functionalities. It involves developing various types of sensors (thermal, electrochemical, mechanical, acoustic, etc.) that can function reliably in the harsh electrochemical environment of a battery cell, pinpointing the fundamental relationships between the measured parameters and the physicochemical processes inside the cell, and devising an advanced BMS with both the internal and external parameters as inputs.

Literature studies have proposed various physical parameters that can provide valuable information about the internal cell status. Dahn's group placed a strain sensor at the cell surface for operando measurement of cell pressure and demonstrated that the shift in average pressure is related to the irreversible volume expansion caused by the growth of solid-electrolyte-interphase (SEI) [13]. Thus, monitoring cell pressure is an effective tool for predicting battery's SOH. Bitzer and Gruhle revealed that measuring cell thickness can detect Li plating during charging, as the volume change caused by the formation of Li metal is 4x the change caused by Li intercalation into graphite [14]. Day et al. [15] proposed that differential thermal analysis (DTA) can track the changes in electrolyte composition and hence is a non-destructive method to correlate the melting point of the electrolyte to the cell's SOH. Deng et al. [16] showed that ultrasonic scanning could reveal the degree of electrolyte wetting in the porous electrodes and hence is useful for diagnostic of electrolyte degradation. Nevertheless, a primary challenge to adopting these techniques in real-world applications is miniaturization, as they either require bulky sensors or special equipment.

Fiber Bragg Grating (FBG) sensors, whose wavelength depends on local thermal factor (temperature) and mechanical factor (strain), have emerged as a promising in-situ battery sensing technique [[17], [18], [19]]. Sommer et al. [20,21] attached FBG sensors onto the surface of a pouch cell to measure the cell strain during charge and discharge. It is demonstrated that the measured strain is reflective of cell SOC. Later, the same group showed that the hair-thin FBG sensors could be embedded inside pouch cells without affecting the cyclability of the cell [22,23]. However, a primary challenge to FBG sensors is how to decouple strain and temperature. Very recently, Huang et al. [24,25] showed that adjusting fiber morphologies can decouple the wavelength changes associated with temperature and pressure, which allows for determining the internal temperature gradient and, subsequently, tracking chemical events such as SEI growth and structural evolution. However, there are still limited studies on the feasibility of using FBG sensors as battery SOH indicators. Moreover, to the best of our knowledge, no one has ever studied the evolution of cell force under mechanical-abuse or thermal-abuse conditions. Literature works showed that magnetic resonance technology, computed tomography technology and 2D acoustic characteristic technology could reveal the battery structure evolution during thermal runaway or during normal operation status [[26], [27], [28]], whereas these techniques require bulky and expensive equipment. Indeed, most state-of-the-art EV batteries only utilize temperature to detect battery safety incidents [29,30].

Here, we present an approach to achieve simultaneous measurements of cell temperature, force, and displacement of a LiB cell using a Multi-Parameter FBG (MP-FBG) sensor. In the research, we explore the service performance of the smart Li-ion battery under conventional charging-discharging condition, long cycle condition and abuse conditions. We highlight that mechanical signals (force, displacement) are valuable, as they are reflective of battery health and safety states. Specifically, the maximum force of a cell correlates linearly with its capacity fade upon cycling and hence can serve as a SOH indicator. Further, we show that the change in cell force in thermal abuse conditions is tens of seconds earlier than temperature change, exhibiting great potential for early detection of battery safety incidents. Through the Li-ion smart battery, we can theoretically change the battery monitoring state from the “black box” state to the “white box” state, and realize a comprehensive grasp of the battery working process.