Propagation mechanism of electric vehicle lithium battery thermal runaway in tunnel environments: Analysis of smoke flow and combustion characteristics in confined spaces

Research Article
Open access

Propagation mechanism of electric vehicle lithium battery thermal runaway in tunnel environments: Analysis of smoke flow and combustion characteristics in confined spaces

Minghui Lai 1*
  • 1 Southwest Jiaotong University    
  • *corresponding author rara481846778@gmail.com
Published on 5 December 2024 | https://doi.org/10.54254/2977-3903/2024.18127
AEI Vol.14
ISSN (Print): 2977-3911
ISSN (Online): 2977-3903

Abstract

This rise in the deployment of lithium-ion batteries in electric cars presents new fire hazards, especially in places such as tunnels where thermal runaway situations are highly dangerous. This work investigates the propagation of thermal runaway in lithium-ion batteries within tunnels, including smoke flow, toxic gas diffusion and heat distribution under various ventilation conditions and tunnel shapes. Tests with 18650 lithium-ion cells were carried out on tunnels with gradients (0°, 2°, and 5°), followed by CFD simulations of the results. We measured smoke spread, temperature, and toxic gas concentrations (CO, HF, CO2) at airflow rates from 0.5 to 3 m/s. The findings indicated that tunnel slope and ventilation rates had a direct influence on smoke content, gas content and evacuation probability, and that sloping tunnels held more smoke at the ends. These results underscore the need for tailored ventilation to facilitate egress and avoid exposure to toxic gases. This work can inform better fire-safety practices in tunnels as electric vehicles continue to become more common.

Keywords:

Thermal runaway, lithium-ion batteries, tunnel fire safety, smoke propagation, toxic gas dispersion

Lai,M. (2024). Propagation mechanism of electric vehicle lithium battery thermal runaway in tunnel environments: Analysis of smoke flow and combustion characteristics in confined spaces. Advances in Engineering Innovation,14,1-6.
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1 Introduction

The popularity of EVs has grown dramatically in recent years, thanks to developments in lithium-ion battery technology and growing concern with the environment. But as EV usage rises, so does the risk of fire – especially in tunnels, where the risks inherent to lithium-ion batteries are magnified. Lithium-ion batteries are susceptible to thermal runaway, a self-generating exothermic reaction that produces excess heat, smoke and toxic fumes. For open areas, these can be confined to a certain extent, if ventilated and controlled by fire suppression. But in tunnels where natural ventilation is absent and airflow may be restricted, thermal runaway is extremely dangerous – potentially hazardous to tunnel infrastructure and humans. As previous experiments demonstrated, tightened environments such as tunnels alter the normal dispersal and distribution of smoke and heat during thermal runaway processes. The tunnel’s enclosed construction can create layers of smoke, stratification, and turbulence, making it difficult to see and exit. In addition, the build-up of deadly gases, including carbon monoxide (CO) and hydrogen fluoride (HF), can pose a serious risk, because these gases have the potential to become fatal in just minutes. Good ventilation is extremely important in such situations as it directly affects the spread and density of smoke and gases, which may be useful in determining whether or not to evacuate [1]. This paper extends the existing work to specifically examine lithium battery explosions in tunnels. It examines the effects of tunnel shape (inclination, length) and ventilation rates on heat, smoke and noxious gases in tunnels. Using a combination of physical experiments and CFD simulations, this work aims to achieve an insight into tunnel thermal runaway, enabling fire-fighting strategies to be tailored to meet the special challenges faced by electric vehicles along constrained highways.

2 Literature review

The phenomenon of thermal runaway in lithium batteries has been extensively examined, particularly in open environments and residential spaces where ventilation and safety controls are more readily implemented. Prior research has shown that lithium battery fires in confined spaces result in complex smoke behaviors, such as stratification and layering, which significantly hinder visibility and create additional challenges for firefighting efforts. Studies have emphasized that ventilation strategies within tunnel environments play a crucial role in controlling smoke dispersion and reducing concentrations of toxic gases [2]. Additionally, the geometry of confined spaces, including variations in tunnel slope and length, has been found to influence heat flux and temperature distributions during thermal runaway events. Specifically, sloped tunnels tend to exhibit higher concentrations of smoke in lower regions due to gravity-driven flows. Building on these insights, this study focuses on lithium battery fires in tunnel environments to further explore how tunnel geometry and ventilation conditions influence fire behavior and the spread of toxic emissions [3].

3 Experimental methodology

3.1 Materials and equipment

To simulate thermal runaway in electric vehicle lithium-ion batteries, we selected 18650 lithium-ion cells (3.7 V, 2.5 Ah). Scaled tunnel models with varying slopes (0°, 2°, and 5°) were constructed to investigate the effects of inclination on smoke flow and toxic gas accumulation. Gas monitors and thermocouples were installed within each tunnel to measure concentrations of CO, HF, and CO₂ and track temperature changes. A ventilation system simulating real tunnel airflow was set up with adjustable speeds (0.5 to 3 m/s) to assess the influence of different ventilation conditions on smoke diffusion and toxic gas concentrations [4].

3.2 Computational simulation setup

To validate experimental results, CFD simulations were conducted using ANSYS Fluent software. The simulated tunnel model was 50 meters long with slopes of 0°, 2°, and 5° [5]. A local heat source at 300°C was used to initiate thermal runaway, with smoke production set at 0.02 kg/s. Key parameters, including smoke propagation rate, temperature distribution, and toxic gas levels, were monitored at specified locations along the tunnel. This approach allowed for analysis of smoke movement and heat accumulation, examining the impact of ventilation rates and tunnel slopes on lithium battery fires [6].

4 Experimental procedure

4.1 Initiation of thermal runaway

To simulate lithium-ion battery thermal runaway in a tunnel environment, 18650 lithium-ion cells were positioned at the center of each tunnel model. The ambient temperature around the cells was gradually raised beyond 200°C using a high-temperature furnace to trigger the exothermic reactions characteristic of thermal runaway. Upon initiation, the cells released high-temperature gases, dense smoke, and toxic by-products such as CO, CO₂, and HF, replicating the conditions of lithium battery fires in real-world scenarios [7]. The heat from combustion sustained the reaction, with visible increases in smoke density and toxicity, highlighting the unique behavior of such fires in confined spaces.

4.2 Data collection on smoke propagation

As thermal runaway continued, thermocouples placed at 5-meter intervals along the tunnel measured temperature changes to map the heat distribution. Readings at various heights captured the layering effects of hot smoke rising and cooler air settling below, providing insights into heat gradients within the tunnel. Gas analyzers, also positioned at these intervals, continuously recorded concentrations of CO, HF, and CO₂ every 30 seconds over a 15-minute duration. This high-resolution data on gas concentration and distribution patterns allowed for a detailed analysis of smoke stratification and gas accumulation, critical for assessing risks to occupants in emergency scenarios [8]. Figure 1 displays the temperature changes at a 5-meter distance from the heat source, highlighting the gradual temperature rise and heat distribution along the tunnel as the thermal runaway progresses.

/word/media/image1.png

Figure 1. Temperature at 5m over Time

4.3 Ventilation variation

The experiment was conducted at three ventilation rates (0.5, 1, and 3 m/s) to assess the effects of airflow on smoke and gas dispersion. Each rate was consistently applied during runs, simulating typical operational airflow speeds in tunnels. Temperature, gas concentration, and visibility were recorded over the 15-minute test to observe how well each ventilation rate managed smoke density, heat, and toxic gas concentrations. Higher ventilation rates (3 m/s) effectively dispersed gases like CO and HF, reducing their concentration near escape routes, whereas lower rates (0.5 m/s) allowed for higher toxic gas accumulation [9]. This setup provided a comprehensive view of how ventilation impacts smoke behavior and gas hazards in confined tunnel environments.

Table 1 presents the experimental data on temperature, gas concentrations (CO, CO₂, and HF), and visibility at various ventilation rates (0.5, 1, and 3 m/s) during a simulated lithium battery thermal runaway event within a tunnel environment. Figure 2 presents visibility changes at a 0.5 m/s ventilation rate, demonstrating the reduction in visibility due to smoke density and how limited ventilation exacerbates the hazard during evacuation.

/word/media/image2.png

Figure 2. Visibility at 0.5 m/s over Time

Table 1. Tunnel Fire Experiment Data

Time (min)

Temperature at 5m (°C)

Temperature at 10m (°C)

Temperature at 15m (°C)

CO Concentration (ppm)

CO2 Concentration (ppm)

HF Concentration (ppm)

Visibility at 0.5 m/s (m)

Visibility at 1 m/s (m)

Visibility at 3 m/s (m)

0.5

141.1590357

143.0034959

101.7876837

409.8142464

5003.572865

19.21606576

2.011863495

4.797680291

7.832298259

1

148.2853774

144.36291

115.9783208

413.2685837

5074.627984

21.66715965

1.874688365

5.032147273

7.948813899

1.5

161.0422853

132.9874684

106.5177958

411.7054684

5160.245102

19.88545728

1.861568568

5.033724913

7.840771832

2

154.8490616

131.4927635

111.1061186

435.288823

5153.313866

20.39909159

1.703584937

5.14631046

8.47966146

2.5

153.2669829

138.7382156

111.6090517

437.2197323

5091.824463

20.9797916

1.911861071

4.851534358

8.082569694

3

151.0129289

141.1132103

109.9090166

450.4658831

5037.817404

22.84825626

1.830746357

4.959633122

7.755142733

3.5

151.1569304

133.8037308

108.6269423

443.9340298

5012.454396

22.49858651

2.018225352

4.898875511

8.407670793

4

161.3839296

136.6399885

116.7826637

474.6366871

5190.429028

20.96353442

1.823059496

4.90391399

7.740524787

4.5

156.6264327

137.2942246

119.9993253

474.6660905

5221.222964

23.27731316

1.918274672

4.465395517

7.981924859

5

160.0472287

138.7750232

113.8846739

484.1884262

5145.596296

22.18741192

1.816497259

5.221601026

8.11801512

5.5

161.0427317

142.7284267

110.6248083

455.6192105

5450.127414

22.38854825

1.699636314

4.399845417

8.103609425

6

169.9535908

142.0865801

124.3235889

512.8118868

5220.235248

19.92490257

1.75074769

4.910895477

8.120865864

6.5

160.4818957

143.2878075

115.8922426

515.9271823

5323.125132

24.4511078

1.858853974

5.103300483

7.848523745

7

157.7810663

139.4575869

119.8152043

535.2363095

5346.690147

23.11948458

1.565394861

5.021011648

7.892273612

7.5

167.7648978

151.8846233

114.7403451

491.6027443

5239.794748

25.35357526

1.402986478

4.590162446

7.436547065

8

163.0936424

143.4367947

128.6924585

519.3361761

5369.112549

24.55605379

1.577680885

4.427953695

7.672455622

8.5

163.1058909

140.491263

114.4292028

518.1707239

5339.33891

23.65218565

1.553504822

4.917403619

7.68547304

9

167.2578365

136.4343363

126.1472384

522.8474367

5439.638117

23.91769412

1.548536302

4.788529034

7.750609077

9.5

170.6518243

140.756101

128.5727226

549.8650578

5429.621027

24.39236592

1.532869471

4.878472112

7.83554202

10

164.9538363

152.3798085

127.2022975

559.0623763

5574.846488

25.83118057

1.553085339

4.755255833

7.619109558

10.5

179.3208315

156.5257307

115.5149594

565.2124451

5510.032537

25.88031142

1.492732968

4.488918072

7.968377178

11

173.1512258

144.2256838

122.7206107

563.458274

5636.995858

25.80106439

1.386642864

4.583563937

8.038547551

11.5

175.7077058

156.3049067

121.6001617

541.4866305

5622.012153

27.08167507

1.32268886

4.563961402

8.070798484

12

175.9722904

147.6168754

120.4210313

582.0162433

5584.558138

25.69239057

1.437135131

4.183267646

7.658931245

12.5

173.0556762

146.5428502

126.1394328

583.5977341

5471.920743

24.33327634

1.398437228

4.968718198

7.812259795

13

173.8213686

141.2636358

127.5112771

591.1416689

5472.663519

25.00942903

1.370757157

4.566981486

7.609103229

13.5

179.3592751

151.8088799

127.4792704

611.2277103

5674.731897

27.11430532

1.342118956

4.497637747

7.742423676

14

174.1924103

146.5085224

128.7478572

616.1227017

5663.973808

27.50423794

1.61497677

4.875389475

7.260919288

14.5

177.6126232

155.3006612

128.5107214

619.0577356

5845.731007

27.1442719

1.267661464

4.692268405

7.643940303

15

186.6567016

149.7341558

125.3367713

634.4217603

5660.294576

26.49144523

1.198626935

4.549894153

7.2872001

5 Discussion

5.1 Smoke propagation dynamics in tunnel environments

The dynamics of smoke flow through a tunnel inside a tunnel during a thermal runaway event is complex and is controlled by a number of interdependent factors. One of the important factors is the rate of initial smoke exit, which depends on the degree of the thermal runaway process and the ventilation conditions in the tunnel. Simulations reveal that under low-ventilation conditions smoke reaches the ceiling in thick strata, severely reducing visibility and limiting evacuation [10]. Its initial release of hot gases blows smoke upwards, which cools as it moves up and down. For steep-sided tunnelling systems, smoke travels in gravity-based flow towards the bottom of the tunnel and builds up at a rate that depends on the angle of the slope. According to their findings, a 2-degree slope increases smoke density at the bottom end by 30% compared with straight tunnels, making visibility even more difficult and necessitating more ventilation.

5.2 Heat flux and temperature profiles

In the context of a thermal runaway, smoke inflow through a tunnel inside a tunnel is highly complex and determined by many mutually reinforcing conditions. The rate of early smoke exit is a significant factor, depending on the extent of the thermal runaway process and ventilation in the tunnel. Simulations show that smoke rises up to the ceiling in dense layers at low ventilation, greatly limiting visibility and evacuation. Its first spurt of warm gaseous gases expel smoke up and up and up, cooling as it ascends and descends. For steep-sided tunnellings, smoke flows by gravity to the base of the tunnel and accumulates depending on the slope angle [11]. Their research suggests that a 2-degree pitch makes the smoke at the bottom end 30% heavier than a straight tunnel, makes it more difficult to see, and requires more ventilation.

5.3 Toxic emission composition and health impacts

/word/media/image3.png

Figure 3. CO Concentration over Time

Lithium battery thermal runaway also emits toxic gases such as carbon monoxide (CO), hydrogen fluoride (HF), and carbon dioxide (CO2). Both gases present different hazards to health and to the environment, especially in sealed tunnels. When measured, CO concentrations 20 metres away can reach 1000 ppm in the first 5 minutes, a level that’s fatal if breathed in for extended periods. Emissions of hydrogen fluoride are another issue, since HF reacts with moisture in the atmosphere to produce hydrofluoric acid, a corrosive and dangerous chemical. Under ventilating conditions where air flow is constrained, CO and HF exceed Occupational Safety and Health Administration (OSHA) permissible exposure limits by 5-7, posing serious hazards for tunnel-users and first responders. Thus, adequate evacuation procedures and respiratory protection equipment are needed to minimise exposure risks during such events [12]. Figure 3 shows the CO concentration levels over time, illustrating the rapid increase in toxic gas accumulation, which poses significant health risks in confined spaces.

6 Conclusion

The authors examined the mechanisms of lithium-ion thermal runaway of a battery inside a tunnel by investigating the spreading of smoke, dispersal of poisonous gases, and temperature over a range of ventilation rates and tunnel shapes. Explicit models and CFD simulations indicated that tunnel slope and ventilation played a key role in smoke and gas dynamics, with sloped tunnels accumulating more smoke at the bottom through gravity-driven flow. Higher rates of ventilation helped to spread harmful gases such as CO and HF away, bringing concentrations down to acceptable values in high-flow settings. Yet, in low ventilation environments, harmful gases reached dangerous levels, highlighting the need for customised ventilation. This study underscores the need for specific fire safety measures in tunnel spaces as the number of electric vehicles grows. By providing additional insights into the relationship between tunnel geometry, ventilation, and fire behaviour, this research can help shape emergency response and evacuation systems to ensure greater safety for tunnel visitors and emergency workers. Future work should include real-time monitoring and customised ventilation to improve fire suppression in tunnels and other enclosed spaces with electric cars.


References

[1]. Degen, F., et al. (2023). Energy consumption of current and future production of lithium-ion and post lithium-ion battery cells. Nature Energy, 8(11), 1284-1295.

[2]. Wei, G., et al. (2023). A comprehensive insight into the thermal runaway issues in the view of lithium-ion battery intrinsic safety performance and venting gas explosion hazards. Applied Energy, 349, 121651.

[3]. Schöberl, J., et al. (2024). Thermal runaway propagation in automotive lithium-ion batteries with NMC-811 and LFP cathodes: Safety requirements and impact on system integration. Etransportation, 19, 100305.

[4]. Quilty, C. D., et al. (2023). Electron and ion transport in lithium and lithium-ion battery negative and positive composite electrodes. Chemical Reviews, 123(4), 1327-1363.

[5]. Bjelland, H., et al. (2024). Tunnel fire safety management and systems thinking: Adapting engineering practice through regulations and education. Fire Safety Journal, 146, 104140.

[6]. Kay, K., et al. (2023). Tasks and their role in visual neuroscience. Neuron, 111(11), 1697-1713.

[7]. Bjørnsen, G., Billett, S., & Njå, O. (2023). First responders' perceived and actual competence in tunnel fire safety. Fire Safety Journal, 136, 103758.

[8]. Sirengo, K., et al. (2023). Ionic liquid electrolytes for sodium-ion batteries to control thermal runaway. Journal of Energy Chemistry, 81, 321-338.

[9]. Lombardi, M., Berardi, D., & Galuppi, M. (2023). A critical review of fire tests and safety systems in road tunnels: limitations and open points. Fire, 6(5), 213.

[10]. Lee, W. M., et al. (2023). A review of test Methods, issues and challenges of Large-Scale fire testing of concrete tunnel linings. Construction and Building Materials, 392, 131901.

[11]. Mallick, S., & Gayen, D. (2023). Thermal behaviour and thermal runaway propagation in lithium-ion battery systems–A critical review. Journal of Energy Storage, 62, 106894.

[12]. Talele, V., et al. (2023). Computational modelling and statistical evaluation of thermal runaway safety regime response on lithium-ion battery with different cathodic chemistry and varying ambient condition. International Communications in Heat and Mass Transfer, 146, 106907.


Cite this article

Lai,M. (2024). Propagation mechanism of electric vehicle lithium battery thermal runaway in tunnel environments: Analysis of smoke flow and combustion characteristics in confined spaces. Advances in Engineering Innovation,14,1-6.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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Journal:Advances in Engineering Innovation

Volume number: Vol.14
ISSN:2977-3903(Print) / 2977-3911(Online)

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References

[1]. Degen, F., et al. (2023). Energy consumption of current and future production of lithium-ion and post lithium-ion battery cells. Nature Energy, 8(11), 1284-1295.

[2]. Wei, G., et al. (2023). A comprehensive insight into the thermal runaway issues in the view of lithium-ion battery intrinsic safety performance and venting gas explosion hazards. Applied Energy, 349, 121651.

[3]. Schöberl, J., et al. (2024). Thermal runaway propagation in automotive lithium-ion batteries with NMC-811 and LFP cathodes: Safety requirements and impact on system integration. Etransportation, 19, 100305.

[4]. Quilty, C. D., et al. (2023). Electron and ion transport in lithium and lithium-ion battery negative and positive composite electrodes. Chemical Reviews, 123(4), 1327-1363.

[5]. Bjelland, H., et al. (2024). Tunnel fire safety management and systems thinking: Adapting engineering practice through regulations and education. Fire Safety Journal, 146, 104140.

[6]. Kay, K., et al. (2023). Tasks and their role in visual neuroscience. Neuron, 111(11), 1697-1713.

[7]. Bjørnsen, G., Billett, S., & Njå, O. (2023). First responders' perceived and actual competence in tunnel fire safety. Fire Safety Journal, 136, 103758.

[8]. Sirengo, K., et al. (2023). Ionic liquid electrolytes for sodium-ion batteries to control thermal runaway. Journal of Energy Chemistry, 81, 321-338.

[9]. Lombardi, M., Berardi, D., & Galuppi, M. (2023). A critical review of fire tests and safety systems in road tunnels: limitations and open points. Fire, 6(5), 213.

[10]. Lee, W. M., et al. (2023). A review of test Methods, issues and challenges of Large-Scale fire testing of concrete tunnel linings. Construction and Building Materials, 392, 131901.

[11]. Mallick, S., & Gayen, D. (2023). Thermal behaviour and thermal runaway propagation in lithium-ion battery systems–A critical review. Journal of Energy Storage, 62, 106894.

[12]. Talele, V., et al. (2023). Computational modelling and statistical evaluation of thermal runaway safety regime response on lithium-ion battery with different cathodic chemistry and varying ambient condition. International Communications in Heat and Mass Transfer, 146, 106907.