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![Figure 2. Global future trends of EV popularization for road EVs [23].](publication/357895640/figure/fig2/AS:1114686674206721@1642773421817/Global-future-trends-of-EV-popularization-for-road-EVs-23_Q320.jpg)
Even though electric vehicles (EV) were invented over a century ago, their popularity has grown significantly within the last 10 years due to the development of Li-ion battery technology. This evolution created an increase in the fire risk and hazards associated with this type of high-energy battery. This review focuses on lessons learned from elec...
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Electromobility has grown rapidly, and especially in China, Europe, and the United States. Within Europe, Germany is the largest market. Our goal in this paper is to provide a data-driven overview of the key data, including the number of vehicles sold, place of registration, battery capacity, and charging power, in Germany. The results were generat...
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... The research contributes valuable insights for designing ventilation systems in tunnels, focusing on optimizing oxygen concentration to manage fire risks effectively while ensuring safe environments during emergencies [84]. Other significant perspectives on using Computational Fluid Dynamics (CFD) for fire safety evaluations, especially regarding smoke evacuation in parking areas, including those with electric fires, was studied by Brzezińska and Bryant [85]. Technical solutions were analyzed for mitigating fire hazards from electric vehicles and methods were presented of performance-based analysis for assessing fire safety in car parks. ...
... The focus was on understanding and mitigating these risks through performance-based analysis and using Computational Fluid Dynamics (CFD) simulations to model fire scenarios. The use of the Fire Dynamic Simulator (FDS) software for predicting smoke dispersion and temperature distribution during an EV fire is highlighted, illustrating its utility in planning for safe evacuation and firefighting operations [85]. ...
The proper design and installation of systems that enable the efficient control and removal of smoke and hot gases in underground parking facilities are necessary for protecting the public and property in the event of a fire. This paper discusses how studies using Computational Fluid Dynamics (CFD) related to smoke venting have contributed to improving fire safety in underground parking facilities. As vehicle fire incidents continue to rise globally, particularly in regions with a high density of underground parking, the need for comprehensive measures to mitigate these incidents has become increasingly urgent. This paper examines the applicability of CFD as a tool to address the challenges of smoke control in underground car parks, including those caused by fires involving electric vehicles. CFD application under various fire scenarios and ventilation strategies allows for identifying more effective smoke removal solutions, improving the protection of occupants and property. However, despite the potential of CFD simulations to enhance fire safety and smoke exhaust efficiency in underground parking, it is important to recognize the limitations of these simulations, particularly in dealing with the complex challenges posed by electric vehicle fires.
... In addition to conventional crash-worthiness, battery thermal runaway and fire have emerged as a new concern in BEV safety, as shown in figure 4. BEV fires have been reported in various scenarios, including charging [52], driving [53], parking [54], crash and post-crash fire [55]. The lithium-ion battery may catch fire if it is mechanically, thermally, or electrically abused. ...
... For individual cell-level experiments, the spherical punch, external short circuit, needle piercing, and thermal chamber tests are commonly employed in cell safety studies. These tests can potentially induce thermal runaway [53,[59][60][61][62][63][64][65][66][67]. ...
Driven by the rising number of fire incidents involving Battery Electric Vehicles (BEVs), this work reviews the current state of knowledge in electric vehicle battery safety, focusing on simulation and experiment methodologies. The critical importance of battery safety is emphasized by the potential for thermal runaway and fires due to various factors. These factors include design and manufacturing flaws, excessive current loads, mechanical damage, improper charging practices (overcharging/overdischarging), extreme temperature exposure, and even as-yet unidentified causes. This study provides a comprehensive review of methodologies employed in lithium-ion battery safety modeling and experiment for BEVs. The review includes various aspects. It includes the high voltage battery system in BEVs, battery safety considerations in BEVs, geometry modeling of battery cells, material modeling of battery cells, simulation framework for batteries, cell-level experiment, testing of materials for cell components, and the application of machine learning. Physics-based simulations that accurately predict battery thermal runaway are crucial for guaranteeing the safety and optimizing the performance of BEVs. While Finite Element Analysis (FEA) is a well-established technique for evaluating the crashworthiness of conventional vehicles, its application to BEVs presents several significant challenges. However, limited literature exists on cell-level experiments involving spray and dropping scenarios. Furthermore, additional data on melting points, thermal properties, and porosity is necessary for component-level testing. This work also highlights the need for robust friction and fatigue models, which remain a critical knowledge gap in this field. Finally, the integration of machine learning approaches for constitutive laws and the development of more complex frameworks are essential advancements for future research. This review is expected to provide a guide in simulation and experiment in EV battery safety engineering.
... Most of the behavioral measures are determined by accident reports and assessments of subjective experiences. They are mainly related to the extent of driving avoidance in different situations [3][4][5][6][7][8]. ...
While driving, stress and frustration can affect safe driving and pose the risk of causing traffic accidents. Therefore, it is important to control the driver’s anxiety level in order to improve the driving experience. In this paper, we propose and implement an intelligent system based on fuzzy logic (FL) for deciding the driver’s anxiety level (DAL). In order to investigate the effects of the considered parameters and compare the evaluation results, we implement two models: DAL Model 1 (DALM1) and DAL Model 2 (DALM2). The input parameters of DALM1 include driving experience (DE), in-car environment conditions (IECs), and driver age (DA), while for DALM2, we add a new parameter called the accident anxiety state (AAS). For both models, the output parameter is DAL. We carried out many simulations and compared the results of DALM1 and DALM2. The evaluation results show that the DAL is very good for drivers’ ages between 30 to 50 years old. However, when the driver’s age is below 30 or above 50, DAL tends to decline. With an increase in DE and IECs, the DAL value is decreased. But when the AAS is increased, the DAL is increased. DALM2 is more complex because the rule base is larger than DALM1, but it makes a better decision of DAL value.
... Cylindrical cells have benefits relative to other cell formats, namely pouch and prismatic cells, in terms of their mechanical stability due to even distribution of internal pressure build-up and slower failure propagation in multi-cell battery modules 12 thanks to air-filled gaps between individual cells which reduce thermal contact. 13 These advantages, paired with the suitability of cylindrical cells for automated manufacturing, mean that they are widely deployed in devices such as laptops, power tools and electric vehicles. ...
Acoustic emission (AE) is a low-cost, non-invasive, and accessible diagnostic technique that uses a piezoelectric sensor to detect ultrasonic elastic waves generated by the rapid release of energy from a localised source. Despite the ubiquity of the cylindrical cell format, AE techniques applied to this cell type are rare in literature due to the complexity of acoustic wave propagation in cylindrical architectures alongside the challenges associated with sensor coupling. Here, we correlate the electrochemical performance of cells with their AE response, examining the differences during pristine and aged cell cycling. AE data was obtained and used to train various supervised binary classifiers in a supervised setting, differentiating pristine from aged cells. The highest accuracy was achieved by a deep neural network model. Unsupervised machine learning (ML) models, combining dimensionality reduction techniques with clustering, were also developed to group AE signals according to their form. The groups were then related to battery degradation phenomena such as electrode cracking, gas formation, and electrode expansion. There is the potential to integrate this novel ML-driven approach for widespread cylindrical cell testing in both academic and commercial settings to help improve the safety and performance of lithium-ion batteries.
... Further development of EVs with lithium-ion batteries is indicated for fire safety (Bisschop, Willstrand, and Rosengren 2020;Dorsz and Lewandowski 2022). According to (Brzezinska and Bryant 2022), the thermal runaway and selfignition of lithium-ion batteries lead to most EV fire accidents. Moreover, compared to gasoline-caused vehicle fire accidents, EVs have raised doubts in terms of fire safety (H. ...
Electric vehicles (EVs) have played a significant role in sustainability, and EVs fire accidents have raised doubts in recent years. To solve the mobile analytical equipment limitation in EVs fire accident and help staff receive prompt results at on-spot inspection, we provide a lightweight but accurate Transformer that can ideally adapt to the mobile environment. First, we built on the simple Segformer and extended it to aggregate the representations of amorphous objects, such as fire traces, in image recognition. Second, we used shunt-based self-attention (SSA) to enhance the model for capturing multi-scale contextual information and help distinguish the deformed level of EVs after combustion. Third, we redesigned a simple multi-level information aggregation (MIA) decoder to obtain the relationship between pixels in the channel dimensions by a weighted aggregation. Furthermore, to foster image trace recognition, we put forwards and evaluated the accuracy of models on electric vehicle fire traces (EVFTrace), a dataset of images of burnt EVs. On EVFTrace, the mean intersection over union (mIoU) achieves 72.24%. The float point operations (Flops) and parameters (Params) achieve 114.83 G and 89.5 M. Our model shows excellent efficiency and accuracy for burnt EVs segmentation tasks.
... The fire caused an explosion and damage to the structure. Also, in Florida in 2020, a Porsche Taycan was completely burned while parking in a garage [7].In Michigan in 2023, An electric Ford F-150 Lightning caught fire due to a battery issue traced back to one of the automaker's suppliers. The blaze spread to two other electric pickups in a holding lot of Fords [8]. ...
... Electric car fires in garages do not pose a risk to people staying in the garage [28]. ...
Once a fire breaks out in an electric bus, it can easily lead to mass casualties and severe injuries, resulting in significant property damage and social impact. The high-temperature smoke and toxic gases in an electric bus fire are key factors that cause a large number of casualties, both of which are closely related to ventilation conditions. In view of this, this study utilized the Fire Dynamics Simulator (FDS 6) software to establish a three-dimensional experimental model of an electric bus. Numerical simulations of the fire combustion process in the electric bus under different ventilation conditions were conducted. Multiple fire scenes were established based on varying ventilation areas, different wind speeds, and diverse window opening positions. This study specifically analyzed the temperature and CO concentration variations under different fire scenes. By comparing the simulation results under different ventilation conditions, it can be concluded that when an electric bus catches fire, opening 100% of the windows, the wind speed is 8 m/s, and opening the rear window of the electric bus first can minimize the fire risk. Through the numerical simulation of electric bus fires under various conditions, this study analyzed the impact of different ventilation conditions on electric bus fires, providing a theoretical basis for firefighting and rescue efforts as well as personnel evacuation in electric bus fire incidents, with the ultimate goal of maximizing public safety.
... They analyze fire impacts on evacuation, rescue, and structures using Computational Fluid Dynamics (CFD). Brzezinska and Bryant (2022) detail battery fires in electric vehicles, addressing safety concerns and protection strategies. Acknowledging the lack of full-scale EV fire tests, they recommend accepted heat release rates for car park design. ...
Theoretical background: The theory of rational consumer choice significantly impacts the shape of the contemporary car market, which constitutes an essential part of the automotive industry and the national economy and has a considerable influence on the behavior of individuals. In the context of the car market, consumers’ decision-making process is subject to several factors, particularly in light of the EU’s initiative to transition the automotive industry towards zero emission solutions. Furthermore, this implies potential changes in the degree of impact on the course of transformation, adoption rate, and economic growth through network effects. Recent years have witnessed changes in various critical factors, alongside the emergence of new factors, which could significantly impact the competitiveness of electric vehicles in relation to internal combustion vehicles. Purpose of the article: The article aims to examine the current condition of the Polish car market in the post-COVID-19 period with particular emphasis on the electric vehicle market and indicate its present shape in comparison to the market of conventional vehicles from the supply perspective. Also, it attempts to identify and define the most critical factors that influenced the development of the market and their role in the coming years. Identifying and categorizing the most critical factors will allow us to indicate the current weaknesses of the zero-emission vehicle market. This may allow for more efficient identification and solving of problems standing in the way of its development. Research methods: In order to realize the goals of the research, several methods were used: a critical analysis of the literature on the subject; a quantitative analysis of statistical data was used along with qualitative research to examine the factors that impacted the car market in Poland. As a result, a network of categories describing the associations between factors and their effects on the researched topic was identified and studied. Main findings: Examination of Poland’s electric vehicle market reveals a complex interplay of variables across market. The identified combined factors impede mass adoption of battery electric vehicles, resulting in dynamic yet relatively insignificant annual percentage changes in market growth within the overall passenger vehicle market. The problems focus on governmental, economic and social factors, but also on very important technological and ecological factors, questioning in some cases the current form of electromobility on the Polish market.
... To investigate the basic laws governing fire spread and mechanical structure response, a pool fire was employed in this study to simulate the initial stage of a vehicle fire. Despite differences in heat release rate profiles [33][34][35], the pool fire retains a certain degree of representativeness during its early stages. ...
... Additionally, gasoline is easily accessible, and simulating automobile fires using gasoline also exhibits high experimental reproducibility. However, it is worth mentioning that the simulation of new energy vehicle battery fires [35] is closely related to gas diffusion and combustion characteristics, which significantly differs from traditional fuel pool fire simulations. Therefore, the study of fuel fires is primarily focused on in this paper. ...
... where Q represents HRR in Figure 7 [41], which belongs to the ultrafast fire in this paper; A represents the projected combustion area; m ′′ represents the mass loss rate per unit area of the large fuel pool (>5 m 2 ), taken as 0.055 kg·m −2 ·s −1 ; χ represents the combustion efficiency, taken as 70% for gasoline; and ∆H c represents the heat of combustion for gasoline. The use of the t 2 fire in the FDS simulation is widely practiced in fire science research, especially when simulating specific scenarios like car fires [35]. Non-steady-state fires can be represented as t 2 fires, and during the initial growth stage of a fire, the HRR approximately follows a t 2 relationship with time [41,42]. ...
In this paper, the firing process and structural failure behavior of outdoor mechanical car parks are innovatively investigated under diverse conditions, leveraging fire experiments, FDS fire simulation, and finite element simulation. The fire experiments reveal the intricate interplay between flame spread and airflow, highlighting the enhanced risk of fire propagation among adjacent spaces. The temperature profile, mirroring the fire’s lifecycle, is delineated into three distinct stages: initial growth, full development, and eventual decay. Notably, full-scale fire simulation in FDS validates the experimental outcomes, underscoring the scalability and reliability of our scaled-down experiments. Furthermore, finite element simulations offer a profound understanding of structural safety in various parking spaces during a fire. Critically, the susceptibility of columns to failure underscores the imperative need for enhanced fire prevention measures in column design, representing a significant advancement in fire protection engineering.
... The production site of electric power workers has very high requirements for personnel safety management [1][2][3]. Although some units have implemented door security, it is generally applied in a small range, most of which are only for office areas [4][5][6][7][8]. At the same time, there is a common situation of mixed traffic between people and vehicles, and related statistics rely on manual labor. ...
To address the issues of low efficiency and high complexity of detection models for electric power workers in distribution rooms, the electric power worker identification approach is proposed. The ArcFace loss function is used as the coordinate regression loss of the target box. According to the score, the template box with the highest score is selected for prediction, which speeds up the rate of convergence. Dimensional clustering is used to set template boxes for bounding box prediction. The experimental results show that the improved YOLOv3 is a high-performance and lightweight model. The electric power worker identification approach proposed in this paper has a high-speed recognition process, accurate recognition results. The effectiveness of the approach is verified with better detection performance and robustness.
