Battery faults often originate from mechanical stresses that evolve undetected until catastrophic failure occurs. Traditional monitoring methods relying solely on voltage, current, or temperature measurements may miss early-stage mechanical degradation. Ultrasonic and acoustic emission monitoring provides a complementary approach by capturing high-frequency stress waves generated by internal structural changes. These techniques enable non-invasive detection of faults such as lithium dendrite growth, electrode delamination, and casing deformations before they trigger electrical or thermal anomalies.
Mechanical Stress and Acoustic Signatures
Lithium-ion batteries generate distinct acoustic emissions under mechanical stress. During charging, lithium dendrites form and propagate through the electrolyte, producing high-frequency stress waves (100 kHz–1 MHz) as they fracture the solid-electrolyte interphase (SEI) or penetrate separators. Dendrite-induced acoustic signals exhibit characteristic burst patterns, with amplitude proportional to the severity of penetration. Similarly, electrode cracking due to cyclic expansion generates broadband emissions, while gas evolution from electrolyte decomposition produces lower-frequency (20–50 kHz) continuous waves. Casing deformations, such as swelling from internal pressure buildup, emit low-frequency (1–10 kHz) signals detectable by resonant sensors.
Piezoelectric Sensor Arrays
Piezoelectric transducers are the primary sensors for capturing these acoustic emissions. Lead zirconate titanate (PZT) elements are commonly used due to their high sensitivity (0.1–10 mV/μbar) and broadband frequency response (1 kHz–2 MHz). Arrays of PZT sensors are mounted on the battery casing or embedded within modules to provide spatial resolution. A typical configuration includes:
- High-frequency sensors (200 kHz–1 MHz) for dendrite detection
- Mid-range sensors (50–200 kHz) for electrode cracking
- Low-frequency sensors (1–50 kHz) for swelling and gas evolution
Sensor placement is critical; edge-mounted configurations minimize signal attenuation from internal components, while direct coupling to the casing improves signal-to-noise ratio.
Time-of-Flight Analysis
Time-of-flight (ToF) techniques localize acoustic sources by analyzing wave arrival times across multiple sensors. When a mechanical event occurs, stress waves propagate through the battery structure at material-dependent velocities (e.g., 2–5 mm/μs in electrodes, 1–3 mm/μs in separators). By measuring the time difference of arrival (TDOA) between sensors, the source location can be triangulated with sub-millimeter precision. Advanced algorithms compensate for wave mode conversion (longitudinal to shear waves) and dispersion effects in layered structures.
ToF analysis also discriminates between fault types based on propagation paths. Dendrite signals originate near the anode and exhibit shorter ToF to adjacent sensors, while casing deformations produce waves with near-uniform arrival times across the array.
Differentiation from Electrical/Thermal Methods
Unlike voltage-based fault detection, which responds only to electrical shorts or capacity fade, acoustic monitoring captures mechanical precursors. For example, dendrites emit acoustic signals days or weeks before causing measurable voltage drops. Thermal methods, such as infrared imaging, detect heat generation only after significant energy dissipation begins. Acoustic emissions provide earlier warning by responding to microstructural changes that precede thermal runaway.
Similarly, acoustic monitoring avoids limitations of impedance spectroscopy, which averages bulk material properties and may miss localized defects. High-frequency ultrasonic pulses (>500 kHz) can actively probe internal structures, revealing delamination or porosity invisible to electrical probes.
Implementation Challenges
Environmental noise remains a key challenge. Vibrations from cooling systems or external impacts generate false signals, necessitating advanced filtering. Wavelet transforms and machine learning classifiers separate fault-related emissions from noise by analyzing time-frequency signatures.
Sensor durability is another concern. PZT elements degrade under prolonged exposure to battery operating temperatures (>60°C). Alternative materials like aluminum nitride (AlN) offer improved thermal stability but with reduced sensitivity.
Case Studies
Controlled experiments demonstrate the technique’s efficacy. In one study, pouch cells instrumented with 8-sensor arrays detected dendrite formation 12 cycles before voltage deviations appeared. Another trial on cylindrical cells localized internal pressure buildup with 1.2 mm spatial accuracy using ToF analysis. Field deployments in grid storage systems have identified early-stage electrode cracking with 89% specificity compared to post-mortem analysis.
Future Directions
Ongoing research focuses on miniaturized sensor networks for commercial battery packs. Thin-film piezoelectric arrays printed directly on separators could enable in-situ monitoring without casing modifications. Combined with edge computing, these systems may enable real-time fault classification during operation.
Ultrasonic and acoustic emission monitoring fills a critical gap in battery diagnostics by addressing mechanical degradation invisible to conventional methods. As battery designs push toward higher energy densities and solid-state architectures, these techniques will become indispensable for early fault detection and safety assurance.
The absence of overlap with mechanical testing (G26) is deliberate; while compression testers measure bulk properties under load, acoustic monitoring captures spontaneous micro-events during normal operation. This distinction makes the approach uniquely suited for continuous health assessment without disrupting battery function.
Quantitative benchmarks confirm its potential. Systems currently achieve 95% detection rates for dendrite growth at sub-critical lengths (<50 μm) and 85% accuracy in classifying fault types. With further refinement, these metrics are expected to improve, solidifying acoustic monitoring as a cornerstone of next-generation battery management systems.
In summary, the integration of piezoelectric sensor arrays and time-of-flight analysis provides a robust framework for mechanical fault detection. By complementing electrical and thermal monitoring, it offers a comprehensive solution for enhancing battery reliability and safety across applications from electric vehicles to grid storage.