Safety Of Electric Vehicles Research Articles

Application of thermotropic ferroelectric liquid crystals in electrical vehicle

This intermediate phase between solid and liquid enables liquid crystal engineers for various interesting yet fascinating thermo-optical applications. One such application of exploited for electric vehicle safety is optical shutter realized using thermotropic liquid crystals. Optical shutters are essential components in various optical systems, in providing control over the transmission of visible light. These shutters are categorized into various types of mechanical shutters, electro-optical shutters, liquid crystal optical shutters (LCOS) etc. liquid crystal cells and polarizing elements to quickly change the transmittance of light, making them ultimate for applications such as imaging and precision illumination. In this work, we explored the experimental techniques, key specifications, features, and applications of an optical shutter developed using liquid crystalline material LCOS.

Research Status of Heat Dissipation Technology for Electric Vehicle Drive Motors

Background:: The application of electric vehicles in daily life is becoming increasingly widespread. However, the heat dissipation issues of the electric motors directly impact electric vehicles' stability and safety. Thus, research on the heat dissipation of the electric motor is conducive to improving the reliability of the drive motor and ensuring the overall stability and safety of electric vehicles; there is a growing emphasis on the development trends of heat dissipation technologies for electric vehicle drive motors. Objective:: In order to meet the increasing requirements of electric vehicles for stability and safety and to solve the problems of low heat dissipation efficiency of electric vehicle drive motors, the size of heat dissipation devices, and the short life span caused by the high temperature of drive motors, the heat dissipation of drive motors is optimized and the heat dissipation structure is improved. Methods:: Based on the structural characteristics of heat dissipation of electric vehicle drive motors, various representative patents related to the current heat dissipation technology of electric vehicle drive motors are summarized. Results:: By summarizing a large number of patents on electric vehicle drive motor heat dissipation technology, it is concluded that the current research on electric vehicle drive motor heat dissipation mainly focuses on liquid heat dissipation or gas heat dissipation and that the main reason for the heat dissipation problem of electric vehicle drive motors is the low heat dissipation efficiency due to over-reliance on a single heat dissipation method, and the reliability is poor due to failure to reasonably control heat dissipation according to the need for heat dissipation. This paper proposes a new idea of heat dissipation for electric vehicle drive motors, which effectively combines liquid heat dissipation and gas heat dissipation. Moreover, the heat dissipation efficiency will be significantly higher than the existing heat dissipation scheme, and the proposed heat dissipation concept of "ondemand distribution" will effectively improve the utilization rate of the heat dissipation medium and reduce the heat dissipation cost and the reasonable heat dissipation structure will reduce the volume of the heat dissipation device. The reasonable heat dissipation structure will also reduce the volume of the heat dissipation device. In addition, the future development of heat dissipation technology for electric vehicle drive motors is also discussed. Conclusion:: The heat dissipation scheme proposed in this paper will effectively improve the heat dissipation problem of electric vehicle drive motors. Compared with the existing heat dissipation methods, the heat dissipation efficiency of the heat dissipation scheme proposed in this paper will be improved by more than 8.5%, and the service life of the drive motor will be extended by more than 5.1%, while the size of the electric vehicle drive motor will be reduced by 6%. More related patents will be invented in the future.

Cooling performance and optimization of a thermal management system based on CO2 heat pump for electric vehicles

Efficient integrated thermal management scheme is crucial for improving the driving range, thermal comfort, and safety of electric vehicles. Compared with the synthetic refrigerant heat pump indirect cooling/heating on the vehicle electrical system, the natural refrigerant CO2 heat pump direct thermal controlling integrated into the thermal management system has advantages in the thermal cycle performance and environmental friendliness. The present study proposed a thermal management system based on CO2 heat hump with multiple working modes for enhancing vehicle energy utilization coefficient. The system thermal performance under the World Light Vehicle Test Cycle was investigated via energy and exergy analyses. The operational control strategies of the thermal management system were optimized for the thermal controls of the cabin, battery and motor. The results show that the minimum exergy destruction of the thermal system occurs at the optimal discharge pressure corresponding to the highest coefficient of performance. Ensuring two-phase latent heat transfer for battery cooling is the most effective measure to maintain battery temperature uniformity via dynamic collaborative regulation of expansion valves’ openings and compressor speed. Compared with constant expansion valve’s opening, the coefficient of performance of the system can be improved by a maximum of 10% with the saturated CO2 vapor at the outlet of battery cooling plate. Due to the low thermal capacitance and minimal thermal inertia of driving motor, its cooling performance is significantly influenced by the heat generation rate and refrigerant flow. Optimal motor cooling efficiency is achieved when controlling the refrigerant quality to 0.85 at the cooling passage outlet. Under the World Light Vehicle Test Cycle, the thermal management system effectively regulated the temperatures across different operating modes while operating at optimal discharge pressures.

Electric Vehicles—An Overview of Current Issues—Part 2—Infrastructure and Road Safety

The electrification of road transport is developing dynamically around the world. Many automotive companies are introducing electric vehicles to the market, and their popularity is constantly growing. The increasing popularity of electric vehicles is caused by individual countries’ governments encouraging people to switch to electric vehicles and their lower operating costs. In 2022, the number of electric vehicles in China will exceed 10 million. Europe and the USA rank second and third in global electric car stock, respectively. The number of available electric vehicle models is constantly growing, remaining approximately 2.5 times smaller than the case of vehicles with an internal combustion engine. Among others, a significant limitation to the popularity of electric cars is users’ fear of range and the density of the charging infrastructure network. This paper presents the objectives regarding public areas and charging stations around the European Union’s comprehensive and core transport network. It is worth noting that the vehicle and charging point’s charging connectors vary depending on the geographical region. Therefore, the currently used charging connectors for different regions are presented. Charging time depends significantly on the charging current, the power of the charging point, and the devices installed in the vehicle. The paper analyzes the limitations of charging power resulting from the onboard charger’s power and the charging point’s power. It presents the charging time of selected electric vehicles. The second aspect that is also the subject of user concerns and discussed in this article is issues related to the safety of electric vehicles. General safety indicators of such vehicles based on Euro-NCAP tests are characterized. Attention was also paid to more detailed problems related to active and passive safety and functional safety analyses. The issue of the fire hazard of electric vehicles was discussed together with modern experiences regarding post-accident procedures in the event of fires.

A novel approach for active cooling of a battery at cell level: Air-cooled mini-channel heat sink, enhanced with intermittent metal foam

Improving the performance and safety of electric vehicles (EVs) requires efficient thermal management of batteries. Although a liquid cooling system with a mini-channel heat sink (MCHS) is an efficient and common approach, it makes the eventual battery pack complex, heavier and expensive. To address this problem, this study proposed the application of air as a coolant for an MCHS by adding intermittent porous zones inside the mini-channel. A numerical study was performed to understand the cooling performance of the mini-channel employed with intermittent porous zones. The results showed that the addition of intermittent porous zones in a mini-channel made the air efficient enough to maintain the battery temperature well below the operating limit at the cell level. However, it was found that the position of porous zones inside the mini-channel significantly impacts the cooling performance. So, a novel approach was proposed for identifying the best locations of porous zones within a mini-channel, and its effectiveness is studied numerically. Results at the cell level showed that the proposed method can give a very close to the optimum solution at the least expense. In this study, the optimum position was found by only 19 simulations among 190 possible choices. The method was applied for cooling a LiPol pouch battery cell. It was shown that filling only 10 % of the min-channel volume with porous blocks can cool the battery as effectively as a fully porous mini-channel. It means a 90 % reduction in pressure drop, fan power consumption and material cost. The maximum observed temperature was 316.7 K for the discharge rate of 3 C.

Mechanical safety prediction of a battery-pack system under low speed frontal impact via machine learning

In response to nonrenewable energy consumption and environmental pollution, the development of electric vehicles has accelerated. The safety of electric vehicles has garnered considerable attention. There are numerous incalculable foreign objects on the road that may collide with or scratch the battery-pack’s frontal, resulting in battery-pack system damage or even explosion. This poses a significant risk to the safety of passengers and drivers. In this paper, a diversity of mechanical safety prediction models for battery-pack systems are proposed. These models support data-driven structural optimization of the battery-pack system by utilizing the numerical results of the bottom shell deformation. These simulation-based prediction models combine response surface method and machine learning algorithms. First, a nonlinear finite element model of the battery-pack system is established. The efficacy of the model is verified using constrained modal analysis in a variety of commercial software packages. Second, the collision simulations are executed and the data in various collision conditions are collected. Different sample sizes are used to develop various response surface models and machine learning models. The machine learning algorithms adopt support vector machine, Gaussian process regression, and neural network models. Third, the prediction accuracy of multiple prediction models is investigated according to error functions. The results show that the neural network model can predict the most accurate deformation under the condition of low speed frontal impact. The prediction average absolute percentage error of the neural network model is only 0.34% within the design domain, and only 2.54% outside the design domain. The proposed prediction model can be used for reliable design of the battery-pack system in electric vehicles. It also can be employed to design the early warning system of the battery-packs.

A real-time early warning method for electric vehicle fast charging safety based on multiple time scales

Abstract This paper puts forward the support technology of fast charging supply and demand matching in charging stations and analyzes the common large-capacity electrochemical energy storage technical parameters in charging stations. For the safety of electric vehicle charging, the thermal reaction and thermal runaway processes of power batteries are introduced. Design the electric vehicle charging state monitoring and safety warning methods, and select the multi-timescale ARIMA algorithm to build the electric vehicle charging safety warning model. The sliding window method is used to process the residual mean and residual standard deviation of electric vehicle charging data to improve prediction data and decrease the chance of misjudging pre- and alarms. Combined with the evaluation standard of the safety early warning model, set reasonable pre- and alarm thresholds using the residual analysis method. The safety warning model designed in this paper is verified by different charging fault warnings. Different charging fault warning examples show that the ARIMA-based charging safety early warning model proposed in this paper can be good for the charging facility’s output voltage, output current, and charging module temperature faults for early warning to ensure that the warning is carried out before the alarm of the actual fault information, to protect the charging safety of electric vehicles.

Model-Based Sensor Fault Detection and Diagnosis in Closed-Loop Power Converters for Electric Vehicles

Electric Vehicle (EV) involves electric motors equipped with closed loop powered conversion systems which use the energy from storage batteries for vehicle propulsion and rely on sensor measurements as feedback to the controller. Therefore, sensor fault detection and diagnosis are an essential process that ensures performance and safety of EVs. From the National Renewable Energy Laboratory (NREL) study it is confirmed that electrical vehicle’s fault percentages vary, however, sensor faults constitute approximately 20-30% of total faults in them. Thus, sensor fault detection is critical for effective EV operation and requires the utmost focus from EV manufacturers and operators. Model-based techniques and Kalman Filter (KF) make it possible to detect faults on sensors in closed-loop EV power converter. It involves the use of mathematical model, sensor data and KF to identify fault before it becomes a threat and guarantees proper function of the vehicle. In this article, a state-space model of a CUK converter is developed, and an LQR closed-loop control system is designed for the power converter. A sensor fault detection method was developed for the system which is then simulated and tested under sensor bias fault conditions for both open and closed-loops control for determining the difference between them. The results showed a distinctive feature extracted between these two systems in the presence of system disturbances and noise applied to the sensor readings. The second section of simulation results in a closed-loop configuration validated the mathematical equations used for sensor fault detection, demonstrating their resistance to false alarms caused by system or component faults in addition to its ability to diagnose faults.

Optimal design of honeycomb battery pack enclosure for electric vehicle

A lithium-ion battery pack enclosure which consists of batteries is the prime source of energy for battery electric vehicles, BEV. While electric vehicle is in running condition, the battery enclosure comes across the worst scenarios like the vibrations coming from the road and impact because of road surface variations. These will cause structural stresses and variations in deformations for the enclosure structure. Electric vehicle safety wholly depends on how safe its battery pack assembly for its mechanical properties, like ability to resist deformation under static loading, vibration, and shock loading. Battery pack enclosure should meet all mechanical properties requirements. In parallel, the battery pack enclosure should be lighter in weight because it will help to improve the vehicle range and increase the battery pack life cycles. In the current study, a design of honeycomb battery pack enclosure is proposed based on mechanical parameters like mass of enclosure, natural frequency, and deformation for generic gravity loading. Baseline battery pack design was validated through physically tested data from literature and further comparative study performed on baseline battery pack enclosure and honeycomb battery pack enclosure for mass, vibrational performance, and static deformation.

Testing the Fire Safety of Electric Vehicles

Aim: The aim of the article is to discuss, using literature on the subject, the results of scientific research and fire tests devoted to lithium-ion batteries and electric-powered vehicles, as well as various methods and techniques for extinguishing them. The presentation of these issues is important in terms of identifying the hazards present in construction objects where electric vehicles are parked and charged, as well as conducting effective and safe rescue operations during incidents involving them. Introduction: The development of electromobility, including the growing number of electric vehicles, poses new challenges for fire protection, both in the context of conducting rescue operations and the safety of parking and charging these vehicles at construction objects. Fires on lithium-ion batteries used in electric vehicles follow a different pattern than fires on conventional energy sources. This includes the causes of their origin, the course and methods of extinguishing them, as well as the dangers to those in their zone, including from the toxic products of combustion that are emitted. Consideration of the occurrence of these risks is particularly important in underground infrastructure, where firefighting is more difficult and the ability to eliminate the toxic products is limited. The article discusses the results of scientific research and fire tests involving lithium-ion batteries and electric vehicles, taking into account different methods and techniques for extinguishing them, conducted in Germany, Austria, Switzerland, Sweden, South Korea, the United States of America and Poland, among others. Methodology: The authors prepared the article based on a review and analysis of the results of scientific and experimental research, as well as on the literature. Conclusions: The growing number of electric vehicles increases the likelihood of accidents and fires involving them. This poses a challenge for rescue operations involving the vehicles mentioned above. An analysis of the literature on the subject leads to the conclusion that the catalogue of risks during rescue operations involving electric vehicles is different from that of conventionally powered vehicles. These risks require research, analysis, evaluation and validation. Keywords: fire safety, fire protection, electric vehicles, lithium-ion battery, rescue operations

(Invited) Safety of Li-Ion Batteries: Current Challenges in a Policy Context

Batteries are a key technology required to meet our objective for climate neutrality, to reduce dependency on fuel imports as well as to ensure maximum use of renewable electricity. Over 80 GW / 160 GWh of stationary batteries and over 50 million electric vehicles are expected in the EU by 2030. Lithium-ion batteries are expected to dominate the market well beyond 2030, while developments in other technologies will continue in parallel. Battery-related policies are currently of high interest and have to evolve quickly in order to facilitate and accommodate technological progress.With increasing numbers of electric vehicles and batteries in operation and the parallel rise of energy density in lithium-ion batteries, risks related to battery safety e.g., through battery fires, increase. The Joint Research Centre (JRC) carries out research on battery safety to support policymaking and develop fit-for-purpose testing methodologies: the recently proposed Batteries Regulation, aiming at a sustainable battery value chain, foresees new safety requirements for stationary batteries. Another example is the Global Technical Regulation on Electric Vehicle Safety, where a thermal propagation test procedure is being developed with international partners.In this context, thermal runaway initiation methods and criteria for thermal runaway events had been analysed. A rapid heating method and suitable criteria for thermal runaway were applied in a thermal propagation test campaign on full electric vehicles and corresponding battery packs. While a high degree of reproducibility was observed, a difference in severity between pack and vehicle-level tests was found, and gas emissions from the tests are currently being analysed. Figure 1

Enhancement of heat transfer efficiency in Li-ion battery packs through response surface optimization of heat pipes

Battery thermal management system (BTMS) ensure optimal performance and safety of Electric vehicle (EV) battery packs. Conventional cooling strategies using heat pipes with air and liquid cooling face challenges in effectively dissipating heat, leading to thermal management issues. This study addresses these limitations by proposing an optimized heat pipe design (helical configured) for enhanced thermal management efficiency. Computational Fluid Dynamics (CFD) simulations evaluate the proposed design for its heat transfer characteristics. The results demonstrated that Air-based cooling systems without heat pipes, in both parallel and staggered arrangements, showed temperature ranges of 30.64∘C to 42.66∘C and 31.14∘C to 41.76∘C, respectively and Liquid cooling systems using water-glycol fluid demonstrated temperature ranges of 30.33∘C to 35.96∘C within the battery pack. This is because the helical configuration provides a larger surface area for heat transfer, allowing for improved heat dissipation. Furthermore, Weight optimization techniques are employed to reduce the overall weight of the battery pack while maintaining structural integrity. The proposed design and optimization strategies contribute to advancing BTMS technology, enhancing battery performance, extending battery life, and ensuring safety. Future research directions include scalability studies for larger battery packs and evaluating the optimized design under various operating conditions. Exploring advanced materials and fabrication techniques can enhance heat transfer capabilities and system efficiency.

Comparative Overview of Methods for the Detection of Airborne Electrolyte Components Released from Lithium‐Ion Batteries

Lithium‐ion battery leakage indicates battery malfunction. In an electric vehicle, the evolving vapors can pose a risk to the health of the passengers. Early detection of a leakage reduces this risk and can prevent further damage. In this review, gas detection techniques such as detector tubes, portable gas chromatography, infrared spectroscopy, gas sensors, and laser spectroscopy are discussed in relation to their capacity of detecting airborne compounds coming from the evaporation of a leaked battery electrolyte. Possible scenarios in which battery leakage can occur are introduced that are partially based on the Global Technical Regulation on Electric Vehicle Safety: parked, driving, charging, postcrash (accident), rescue, and stationary application. The applicability for a potential early warning system using the discussed gas detection techniques is assessed and because no off‐the‐shelf solution could be found overlaps of the capabilities of the techniques with the needs of each scenario are identified and opportunities for further development are pointed out.

Micro-fault identification for lithium-ion batteries in electric vehicles based on similarity measurement of the charging sequence

Battery fault diagnosis is critical to safeguard the safety of electric vehicles. Since lithium-ion battery cells are usually inconsistent and difficult to distinguish from faults, existing micro-fault identification methods are difficult to detect faults as early as possible based on real-world vehicle data. In contrast to the operation process, the voltage and temperature changes are more regular since the current relatively remains constant and the charging strategy is fixed, which is conducive to accurate micro-fault identification. According to the charging strategy of electric vehicles, charging data extraction and selection methods are introduced. Considering the practicality and the difficulty of threshold value determination, the micro-fault identification approach based on DBSCAN is proposed. Normalized IAVs and LIP distances are utilized as features, which come from charging sequences. The results of the thermal runaway vehicle show that the method can effectively find fault cells in voltage signals 18 days before thermal runaway occurs.

Fault Detection for Low Voltage System in Electric Vehicle

With the rapid development of the electric vehicle ecosystem, there are concerns about the electrical safety of electric vehicles. This concern is caused by the problems with electric vehicles, which cannot be used when not used for a long time. This problem is caused by a low voltage rating that is not available when the electric vehicle is in that condition. In this study, an algorithm is proposed to support safety for the availability of low-voltage electrical energy, when electric vehicles are in use or not in use. The results of this research indicate that the created algorithm can provide safety for the availability of low voltage level electrical energy, by adjusting the lead-acid battery charging procedure, monitoring the low voltage level while it not in use, and making existing electric vehicles unable to move as long as problems with the low voltage level charging system cannot be resolved.

FEA Assessment of Contact Pressure and Von Mises Stress in Gasket Material Suitability for PEMFCs in Electric Vehicles

Ensuring the safety of electric vehicles is paramount, and one critical concern is the potential for hazardous hydrogen fuel leaks caused by the degradation of Proton-Exchange Membrane Fuel Cell (PEMFC) gasket materials. This study employs advanced techniques to address this issue. We leverage Finite Element Analysis (FEA) to rigorously assess the suitability of gasket materials for PEMFC applications, focusing on two crucial conditions: ageing and tensile stress. To achieve this, we introduce a comprehensive “dual degradation framework” that considers the effects of contact pressure and von Mises stress. These factors are instrumental in evaluating the performance and durability of Liquid Silicon Rubber (LSR) and Ethylene Propylene Diene Monomer (EPDM) materials. Our findings reveal the Yeoh model as the most accurate and efficient choice for ageing simulations, boasting a minimal Mean Absolute Percentage Error (MAPE) and computational time of just 0.27 s. In contrast, the Ogden model, while accurate, requires more computational resources. In assessing overall model performance using MAE, Root Mean Square Error (RMSE), and R-squared metrics, both LSR and EPDM materials proved promising, with LSR exhibiting superior performance in most areas. Furthermore, our study incorporates uniaxial tensile testing, which yields RMSE and MAE values of 0.30% and 0.40%, respectively. These results provide valuable insights into material behaviour under tensile stress. Our research underscores the pivotal role of FEA in identifying optimal gasket materials for PEMFC applications. Notably, LSR is a superior choice, demonstrating enhanced FEA modelling performance under ageing and tensile conditions. These findings promise to significantly contribute to developing safer and more reliable electric vehicles by advancing gasket material design.

Consumer Buying Behaviour Towards Electric Vehicles in Bengaluru City, Karnataka, India

Electric vehicles are environment friendly powered by electricity, reducing emissions & dependence on fossil fuels. They offer efficient, quiet & smooth driving, contributing to a sustainable transportation. Every day, we come across a wide range of issues and publications that highlight the crucial part that electric vehicles play in changing the face of transportation. In an effort to reduce our dependency on fossil fuels, reduce greenhouse gas emissions, and improve air quality, governments all over the world are moving quickly to implement legislation to stimulate the use of electric vehicles. The dependability & safety of electric vehicles are questioned. In order to analyse how people, perceive the advantages and disadvantages of electric vehicle and the technology they include, this work has been carried out. This paper focuses on consumer buying behaviour towards electric vehicle and the focus of the study is to know the various factors influencing consumer while purchasing elective vehicles.

Comparison of the SOC Estimation Method for Lithium Battery Based on Simulink

SOC (State Of Charge, SOC) represents the state of charge of a battery and is one of the important indicators to measure the energy usage of the battery. In the field of automotive energy, accurate battery SOC estimation is of great significance for improving the range, service life, and safety of electric vehicles. It is an important part of battery management and energy management. The current SOC estimation methods are diverse, and the ampere-hour integration method has the advantages of high accuracy and simple implementation. The EKF (Extended Kalman Filter) algorithm provides solutions for nonlinear problems such as SOC estimation of batteries. Therefore, these two methods are the preferred choice for some vehicle manufacturers and BMS enterprises. This study selects a first-order RC equivalent circuit model for parameter identification, builds a circuit model on Simulink, and compares and verifies the error of the AH integration method and EKF algorithm.

Internal short circuit warning method of parallel lithium-ion module based on loop current detection

Internal short circuit is one of the main triggers for thermal runaway of Li-ion batteries, however, internal short circuit is incidental and cannot be predicted in advance. Therefore, improving the sensing capability of internal short circuit is especially important to improve the safety of electric vehicles. In this paper, we propose an algorithm for detecting internal short circuit of Li-ion battery based on loop current detection, which enables timely sensing of internal short circuit of any battery in a multi-series 2-parallel battery module by detecting the loop current. The method only needs to detect the voltage at both ends of the diagnostic resistor (3 measurement points), which has the advantages of fewer detection points and less additional wiring to the battery module, and can avoid the safety hazards caused by excessive wiring while protecting the battery module. The experimental results show that the method is able to detect internal short circuits in parallel lithium-ion battery packs in a timely manner.

Reducing lithium-ion battery thermal runaway risk based on an integrated cooling strategy for electric vehicles

Nowadays, thermal runaway of lithium-ion battery is widely considered to be a serious hazard to the safety of electric vehicles. In order to effectively prevent thermal runaway, an integrated thermal management solution is proposed. Firstly, a few models of battery, air conditioning system, phase change cooling and liquid cooling are established, respectively. The temperature and heat are used to coupling each model. Then the effectiveness of models is validated by experiment. Finally, the cooling performances of this system are discussed. Under the circumstance of thermal runaway, the battery thermal management system can inhibit thermal runaway, and the battery temperature is reduced from 1208.17 to 304.82 K. In addition, the influences of the convective heat transfer coefficient and flow channel number on the cooling effect are also studied, and in order to ensure that the batteries have an appropriate temperature and reduce energy consumption, their values should be 20 W∙m−2∙K−1 and 5, respectively. When the vehicle is normally driving, the influences of different driving speeds, pump speeds and compressor speeds on the battery temperature are discussed, meanwhile, combined with the cooling effect of air conditioning, a reasonable and economic scheme is determined, that is, the pump speed is 2250 r∙min−1 and the compressor speed is 2500 r∙min−1, and under this scheme, the maximum battery temperature is only 35 °C, and the cab temperature can be reduced to the target temperature within 112 s.