Thermal runaway of lithium-ion batteries constitutes a challenge to the safety of energy storage stations, as the process is accompanied by the ejection and accumulation of large volumes of flammable gases, potentially leading to severe fire or explosion accidents. The pressure relief valve (on the battery pack enclosure) serves as a critical safety structure that regulates the release of these gases into the station space. Its dynamic behavior directly dictates internal pressure evolution of pack and external flammable gas dispersion of station, making it a pivotal yet poorly understood link in the thermal safety chain. Current research lacks a comprehensive depiction of its operational mechanism in real thermal runaway scenarios, specifically, a systematic model to quantify its role in the transfer process from pack pressure and valve mechanics to station-level gas dispersion and combustion risk. To bridge this gap, this study constructs a unified multi-physics coupling model that integrates cell gas generation, pack internal flow, valve mechanical dynamics, and station-level gas dispersion and combustion. It specifically reveals the impact of valve hysteresis on intermittent venting behavior and subsequent flammable gas accumulation. Validated by dedicated valve characteristic and pack thermal runaway tests, the model accurately predicts pressure response and venting dynamics, with a minimal internal pressure error of <0.6 kPa. Further, the explosion process of the energy storage station was predicted based on the model. This study provides design tools for the safety of stations.

Windshield wiper system is essential for driving safety. The random forest algorithm (RFA) is widely utilized for fault identification of windshield wiper system. However, the RFA exhibits significant parameters dispersion, traditional manual adjusting is difficult to achieve the optimal solutions. This study proposes an optimized random forest algorithm (ORFA) to identify vibration and noise patterns in electric vehicle wiper systems, thereby enhancing fault diagnosis accuracy. Firstly, the test bench of windshield is established to obtain the time-domain fault signals; Then, the high-dimensional feature values of the fault signal are extracted. Thirdly, the proposed ORFA are employed to realize the fault property through global domain. Experimental results indicate that the ORFA enhances the accuracy to 96.75%, comparing to the traditional RFA 91.87%. The optimized model provides a reproducible diagnostic framework that enhances early fault identification accuracy and thereby supports subsequent reliability-improvement strategies.

Bushings are widely applied in buildings, bridges, and vehicle chassis to mitigate vibration. Under harsh service conditions, fatigue failure caused by crack initiation and propagation remains a critical challenge limiting their durability. Basalt fiber is widely utilized to reinforce asphalt road, concrete, and friction disc, due to its low cost and high stability. In this paper, the fishbone-inspired basalt fiber-reinforced rubber bushing (F-BFRB) is designed and fabricated to extend the durability of bushings to meet the harsh requirements of heavy load trucks. Besides, the multiscale numerical model is established to optimize the distribution of basalt fiber, which subsequently improves the stress condition of basalt fiber and matrix. Results indicate that the symmetrical 45 degrees fishbone-inspired arrangement can transfer and mitigate stress effectively, reducing the matrix stress by about 38%, while increasing durability by approximately 6.2 times and torsional stiffness by about 6.3 times compared with the traditional arrangement. Finally, the reinforcement mechanism is discussed based on numerical simulations, while the crack propagation path of the F-BFRB is significantly extended. This investigation provides a theoretical foundation for developing the F-BFRB.

Surface fretting corrosion of the bipolar plate (BPP) impacts power density, efficiency, and durability of fuel cell. Traditional research focuses on surface coatings, while the significant degeneration of BPP surface due to road vibration is rarely considered. In this paper, a test bench is designed and fabricated to investigate the electrical contact of BPP interface, the contact vibration, current and interface force are regulated respectively, to obtain their impacts on performance degeneration of BPP. Results indicate the BPP surface temperature increases rapidly under 1 Hz vibration, which is close the fuel cell vibration under road operation, while the surface heat increases slowly under high frequency, high interface pressure and lower surface current density. Furthermore, the variation principle of surface contact resistance is analyzed, based on surface erosion characterization. And the erosion evolution mechanism is characterized and deduced. This investigation can provide a theoretical foundation and scientific evidence for inhibiting dynamic damage of the bipolar plate interface.

Electrical contact is a key function of Bipolar Plate (BPP), transient failure occurs frequently on its interface due to the complex working conditions (random vibration, large current, and nonlinear load). Different from the traditional experimental study, an electrical contact model was established by using numerical simulation. Furthermore, the surface oxide film of BPP is considered at microscale, and the effects of vibration, current density, and normal load on Joule heat were systematically investigated by multiscale modeling approach. Experimental comparison and verification demonstrate that: Under low-frequency conditions (1 Hz), the temperature rise rate of the model with an oxide film is 27.9 % higher than that of the film-free model. A larger load (5 N) can maximize the stability of the contact pair by approximately 67.4 %. The transient high temperature (400 degrees C) caused by a large contact current (5A) will greatly accelerate the electrical contact damage process of the bipolar plate, the oxide generation and dissipation mechanism were analyzed, based on intensified joule heating, surface oxide accumulation as well as experiments. This investigation provides a precise approach to capture the transient failure mechanism of BPP under complex working conditions.

Electric vehicles (EVs) have gained popularity due to its efficiency, low emissions, and reduced noise. However, limited driving range, or range anxiety, remains a challenge, as all EV accessories rely on battery power. This study proposes a digital twin-driven methodology to design energy-efficient wipers, addressing this issue. Five driving modes are proposed, the authors analyzed wiper motor energy consumption through both experimental test and digital modeling, and compared with the traditional wiper drive mode, the results show potential efficiency improvements of up to 33%, demonstrating significant energy-saving opportunities. This study also examines wiper vibration properties and develop contact models to create quieter prototypes. This research guides the design of energy-efficient EV accessories, potentially easing range anxiety and improving overall performance. The approach could be applied to other EV components to further enhance efficiency and driving range.

Advanced nanofibrous materials with excellent performance and functional integration is highly desired for developing emerging wearable electronics. In this work, carbon quantum dots/poly(vinylidene fluoride) (CDs/PVDF) based composite nanofibrous material is proposed and acts as a highly negative material to boost output performance for triboelectric nanogenerators (TENGs). The nanometer-sized and surface-functionalized CDs acting as nucleating inducers facilitate the polarized beta-phase transition of PVDF polymer. The more negative surface charge density of CDs/PVDF nanofibrous membrane is generated through the polarized beta-phase PVDF, thereby leading to a larger electrostatic potential difference to enhance charge transfer. Besides the decreased beaded defects, more uniform morphology fibers are yielded to improve the effective contact surface area. Moreover, the CDs/PVDF composite nanofibers demonstrate the unique multicolor fluorescence effect enabling promising applications in visualized displays and sensing. Finally, the fabricated TENG features a short-circuit current density of similar to 61.8 mA/m(2) and a maximum peak power density of similar to 11.7 W/m(2), exceeding that of most state-of-the-art nanofiber-based TENG reported to date. As a demonstration of application potential, this TENG shows the energy-harvesting ability to charge capacitors and light up 125 green LEDs and self-powered sensing capability for human motion monitoring. This work provides insights for exploiting novel tribomaterials for high-output TENGs with promising potential in biomechanical energy harvesting, self-powered sensing, and so forth.

Plastic cutlery is widely used in dairy industry, with a huge production volume. Defects inevitably arise from factors such as raw material qualities, production processes, and environmental conditions. Traditionally, these defects are inspected manually, leading to high costs, high intensity, low accuracy, and reduced productivity. To address these issues, a high-efficiency defect detection prototype was designed and manufactured to accomplish the automatic sorting task of plastic cutlery. An improved deep learning model, YOLO-spoon, is proposed and integrated into the prototype. To tackle the characteristics of small product defects and packaging glare, Squeeze-and-Excitation attention module is employed to enhance the network's focus on defect features, thereby improving the accuracy of target defect detection. The C3 module of the backbone network is replaced with the attention module to reduce the network's complexity and enhance real-time performance. Experimental results demonstrate that, compared to the original algorithm, the average precision (mAP@0.5) of the proposed algorithm increased by 2.8

An automobile fuel cell stack mounted horizontally will be subjected to a large impact in the direction parallel with the cells. This may cause interfacial slippage between cells, showing a downward bowing phenomenon, which may cause decay in the performance, and even stack leakage. Therefore, ensuring structural and mechanical integrity is very important in stack assembly design, especially for high power stacks with hundreds of unicells. In this paper, the authors presented numeric analysis for a 300 kW stack with 550 unicells, and analyzed the local vibration from the stack global modes based on finite element analysis (FEA), further evaluated the vibration responses, such as deformed shape and directions, then modified the stack structurally by applying the reinforcement bars, and finally confirmed the robustness of the reinforced stack. It is demonstrated that with proper design, a single stack with hundreds of unicells can be produced for vehicle applications.

Proton exchange membrane fuel cell (PEMFC) as an efficient energy device, has great application prospects. However, due to the assembly design, the efficiency and reliability of PEMFC are easily affected, especially the uneven distribution of bipolar plate contact pressure. Therefore, a simple and reliable assembly methodology based on the wave spring is proposed to achieve the purpose of uniform load and obtain high-performance PEMFC in this paper. The effectiveness of wave spring suspension approach is verified by experiments. This achievement represents an important step in improving the performance of PEMFC.

The vibration from the road inevitably causes the microscopic dynamic contact of the contact interface inside the proton exchange membrane fuel cell (PEMFC), and the dynamic characteristics of the contact interface have an obvious influence on the dynamic behavior of the whole stack. In this paper, the normal and tangential contact between bipolar plate (BP) and membrane electrode assembly (MEA) is investigated by fractal theory, and the variation of contact stiffness with fractal dimension, characteristic length and loading force is studied comprehensively. Then, through the virtual material method, a dynamic model of the fuel cell stack reflecting the contact characteristics is established. It is found that the natural frequencies of the stacks considering the contact stiffness are lower than those not considering it. The larger the contact stiffness corresponding to the fractal dimension and characteristic length, the higher the natural frequency of the stack, and the effect of fractal parameters on the surface roughness is explored. Increasing the total clamping force can increase the stack global modal frequency, but it will decrease the cell local modal frequency.

The contact pressure between bipolar plates in proton exchange membrane fuel cells (PEMFCs) is nonlinearly distributed, because of the bolt assembly. This nonlinearity in the contact pressure distribution can be amplified under vibration, and the convex point on the rough surface of a membrane electrode assembly (MEA) is equivalent to a Hertz contact. Under the friction effect, a transient current is generated and the bipolar plate corrodes suddenly, resulting in hydrogen and oxygen leakage. This study proposes a woodpecker inspired assembly PEMFC based on a hyoid-shaped wave spring (WIA-PEMFC), to achieve uniform contact pressure on the bipolar plates under both static and dynamic conditions. Then, the effectiveness of WIA-PEMFC was verified via finite element simulations and experiments. Compared with that of conventional assembly methods, the nonuniformity of the contact pressure can be reduced by up to 60%. Additionally, the electrical performance of WIA-PEMFC was also tested, and the results revealed a significant improvement in the electrical performance. Moreover, WIA-PEMFCs boast high reliability, low cost, and zero emissions due to the lack of energy supply equipment, which can facilitate the engineering development of PEMFC stacks with high reliability and high efficiency.

Flow sensing exhibits significant potential for monitoring, controlling, and optimizing processes in industries, resource management, and environmental protection. However, achieving wireless real-time and omnidirectional sensing of gas/liquid flow on a simple, self-contained device without external power support has remained a formidable challenge. In this study, a compact-sized, fully self-powered wireless sensing flowmeter (CSWF) is introduced with a small size diameter of down to less than 50 mm, which can transmit real-time and omnidirectional wireless signals, as driven by a rotating triboelectric nanogenerator (R-TENG). The R-TENG triggers the breakdown discharge of a gas discharge tube (GDT), which enables flow rate wireless sensing through emitted electromagnetic waves. Importantly, the performance of the CSWF is not affected by the R-TENG's varied output, while the transmission distance is greater than 10 m. Real-time wireless remote monitoring of wind speed and water flow rate is successfully demonstrated. This research introduces an approach to achieve a wireless, self-powered environmental monitoring system with a diverse range of potential applications, including prolonged meteorological observations, marine environment monitoring, early warning systems for natural disasters, and remote ecosystem monitoring. A compact-sized fully self-powered wireless sensing flowmeter (CSWF) with a small size diameter of 50 mm is demonstrated, which can transmit real-time and omnidirectional wireless signals. The CSWF achieves a relatively long effective transmission distance of more than 10 m and the strong correlation coefficients between wind speed, water flow rate, and discharge frequency are 0.9996 and 0.9995, respectively. image

The traditional damping structure usually transfers the vibration energy into heat, dissipated and without harvesting. But for harsh environments, such as military activities and lunar probe patrols, the vibration energy can be extracted, and realize the purpose of self-power condition monitoring. In this paper, a bionic suspension with energy-harvesting property is proposed based on bionic configurations. The bionic suspension adopts a symmetrical three-link arrangement to simulate the arrangement of bones, and a horizontal spring to simulate muscles. The micro-generator embedded in the knee joint provides the main damping force for the overall structure and also plays a role in harvesting energy. The dynamic equation and virtual prototype model are established, and the effects of parameter changes on the performance of vibration reduction and energy harvesting are analyzed, and the relationship between the two is revealed. The results show that the parameters to achieve their respective optimal performance are not consistent in the trend, though it is difficult to obtain the best performance of both, it can be designed according to the specific functions to be satisfied. This structure can be utilized as a general model for vibration reduction and energy harvesting scenarios, providing new ideas for self-powered sensing and condition monitoring configurations.

The solenoid pulse valve (SPV) is a key component of dust collector. The frequent switch of SPV accelerates its damage, subsequently decrease operation efficiency of dust collector. The traditional manual inspection methods lack reliability and efficiency, while vibration-based condition monitoring is costly and sophisticated in acceleration sensor distribution and signal processing. This paper proposes a fault diagnosis approach based on SPV noise. The average coherence coefficient of SPV noise and vibration signals is above 0.8 and close to 1, which demonstrates that there is a close relationship between SPV noise and its structural vibration. Furthermore, the validation experiments indicate that the SPV fault can be clearly distinguished by its noise signal, confirms the effectiveness of proposed approach. By utilizing this noise monitoring method, the number of sensors can be reduced by about 95 %, the work intensity of the staff is greatly reduced, and production efficiency and safety are guaranteed.

To meet the requirements of power grid operation control, constructing an extensive sensor network in the power grid is a future development trend. However, due to the high cost, the difficulty of continuous power supply for a long time, the large amount of energy consumption, and the environmental problems caused by abandoned batteries, the traditional power supply mode based on batteries for sensors is inconsistent with China's goal of carbon peak and carbon neutrality. It cannot meet the needs of the future grid. Therefore, it is significant to solve the energy supply problem of numerous sensors to promote the construction of new power grid and improve the utilization rate of renewable energy. As an emerging energy harvesting device, triboelectric nanogenerators (TENG) are suitable for developing self‐powered sensors and powering low‐power sensors due to their mall size, high efficiency, low cost, and environmental friendliness. At the same time, due to the abundant, stable, and widely distributed magnetic field around the equipment in the grid, it can provide continuous excitation for the TENG. Therefore, applying magnetic field energy‐harvesting TENG in the future power grid has a broad development prospect. This paper analyzes the development trend and the crucial problems facing the power grid in the future. We review the research and application of TENG based on the magnetic field in recent years and explain the mechanism of TENG in detail. Finally, the application prospect of TENG in the future power grid has been prospected. This paper can provide a reference for applying magnetic field energy harvesting triboelectric nanogenerators in future power grids. image

Currently, the performance improvement of triboelectric nanogenerators (TENGs) mainly depends on materials, structures, and energy management circuits. In this article, we propose a power bonding diagram model that is similar to the vertical contact-separation TENG. This model can handle systems with multiple forms of energy in a unified way, and intuitively reveal the interaction and energy conversion relationships among the components of the TENG system during operation. Various factors that affect the TENG output performance can be quantitatively described using parameters in the power bonding diagram model of the TENG. Through parameter simulation analysis, it can be found that different changes in parameters during a contact-separation motion of the TENG will have different impacts on its output performance. Among them, the contact charge amount q9 determines the theoretical maximum output electric energy Emax of the TENG. In practical applications, increasing the value of the nonlinear energy R6 during the contact process of the TENG as much as possible will make the actual output electric energy of the TENG approach Emax. The parameter analysis of the power bonding diagram model of the TENG can inspire researchers to improve the output electric energy from both theoretical and practical aspects.

Clamping load impacts the contact area, resistance, sealing and heat generation of fuel cell stacks, the uneven distribution of clamping load decreases the durability of PEMFC stacks, therefore it is essential to quantitative modeling the pressure distribution and improve the imbalance distribution issue. In this paper, a quantitative model is proposed to characterize the pressure distribution on bipolar plates. A theoretical model is established based on both finite element modeling (FEM) and measurement, and the flexible pressure sensors are applied in the established test systems. Furthermore, a nacre-inspired optimization approach is applied to improve the uneven pressure distributions based on the quantitative model. Results indicate that the optimized design can significantly improve the uneven clamping load, and it provides an effective approach for the design of durable PEMFC stacks.

Triboelectric nanogenerators (TENGs) can convert random mechanical vibrations around the environment into electricity and have huge potential in artificial intelligence, blue energy, carbon neutrality, human–machine interface, e-skin, etc. Although many efforts have been made on the working mechanism and performance enhancement in the past decade, characterizing and evaluating the performance of TENGs remains challenging due to the lack of benchmarking guidelines. Previous works based on different measurement methods and metrics as well as the lack of details result in difficulties in performance comparison. In this review, we discuss fundamental works on electrical measurement and performance evaluation of TENGs. Issues in measurement are elucidated and corresponding solutions are presented. Then, the origin and development of the figure-of-merits (FOMs) of TENGs are reviewed. The standardization not only broadens our understanding but also facilitates the commercialization and industrialization of TENGs. We believe that the correct measurement and fair evaluation can promote the performance assessment of TENGs and the continuous development of this field.