In recent years, the escalating global energy crisis and environmental pollution have driven governments worldwide to promote the development of electric vehicles (EVs) as a sustainable alternative to traditional internal combustion engine vehicles. Compared to conventional燃油vehicles, pure electric vehicles can significantly reduce fuel consumption and lower environmental contamination. As a result, EVs have become a dominant trend in the automotive industry. However, their widespread adoption is hampered by critical issues such as range anxiety and safety concerns, particularly the risk of fire or explosion following collisions. The safety of lithium-ion batteries, the core energy storage components in EVs, is paramount to public acceptance of新能源汽车. Accidents involving thermal runaway or mechanical failure in lithium-ion batteries can lead to catastrophic outcomes, underscoring the urgent need for rigorous safety assessments.
To address these challenges, extensive research has been conducted on the crash safety of electric vehicles, focusing on areas such as material mechanical properties, single-cell testing, and multi-physics coupling. Despite these efforts, there remains a gap in detailed analyses of the entire modeling process for lithium-ion batteries and the mechanical传导patterns of battery modules under various collision scenarios. In this study, we aim to fill this gap by developing a simplified finite element model of lithium-ion battery单体和模组based on actual尺寸measurements. We validate the model against existing literature and subsequently analyze the mechanical传导laws and failure locations of battery modules under different impact conditions. This work seeks to provide insights that can inform the design of safer battery防护systems for electric vehicles.
The lithium-ion battery under investigation is a widely used 18650 ternary nickel-cobalt-manganese (NCM) cell. Accurate modeling begins with precise dimensional measurements, which are summarized in Table 1. These parameters are essential for creating a realistic geometric representation of the lithium-ion battery. The nominal capacity of this lithium-ion battery is 3250 mAh, with a charging voltage of 4.2 V and a discharge cutoff voltage of 2.5 V. Such specifications are typical for high-energy-density lithium-ion batteries used in electric vehicles, highlighting their importance in energy storage applications.
| Parameter | Value |
|---|---|
| Rated Capacity (mAh) | 3200 |
| Nominal Capacity (mAh) | 3250 |
| Cutoff Voltage (V) | 3.6 |
| Discharge Cutoff Voltage (V) | 2.5 |
| Charging Voltage (V) | 4.2 |
Using SolidWorks software, we constructed a three-dimensional model of the lithium-ion battery based on the measured dimensions. This model was then imported into Hypermesh for meshing. To balance computational accuracy and efficiency, we employed hexahedral elements with a grid size of 1 mm, as recommended in prior studies. The lithium-ion battery model was simplified into two main components: the outer steel shell and the inner wound core. The shell was modeled using shell elements with a thickness of 1 mm, while the wound core was represented by solid hexahedral elements. The total mesh count for the single lithium-ion battery model was 36,260 elements. This simplification is justified because the mechanical behavior of the lithium-ion battery under impact is primarily governed by these two components, with negligible effects from other internal细节such as the separator or electrolyte in purely mechanical analyses.
The material properties assigned to the lithium-ion battery components are critical for accurate simulation. For the steel shell, we used a linear elastic-plastic model with parameters derived from standard steel alloys. The wound core, composed of layered electrodes and separators, was modeled as a homogeneous orthotropic material to capture its anisotropic mechanical response. The constitutive relationships for these materials can be expressed using Hooke’s law for linear elasticity and a yield criterion for plasticity. For instance, the stress-strain relationship for the steel shell is given by:
$$ \sigma = E \epsilon $$
where $\sigma$ is the stress, $E$ is the Young’s modulus, and $\epsilon$ is the strain. For plastic deformation, we employed the von Mises yield criterion:
$$ \sigma_{vm} = \sqrt{\frac{1}{2}\left[(\sigma_1 – \sigma_2)^2 + (\sigma_2 – \sigma_3)^2 + (\sigma_3 – \sigma_1)^2\right]} $$
where $\sigma_{vm}$ is the von Mises stress, and $\sigma_1$, $\sigma_2$, $\sigma_3$ are the principal stresses. The material parameters used in the simulation are summarized in Table 2. These values are based on experimental data from literature to ensure the fidelity of the lithium-ion battery model.
| Component | Material | Young’s Modulus (GPa) | Density (kg/mm³) | Poisson’s Ratio | Yield Strength (MPa) |
|---|---|---|---|---|---|
| Steel Shell | MATL24 | 210.0 | 7.89e-6 | 0.30 | 235 |
| Wound Core | MATL63 | 1.5 | 2.80e-6 | 0.15 | 10* |
| Platen | MATL20 | 210.0 | 7.80e-6 | 0.30 | – |
| Support Platform | MATL20 | 210.0 | 7.80e-6 | 0.30 | – |
*Note: The wound core yield strength is based on a failure criterion where internal short circuits occur at 10 MPa stress.
To validate the finite element model of the lithium-ion battery, we simulated a quasi-static compression test, which is commonly used to assess the mechanical integrity of电池cells. The compression setup consisted of a rigid platen, the lithium-ion battery, and a fixed support platform, as shown in the validation model. The platen was assigned a velocity of 1 mm/ms to compress the电池by a displacement of 7 mm. Contact interactions were defined using surface-to-surface自动contact algorithms in LS-DYNA. The simulation results, specifically the force-displacement curve, were compared with experimental data from published studies. As illustrated in the validation plot, the仿真curve closely matches the experimental data, with both showing an initial linear elastic region followed by a plateau due to plastic deformation and internal structure collapse. The peak force and overall trend align well, confirming the validity of our lithium-ion battery model for mechanical abuse simulations.
The force-displacement relationship from the compression test can be mathematically described by a piecewise function. For the elastic region:
$$ F = k x $$
where $F$ is the force, $k$ is the stiffness, and $x$ is the displacement. For the plastic region, the force plateaus and can be modeled as:
$$ F = F_{plateau} $$
where $F_{plateau}$ is the sustained force during collapse. The agreement between simulation and experiment validates the material properties and modeling approach for the lithium-ion battery, enabling us to proceed with module-level analyses.
Building on the validated single-cell model, we developed a battery module model to investigate mechanical传导under crash conditions. The module consists of a simplified outer casing made of PA6 (polyamide 6) and an array of 60 lithium-ion battery cells arranged in a specific configuration. The module casing was modeled using shell elements with material properties as listed in Table 3. The arrangement of lithium-ion battery cells within the module is designed to mimic typical EV battery packs, with cells positioned in rows and columns to maximize energy density. This configuration is critical for understanding how impacts affect multiple lithium-ion battery cells simultaneously.
| Component | Material | Young’s Modulus (GPa) | Density (kg/mm³) | Poisson’s Ratio | Yield Strength (MPa) |
|---|---|---|---|---|---|
| Module Casing | PA6 | 2.32 | 1.13e-6 | 0.34 | 100 |
We conducted collision simulations on the battery module by applying an impact load using a rigid cylindrical indenter at different velocities and orientations. Two primary impact directions were considered: along the length and width of the module. The indenter was assigned velocities ranging from 1 mm/ms to 10 mm/ms to represent various crash severities. The dynamic response of the lithium-ion battery module was analyzed using explicit finite element analysis in LS-DYNA, with focus on stress distribution, deformation patterns, and failure initiation.
The mechanical传导within the module during impact can be described by wave propagation theory. When an impact occurs, stress waves travel through the module casing and into the lithium-ion battery cells. The wave speed in a material is given by:
$$ c = \sqrt{\frac{E}{\rho}} $$
where $c$ is the wave speed, $E$ is the Young’s modulus, and $\rho$ is the density. For the PA6 casing, $c \approx 1432 \text{ m/s}$, while for the steel shell of the lithium-ion battery, $c \approx 5150 \text{ m/s}$. This difference influences how stress is transmitted and localized within the module.
Under length-direction impact, the indenter strikes the module along its longest dimension. The stress distribution on the module casing is shown in the simulation results. The maximum von Mises stress exceeds 100 MPa at the contact area, indicating that the PA6 casing may fracture, potentially leading to ejection of lithium-ion battery cells. The force transmitted to the first row of lithium-ion battery cells is significant, causing high stress concentrations on their steel shells. The stress on these shells often surpasses the yield strength of 235 MPa, risking shell rupture and electrolyte leakage. The deformation of the lithium-ion battery cells is asymmetric, with cells tilting and intruding into neighboring cells, creating a chain reaction of mechanical abuse.
For width-direction impact, the indenter strikes the module along its shorter dimension. The stress patterns differ, with more localized deformation but higher peak stresses on the lithium-ion battery cells directly under impact. The module casing experiences lower overall stress compared to length-direction impact, but the affected area is more concentrated. The first row of lithium-ion battery cells again shows the highest stress, with values exceeding 235 MPa, indicating severe risk of failure.
To quantify the failure risk, we applied a failure criterion for the wound core of the lithium-ion battery. Based on literature, internal short circuits occur when the core stress reaches 10 MPa. The stress distribution in the wound cores during impact is visualized in the simulation云图. For length-direction impact, multiple lithium-ion battery cells in the first row exhibit core stresses above 10 MPa, indicating high probability of internal short circuits. In contrast, for width-direction impact, fewer cells exceed this threshold, but the ones that do are more severely stressed. This difference highlights the importance of impact orientation on the safety of lithium-ion battery modules.
The mechanical response of the lithium-ion battery module can be summarized using dynamic equations of motion. For a simplified mass-spring-damper system representing the module:
$$ m \ddot{x} + c \dot{x} + k x = F_{impact} $$
where $m$ is the effective mass, $c$ is the damping coefficient, $k$ is the stiffness, $x$ is the displacement, and $F_{impact}$ is the impact force. Solving this equation numerically helps understand the transient dynamics of the lithium-ion battery module during collision.
We further analyzed the effect of impact velocity on the mechanical传导. Higher velocities result in greater kinetic energy, leading to more severe deformation and higher stresses in the lithium-ion battery cells. The relationship between impact velocity and peak stress in the first row of cells can be approximated by a power law:
$$ \sigma_{peak} = \alpha v^\beta $$
where $\sigma_{peak}$ is the peak von Mises stress, $v$ is the impact velocity, and $\alpha$ and $\beta$ are constants determined from simulation data. For length-direction impact, $\beta \approx 1.5$, indicating a super-linear increase in stress with velocity, while for width-direction impact, $\beta \approx 1.2$, showing a slightly less sensitive response. This underscores the nonlinear behavior of lithium-ion battery modules under dynamic loading.
In addition to stress analysis, we evaluated the energy absorption characteristics of the lithium-ion battery module. The total energy absorbed during impact is the integral of the force-displacement curve:
$$ E_{absorbed} = \int F \, dx $$
where $E_{absorbed}$ is the absorbed energy, $F$ is the contact force, and $x$ is the crushing displacement. The module casing and lithium-ion battery cells contribute differently to energy absorption. The casing absorbs energy through elastic deformation and plastic yielding, while the lithium-ion battery cells absorb energy via cell collapse and internal friction. Table 4 summarizes the energy absorption for different impact scenarios, highlighting the role of each component in mitigating crash forces.
| Impact Direction | Impact Velocity (mm/ms) | Energy Absorbed by Casing (J) | Energy Absorbed by Cells (J) | Total Energy Absorbed (J) |
|---|---|---|---|---|
| Length | 1 | 15.2 | 28.7 | 43.9 |
| Length | 5 | 89.5 | 145.3 | 234.8 |
| Length | 10 | 210.4 | 320.1 | 530.5 |
| Width | 1 | 12.8 | 25.4 | 38.2 |
| Width | 5 | 75.6 | 130.8 | 206.4 |
| Width | 10 | 180.2 | 290.5 | 470.7 |
The data shows that the lithium-ion battery cells absorb more energy than the casing, emphasizing their role in crash energy management. However, this energy absorption is associated with cell damage, which can compromise the safety and functionality of the lithium-ion battery module. Therefore, optimizing the module design to balance energy absorption and cell protection is crucial for enhancing the crashworthiness of electric vehicles.
Another critical aspect is the propagation of failure within the lithium-ion battery module. Once a cell fails due to core stress exceeding 10 MPa, it can trigger thermal runaway, leading to cascading failures in adjacent cells. The risk of thermal runaway depends on the mechanical damage and the electrical configuration of the module. To model this, we can consider a coupled mechanical-thermal-electrical framework, but in this study, we focus solely on the mechanical aspects. The failure propagation speed can be estimated based on the stress wave speed and the arrangement of lithium-ion battery cells. For a linear array of cells, the time for failure to propagate from the first to the last cell is:
$$ t_{propagation} = \frac{(n-1) d}{c} $$
where $n$ is the number of cells, $d$ is the spacing between cells, and $c$ is the stress wave speed in the cells. For our module with 60 cells, $t_{propagation}$ is on the order of milliseconds, indicating rapid failure spread under severe impact.
We also investigated the effect of cell spacing and module casing thickness on mechanical传导. Increasing the spacing between lithium-ion battery cells reduces stress concentration but increases module volume, which may not be feasible for compact EV designs. Similarly, thickening the casing improves protection but adds weight. A parametric study was conducted by varying these parameters and simulating impacts. The results are summarized in Table 5, which provides guidance for optimizing module design to enhance the safety of lithium-ion batteries.
| Cell Spacing (mm) | Casing Thickness (mm) | Peak Stress in Cells (MPa) | Module Weight Increase (%) | Safety Index* |
|---|---|---|---|---|
| 1.0 | 2.0 | 280 | 0 | 0.5 |
| 2.0 | 2.0 | 240 | 5 | 0.7 |
| 3.0 | 2.0 | 210 | 10 | 0.8 |
| 1.0 | 3.0 | 250 | 15 | 0.6 |
| 2.0 | 3.0 | 220 | 20 | 0.9 |
| 3.0 | 3.0 | 190 | 25 | 1.0 |
*Safety Index: A normalized metric (0-1) based on peak stress and failure risk, with 1 being safest.
The findings suggest that a combination of moderate cell spacing and increased casing thickness can significantly improve the mechanical safety of lithium-ion battery modules without excessive weight penalty. This optimization is essential for practical EV applications where both safety and efficiency are paramount.
In conclusion, this study presents a comprehensive mechanical modeling and simulation framework for lithium-ion batteries, from single cells to modules. We developed and validated a finite element model of an 18650 lithium-ion battery using compression test data. The model was then extended to a battery module to analyze mechanical传导under different collision scenarios. Our simulations reveal that impact orientation and velocity critically influence stress distribution, deformation patterns, and failure initiation in lithium-ion battery modules. Length-direction impacts tend to affect more cells with lower peak stresses, while width-direction impacts cause higher localized stresses but on fewer cells. The failure criterion based on core stress (10 MPa) helps identify cells at risk of internal short circuits. Additionally, parametric studies on module design offer insights into optimizing cell spacing and casing thickness for enhanced crashworthiness.
This work contributes to the ongoing efforts to improve the safety of lithium-ion batteries in electric vehicles. By understanding the mechanical传导laws and failure mechanisms, manufacturers can design better protective structures and battery management systems. Future research should integrate multi-physics couplings, such as thermal and electrochemical responses, to fully capture the complex behavior of lithium-ion batteries under abuse conditions. Moreover, experimental validation of module-level impacts will further refine the models and ensure their reliability for real-world applications. Ultimately, advancing the mechanical integrity of lithium-ion batteries is key to fostering public trust and accelerating the adoption of electric vehicles worldwide.