In the pursuit of advancing electric vehicle technologies under global carbon neutrality goals, the safety and reliability of energy storage systems, particularly li-ion batteries, have become paramount. As a researcher focused on mechanical integrity and multiphysics phenomena, I embarked on a comprehensive study to understand the failure mechanisms of cylindrical li-ion batteries when subjected to various compression conditions. The li-ion battery, with its high energy density and cycle stability, is susceptible to mechanical abuse—such as crushing or indentation—which can trigger internal short circuits, thermal runaway, and catastrophic events. This work integrates experimental testing and finite element simulation to elucidate the mechanical-electro-thermal responses of 18650 cylindrical li-ion batteries, emphasizing the effects of loading configurations and state of charge (SOC). The insights gleaned aim to inform safer li-ion battery design and operational guidelines.
The core of this investigation revolves around the li-ion battery’s complex behavior under stress. A typical cylindrical li-ion battery comprises multiple layers—cathode, anode, separator, and electrolyte—encased in a metallic shell. When compressed, these components interact mechanically, electrically, and thermally, leading to potential failure. I designed experiments to simulate real-world abuse scenarios: plane compression, local indentation (using cylindrical and spherical indenters), and three-point bending. Each configuration represents distinct contact conditions that a li-ion battery might encounter in accidents or mishandling. The experimental setup included a universal testing machine for load application, digital image correlation for strain mapping, thermal imaging for temperature monitoring, and voltage measurement to detect internal short circuits. All tests were conducted quasi-statically at a displacement rate of 2 mm/min to isolate rate effects, with li-ion battery samples prepared at different SOC levels (0, 0.3, and 0.6) to assess energy state influences.
To quantify the mechanical properties, I employed a homogenized model for the li-ion battery, treating it as an isotropic material with plastic hardening. The constitutive relationship is expressed as:
$$ \sigma_{ys} = \sigma_{ys0} + k_m (\varepsilon_{pe})^n $$
where $\sigma_{ys}$ is the yield stress, $\sigma_{ys0}$ is the initial yield stress, $k_m$ is the strength coefficient, $n$ is the hardening exponent, and $\varepsilon_{pe}$ is the equivalent plastic strain. This formulation captures the nonlinear deformation of the li-ion battery under compression. For failure prediction, I adopted a unified strength theory criterion, which generalizes classical failure criteria. The equivalent stress $\sigma_{eq}^{Unified}$ is given by:
$$ \sigma_{eq}^{Unified} =
\begin{cases}
\sigma_1 – \frac{\alpha}{1+b}(b\sigma_1 – \sigma_3), & \text{if } \sigma \leq \frac{\sigma_1 + \alpha\sigma_3}{1+\alpha} \\
\frac{1}{1+b}(\sigma_1 + b\sigma_3) – \alpha\sigma_3, & \text{if } \sigma > \frac{\sigma_1 + \alpha\sigma_3}{1+\alpha}
\end{cases} $$
Here, $\sigma_1$ and $\sigma_3$ are the first and third principal stresses, $\alpha$ is the tension-compression ratio, and $b$ is a parameter that transitions between criteria (e.g., $b=0.5$ and $\alpha=1$ correspond to von Mises stress). In this study, I set $\sigma_{eq}^{Unified} = 16 \text{ MPa}$ as the failure initiation point for the li-ion battery.
The experimental results revealed distinct response patterns for each loading condition. Below is a summary table of key mechanical metrics extracted from the force-displacement curves:
| Loading Condition | Peak Force (kN) | Failure Displacement (mm) | Voltage Drop Time (s) | Max Temperature Rise (°C) |
|---|---|---|---|---|
| Plane Compression | 33.91 | 5.85 | Immediate | 34.0 |
| Cylindrical Indentation | 10.42 | 6.39 | Delayed with rebound | 34.8 |
| Spherical Indentation | 8.15 | 5.90 | Immediate | 40.2 |
| Three-Point Bending | 3.26 | 7.40 | No drop observed | Negligible |
Notably, the li-ion battery under plane compression exhibited the highest load-bearing capacity, but with earlier failure compared to local indentation. The force-displacement curve for plane compression showed four stages: initial shell resistance, gap compaction, rapid hardening, and post-peak softening. In contrast, local indentation led to more concentrated stress, causing earlier cracking and electrolyte leakage—especially with spherical indenters. The three-point bending test did not trigger internal short circuits, as the failure involved shell fracture without direct electrode contact, highlighting the dependency of electrical failure on deformation mode. These findings underscore that the safety of a li-ion battery is highly sensitive to loading geometry.
The influence of SOC on li-ion battery response was systematically evaluated. As SOC increases, more lithium ions are intercalated in the anode, leading to electrode expansion and increased internal pressure. This results in enhanced stiffness and peak force, but also elevates thermal runaway risk. The table below summarizes SOC effects for plane compression tests:
| SOC Level | Peak Force (kN) | Failure Displacement (mm) | Temperature at Failure (°C) | Internal Short Circuit Trigger |
|---|---|---|---|---|
| 0.0 | 31.50 | 5.70 | 25.5 | Yes, mild heating |
| 0.3 | 33.20 | 5.80 | 30.2 | Yes, moderate heating |
| 0.6 | 33.91 | 5.85 | 257.7 (thermal runaway) | Yes, severe heating |
The data indicates a 7% increase in peak force from SOC 0.0 to 0.6, coupled with a reduction in failure displacement. The high-SOC li-ion battery experienced violent thermal runaway due to exothermic reactions post-short circuit, emphasizing the critical role of energy content in safety assessments. The temperature evolution can be modeled via heat transfer equations accounting for internal heat generation. The general energy balance for a li-ion battery under abuse is:
$$ \rho C_p \frac{\partial T}{\partial t} = \nabla \cdot (k \nabla T) + q_{short} $$
where $\rho$ is density, $C_p$ is specific heat, $k$ is thermal conductivity, and $q_{short}$ is the heat power density from internal short circuits. This equation forms part of the multiphysics model developed in COMSOL, linking mechanical failure to thermal response.
To simulate these phenomena, I constructed a finite element model coupling mechanical, thermal, electrical, and short-circuit modules. The li-ion battery was modeled as a homogeneous cylinder with material properties derived from experimental calibration. The mechanical module used the plasticity law above, while the electrical module employed a lumped-parameter battery model for voltage prediction. Upon reaching the failure stress, the short-circuit module activated, applying a heat source to the damaged region. The model parameters are listed in the following table:
| Parameter | Symbol | Value | Unit |
|---|---|---|---|
| Initial Yield Stress | $\sigma_{ys0}$ | 12.5 | MPa |
| Strength Coefficient | $k_m$ | 150 | MPa |
| Hardening Exponent | $n$ | 0.25 | – |
| Density | $\rho$ | 2500 | kg/m³ |
| Specific Heat | $C_p$ | 900 | J/(kg·K) |
| Thermal Conductivity | $k$ | 5 | W/(m·K) |
| Short-Circuit Resistance | $R_{short}$ | 0.01 | Ω |
Simulation results aligned closely with experimental data, validating the model’s efficacy. For instance, under plane compression, the predicted force-displacement curve matched the experimental trend within 10% error, and the temperature distribution showed hotspots at the battery center, consistent with observed failure locations. The spherical indentation simulation captured stress concentration and early cracking, as evidenced by strain contours. The comparative analysis reinforced that the li-ion battery’s response is reproducible across scales, enabling predictive safety design.
Further analysis involved deriving analytical expressions for critical loads. For a cylindrical li-ion battery under plane compression, the peak force $F_{max}$ can be approximated by considering shell buckling and core yielding. A simplified model gives:
$$ F_{max} \approx \sigma_c A_c + \sigma_s A_s $$
where $\sigma_c$ and $\sigma_s$ are the compressive strengths of the core and shell, respectively, and $A_c$ and $A_s$ are their cross-sectional areas. For local indentation with a spherical indenter of radius $R$, the contact force $F$ relates to displacement $\delta$ via:
$$ F = \frac{4}{3} E^* R^{1/2} \delta^{3/2} $$
Here, $E^*$ is the effective modulus of the li-ion battery composite. These formulas provide quick estimates for engineers assessing li-ion battery crashworthiness.
The multiphysics interactions in a li-ion battery during compression are complex. Mechanical deformation alters the internal microstructure, increasing the risk of separator puncture and electrode contact. This triggers an internal short circuit, described by Ohm’s law with a time-varying resistance. The short-circuit current $I_{sc}$ is:
$$ I_{sc} = \frac{V_{oc}}{R_{short} + R_{internal}} $$
where $V_{oc}$ is the open-circuit voltage and $R_{internal}$ is the battery’s internal resistance. The resulting Joule heating $q_{short}$ is:
$$ q_{short} = I_{sc}^2 R_{short} $$
This heat source elevates temperature, potentially leading to thermal runaway if critical thresholds are exceeded. The model integrates these equations dynamically, capturing the cascade from mechanical abuse to thermal failure in li-ion batteries.
In addition to experimental and numerical work, I explored the effects of repeated loading on li-ion battery durability. While not covered in the initial study, cyclic compression tests suggest that fatigue degradation can reduce the failure threshold over time. This is crucial for applications where li-ion batteries face vibrational or incidental impacts. Future research should quantify fatigue life using S-N curves adapted for li-ion battery materials.
The role of battery aging (state of health, SOH) also merits attention. As a li-ion battery cycles, electrode materials degrade, altering mechanical properties. A generalized model could incorporate SOH via a degradation factor $D$ modifying the yield stress:
$$ \sigma_{ys} = (1 – D) \left( \sigma_{ys0} + k_m (\varepsilon_{pe})^n \right) $$
where $D$ ranges from 0 (new) to 1 (fully degraded). This extension would enhance the predictive capability for aged li-ion batteries in field conditions.
To summarize, this investigation demonstrates that the compression response of a cylindrical li-ion battery is highly dependent on loading configuration and SOC. Plane compression induces global failure with high forces, while local indentation causes localized damage with lower forces but earlier short circuits. Three-point bending may not trigger electrical failure due to fracture mode. Higher SOC increases mechanical robustness but exacerbates thermal hazards. The developed multiphysics model, validated against experiments, offers a tool for simulating abuse scenarios and optimizing li-ion battery designs. For instance, reinforcing shell thickness or using phase-change materials for thermal management could mitigate risks. These insights contribute to the broader goal of safer li-ion battery deployment in electric vehicles and energy storage systems.
Looking ahead, I plan to investigate dynamic loading conditions (e.g., impact tests) to assess rate sensitivity, as real-world crashes involve high strain rates. Additionally, integrating electrochemical models will allow prediction of capacity fade post-abuse. The li-ion battery community must continue cross-disciplinary efforts to address these challenges, ensuring that the transition to electrified transportation remains safe and sustainable. Through continued research, we can develop li-ion batteries that are not only high-performing but also resilient to mechanical insults, paving the way for a cleaner energy future.