Electrochemical Impedance Spectroscopy (EIS) is a powerful diagnostic tool for assessing the State of Health (SOH) of batteries. By analyzing the impedance response of a battery over a range of frequencies, EIS provides detailed insights into the underlying degradation mechanisms that affect performance and lifespan. This technique is widely used in electric vehicles (EVs), grid storage systems, and other applications where accurate SOH monitoring is critical for operational reliability and safety.

The fundamental principle of EIS involves applying a small alternating current (AC) signal across a battery and measuring the voltage response. The impedance, which represents the opposition to current flow, is calculated as the ratio of voltage to current. By sweeping the frequency of the AC signal—typically from millihertz to kilohertz—EIS captures the battery's response across different time scales. The resulting impedance spectrum, often presented as a Nyquist plot, reveals distinct features corresponding to various electrochemical processes.

A Nyquist plot for a lithium-ion battery typically includes a high-frequency semicircle, a mid-frequency semicircle, and a low-frequency tail. The high-frequency semicircle is associated with the ohmic resistance of the electrolyte and electrode materials. The mid-frequency semicircle corresponds to charge transfer resistance at the electrode-electrolyte interface, while the low-frequency tail reflects diffusion processes within the electrodes. Changes in these features over time can be correlated with specific degradation mechanisms.

One of the primary degradation mechanisms detectable by EIS is solid electrolyte interphase (SEI) growth. The SEI layer forms on the anode surface during initial cycles and continues to evolve with aging. An increase in the mid-frequency semicircle diameter indicates SEI growth, which raises charge transfer resistance and reduces battery capacity. EIS can distinguish SEI-related impedance from other effects, enabling precise tracking of anode degradation.

Lithium plating is another critical degradation mode that EIS can identify. Plating occurs when lithium ions deposit as metallic lithium on the anode surface instead of intercalating into the electrode material. This phenomenon is particularly prevalent at low temperatures or high charging rates. EIS detects lithium plating through changes in the low-frequency impedance response, as plated lithium alters diffusion dynamics and increases interfacial resistance. Early detection of plating is crucial for preventing capacity loss and safety hazards.

Cathode degradation, including structural changes and active material loss, also influences the impedance spectrum. For example, in layered oxide cathodes, impedance increases due to particle cracking and contact loss between active material and conductive additives. EIS can track these changes by monitoring shifts in the high-frequency resistance and mid-frequency semicircle. By correlating these shifts with capacity fade, EIS provides a non-invasive means of assessing cathode health.

The advantages of EIS for SOH monitoring are significant. Unlike destructive methods such as post-mortem analysis, EIS is non-invasive and can be performed during normal operation. It offers high-resolution data, revealing subtle changes in electrochemical behavior that other techniques might miss. Additionally, EIS can be integrated into battery management systems (BMS) for real-time diagnostics, enabling proactive maintenance and fault detection.

However, EIS has limitations that must be considered. Interpreting impedance spectra requires expertise, as overlapping processes can complicate data analysis. Advanced modeling techniques, such as equivalent circuit fitting or distribution of relaxation times (DRT), are often needed to deconvolute contributions from different degradation mechanisms. Furthermore, EIS equipment can be expensive, and measurements may be sensitive to temperature, state of charge (SOC), and other operational conditions.

In real-world applications, EIS is increasingly used in EVs to enhance battery longevity and safety. By periodically performing EIS measurements, onboard systems can detect early signs of degradation and adjust charging protocols accordingly. For example, if lithium plating is detected, the BMS can reduce charging currents or increase temperatures to mitigate further damage. Similarly, grid storage systems employ EIS to monitor large battery banks, ensuring optimal performance over extended periods.

Compared to other SOH estimation methods, EIS offers unique benefits. Coulomb counting, which tracks charge and discharge cycles, is simple but prone to errors due to capacity drift and coulombic inefficiency. Voltage-based methods, such as open-circuit voltage (OCV) analysis, are less precise in identifying specific degradation modes. In contrast, EIS provides a comprehensive view of internal processes, though it requires more computational resources and calibration.

Emerging trends in EIS research focus on improving data interpretation and integration with machine learning. By training algorithms on large datasets, researchers can automate impedance analysis and enhance predictive accuracy. Additionally, advancements in portable EIS hardware are making the technique more accessible for field applications.

In summary, Electrochemical Impedance Spectroscopy is a versatile and insightful tool for monitoring battery State of Health. Its ability to non-invasively probe degradation mechanisms such as SEI growth, lithium plating, and cathode degradation makes it invaluable for EVs, grid storage, and other critical applications. While challenges remain in data interpretation and cost, ongoing advancements are expanding its practicality and adoption. As battery technologies evolve, EIS will continue to play a central role in ensuring performance, safety, and longevity.