Search Results (4,520)

Nowadays, attempts to commercially apply non-pneumatic tires (NPTs) in a wide range of vehicles can be observed. These types of wheels use a specific structure and material selection to mimic the function of compressed air in pneumatic tires (PTs). This paper reviews the mechanical properties and vehicle applications of non-pneumatic tires. This review will provide information about the influence of the shape of the radial, longitudinal, and lateral characteristics, as well as the possibility of selecting contact pressure values at the wheel design stage and the influence of the type of elastic structure on the concentration of pressures in the contact length. The radial characteristics of non-pneumatic tires depend on the type of elastic structure. The spoked elastic structure will be characterized by greater displacements compared to the cellular structure, which will reduce radial stiffness. The radial stiffness of non-pneumatic tires is increased by increasing the number of elastic structure elements and their thickness and decreasing their length. The longitudinal stiffness of non-pneumatic tires increases with the number of elements forming the elastic structure and with the elastic structure’s lack of susceptibility to circumferential deformation. Spoked non-pneumatic tires will have lower longitudinal stiffness compared to cellular non-pneumatic tires. The elastic structure is characterized by a low susceptibility to lateral deformation, which contributes to the high lateral stiffness of the non-pneumatic tire. Non-pneumatic tires have a limited ability to shape the contact patch parameters, which mainly depend on the vertical load and the shape of the tread area. The type of band used will influence the formation of contact pressures. An isotropic elastomer used in a shear band will cause pressure concentration at the ends of the contact length. A more uniform pressure distribution is achieved by using a laminated elastomer. Full article

During the service life of steel bridges, the structural stress histories display combined cyclic characteristics due to the superposition of low-frequency thermal loading and high-frequency vehicle loading. To investigate the fatigue performance under such loading patterns, a series of constant-amplitude and high-low frequency superimposed loading fatigue (HLSF) tests were conducted on notched specimens fabricated from Q355D bridge steel. The influence of HLSF waveform parameters on fatigue life was systematically investigated. Based on the fracture evolution mechanism, a concept of low-frequency periodic damage acceleration factor was proposed to effectively model the block nonlinear damage effects, and the applicability of existing fatigue life prediction models was discussed. The results show that the effect of average stress on the fatigue life under HLSF can be effectively considered by Walker’s formula. Low-amplitude ratios and low-frequency ratios indicate unfavorable loading conditions that may accelerate the Q355D fatigue damage accumulation, and these conditions are not adequately accounted for in current life prediction models. Compared to constant amplitude loading, HLSF can lead to a 66% and 46% reduction in high-frequency life when the amplitude ratio reaches 0.12 and the frequency ratio reaches 100. Compared to Miner’s rule, the proposed damage correction method reduces the life prediction error for HLSF by 11%. These findings provide valuable references for the fatigue assessment of bridge steel structures under the coupled effects of temperature and vehicle loading. Full article

The increasing integration of renewable energy sources and the widespread adoption of electric vehicles have introduced considerable uncertainty into the operation of large-scale power systems. Traditional deterministic unit commitment models are insufficient for managing such variability in a reliable and cost-effective manner. This study proposes a two-stage stochastic unit commitment model that captures uncertainties in solar photovoltaic generation, electric vehicle charging demand, and load fluctuations using a mixed-integer linear programming framework with recourse. The model is applied to Thailand’s national power system, comprising 171 generators across five regions, to assess its scalability for sustainable large-scale planning. Results indicate that the stochastic model significantly enhances system reliability across most demand profiles. Under the Winter Weekday group, the number of lacking scenarios decreases by 76.92 percent and the number of missing periods decreases by 78.57 percent, while the average and maximum lack percentages are reduced by 56.32 percent and 72.61 percent, respectively. Improvements are even greater under the Rainy Weekday group, where lacking scenarios and periods decline by more than 92 percent and the maximum lack percentage falls by over 98 percent, demonstrating the model’s robustness under volatile solar output and load conditions. Although minor anomalies are observed, such as slight increases in average and maximum lack percentages in the Summer Weekday group, these are minimal and likely attributable to randomness in scenario generation or boundary effects in optimization. Overall, the stochastic model provides substantial advantages in managing uncertainty, achieving notable improvements in reliability with only modest increases in operational cost and computational time. The findings confirm that the proposed approach offers a robust and practical framework for supporting sustainable and resilient power systems in regions with high variability in both generation and demand. Full article

The stroke control of a hydrostatic transmission (HST) is crucial for improving the energy efficiency and power variability of heavy-duty vehicles, including agricultural, construction, mining, and forestry equipment. This study introduces a new control strategy: an Artificial Neural Network (ANN) controller that imitates a Multiple Model Predictive Controller (MPC). The goal is to compare their performance in controlling the HST’s stroke. The proposed controller is designed to track complex stroke reference trajectories for both primary and secondary regulations under realistic disturbances, such as engine and load torques, which are influenced by soil and road conditions for an HST system in line with a nonlinear and time-varying mathematical model. Processor-in-the-Loop simulations suggest that the ANN controller holds several advantages over the Multiple MPC and classical control strategies. These benefits include its suitability for multi-input–multi-output systems, its insensitivity to external stochastic disturbances (like white noise), and its robustness against modeling errors and uncertainties, making it a promising option for real-time HST implementation and better than the Multiple MPC scheme in terms of simplicity and computational cost-effectiveness. Full article

Power batteries are one of the important components of electric vehicles, but the manufacturing process of vehicle power batteries is complex and diverse. Traditional scheduling methods face challenges such as low production efficiency and inadequate quality control in complex production environments. To address these issues, a multi-objective optimization model with makespan, total machine load, and processing quality as the established objectives, and a Multi-objective Particle Swarm Energy Valley Optimization (MPSEVO) is proposed to solve the problem. MPSEVO integrates the advantages of Multi-objective Particle Swarm Optimization (MOPSO) and Energy Valley Optimization (EVO). In this algorithm, the particle stability level is combined in MOPSO, and different update strategies are used for particles of different stability to enhance both the convergence and diversity of the solutions. Furthermore, a local search strategy is designed to further enhance the algorithm to avoid the local optimal solutions. The Hypervolume ($HV$) and Inverted Generational Distance ($IGD$) indicators are often used to evaluate the convergence and diversity of multi-objective algorithms. The experimental results show that MPSEVO’s $HV$ and $IGD$ indicators are better than other algorithms in 10 computational experiments, which verifies the effectiveness of the proposed strategy and algorithm. The proposed method is also applied to solve the actual battery workshop scheduling problem. Compared with MOPSO, MPSEVO reduces the total machine load by 7 units and the defect rate by 0.05%. In addition, the effectiveness of each part of the improved algorithm was analyzed by ablation experiments. This paper provides some ideas for improving the solution performance of MOPSO, and also provides a theoretical reference for enhancing the production efficiency of the vehicle power battery manufacturing workshop. Full article

With the ongoing electrification of vehicles and the resulting demand for higher power densities, drivetrain requirements are becoming increasingly stringent. Shaft-hub connections are particularly affected in terms of both quantity and design, making innovative solutions necessary. A key factor in meeting these requirements is knowledge of the stress state within the contact area. One promising approach is the application of a thin-film-based sensor system directly onto the shaft surface. This enables, for the first time, the direct measurement of contact pressure in the interface, allowing for more precise connection design. To fully exploit the potential of this sensor technology, its influence on the joining process of shaft-hub connections must be investigated. In this study, cylindrical interference-fits were coated with two thin-film systems relevant to the application, followed by joining tests. The resulting damage was analyzed to derive general recommendations for the joining of coated shaft-hub connections. The results show that shrink-fitting enables damage-free joining, provided specific parameters are met, as confirmed by experimental testing and microscopic examination. This not only preserves the integrity of the sensor system but also establishes the prerequisite for potential in situ measurements, thereby laying the foundation for the feasibility of direct load monitoring during operation. Full article

Ro-Ro (Roll-on/Roll-off) vessels require adaptable deck systems to efficiently accommodate vehicles of varying sizes. Conventional fixed or hydraulically lifted car decks often face challenges related to structural efficiency, maintainability, and limited flexibility. To address these issues, this study proposes a novel hoistable car deck system that incorporates a hinge-based folding mechanism and modular connections. The design enhances maintainability, allows independent adjustment of deck panels without external lifting equipment, and improves adaptability to diverse ship layouts. In addition, the proposed concept was systematically evaluated to verify its structural integrity and serviceability under representative loading conditions, highlighting its compliance with classification society requirements. These results suggest that the hinge-based modular deck provides a promising solution for next-generation Ro-Ro vessels, offering both operational flexibility and improved efficiency while paving the way for practical applications in shipbuilding and retrofitting projects. Full article

Tire deformation monitoring is a critical requirement for improving vehicle safety, performance, and intelligent transportation systems. However, most existing flexible strain sensors either lack directional sensitivity or have not been validated in real-world driving environments, limiting their practical application in smart tires. In this work, we report the fabrication of a flexible piezoresistive strain sensor based on a porous laser-induced graphene (LIG) network embedded in an Ecoflex elastomer matrix, with integrated directional force recognition. The LIG–Ecoflex sensor exhibits a high gauge factor of 9.7, fast response and recovery times, and stable performance over 10,000 cycles. More importantly, the anisotropic structure of the LIG enables accurate multi-directional stress recognition when combined with a convolutional neural network (CNN), achieving an overall classification accuracy exceeding 98%. To further validate real-world applicability, the sensor was mounted inside passenger car tires and tested under different loads and speeds. The results demonstrate reliable monitoring of tire deformation with clear correlations to load and velocity, confirming robustness under dynamic driving conditions. This study provides a new pathway for the integration of direction-aware, high-performance strain sensors into intelligent tire systems, with broader potential for wearable electronics, vehicle health monitoring, and next-generation Internet of Vehicles applications. Full article

Axial flux motors, characterized by compact axial dimensions and high torque density, are well-suited for space-constrained applications such as in-wheel drives and flying vehicles. However, conventional axial flux permanent magnet synchronous motors (AFPMSMs) face challenges such as high-temperature demagnetization, reduced efficiency at high speeds, and elevated manufacturing costs. Electrically excited synchronous motors (EESMs) offer a promising alternative, providing high-temperature reliability and superior high-speed capability while maintaining high torque density. In this paper, a novel composite-cooled axial flux electrically excited synchronous motor (AFEESM) is proposed. From an electromagnetic design perspective, the effects of key parameters such as shaft-to-outer-diameter ratio, inner-to-outer-diameter ratio, slot depth, and yoke thickness on output performance are systematically investigated, and a dedicated design procedure is established. Through multi-objective optimization, the motor’s torque output is increased by 19.6%. Comparative simulations are conducted to evaluate differences in torque density, efficiency, and cost between the proposed AFEESM, a conventional radial flux EESM, and an AFPMSM. To address the cooling requirements of double-sided windings on both the stator and rotor, a dual-channel composite cooling structure is developed, integrating internal–external double-loop water cooling for the stator and axial through-hole air cooling for the rotor, reducing the peak temperature by over 36%. Finally, a prototype is manufactured, and no-load characteristics and load efficiency validate the effectiveness of the electromagnetic design and the structural reliability of the motor. Full article

To mitigate the risks posed by uncertainties in renewable energy output and Electric Vehicle (EV) travel patterns on the scheduling of Virtual Power Plants (VPPs), this paper proposes an optimal scheduling model for a VPP incorporating EVs based on Information Gap Decision Theory (IGDT). First, a Monte Carlo load forecasting model is established based on the behavioral characteristics of EV users, and a Sigmoid function is introduced to quantify the dynamic relationship between user response willingness and VPP incentive prices. Second, within the VPP framework, an economic optimal scheduling model considering multi-source collaboration is developed by integrating wind power, photovoltaics, gas turbines, energy storage systems, and EV clusters with Vehicle-to-Grid (V2G) capabilities. Subsequently, to address the uncertain parameters within the model, IGDT is employed to construct a bi-level decision-making mechanism that encompasses both risk-averse and opportunity-seeking strategies. Finally, a case study on a VPP is conducted to verify the correctness and effectiveness of the proposed model and algorithm. The results demonstrate that the proposed method can effectively achieve a 7.94% reduction in the VPP’s comprehensive dispatch cost under typical scenarios, exhibiting superiority in terms of both economy and stability. Full article

For electric vehicles widely used recently, lithium-ion batteries serve as the primary energy storage units, affecting the vehicles’ performance, safety, and lifespan. Accurate state of charge (SOC) estimation is pivotal for the battery management system (BMS) to enhance the predictability of the vehicle’s range and avert thermal runaway due to improper charging methods. In this study, an adaptive SOC estimation methodology was developed using parameter identification with forgetting factor recursive least squares (FFRLS). These parameters are then incorporated into a dual adaptive extended Kalman filter (DAEKF) for SOC estimation under varying load conditions. DAEKF is used to dynamically adjust the covariance matrices for process and measurement noises, significantly enhancing the filter’s adaptability and precision. The integration of FFRLS and DAEKF enables a robust SOC estimation of electric vehicles, featuring rapid computation speeds, high accuracy, and excellent adaptability, positioning them as ideal candidates for enhancements in battery management system technology. Full article

Recycled asphalt pavement (RAP) can support traffic loads comparable to those of roads constructed with conventional materials. The structural evaluation of RAP is performed through the deflection generated by vehicles via recoverable deflection in the pavement layers. The deflection record is translated into a curve that geometrically interprets the behavior of the layers that make up the pavement. In this study, a falling weight deflectometer (FWD) was used to emulate transit loads and measure deflection in two models. Both contained 30% RAP, and one of them had fiberglass geogrid in the center of the asphalt layer. Through normalized maximum deflection (limit value based on constant stress), the structural index (SI), and the dynamic stiffness modulus (DSM), the structural behavior of the models under different load levels was evaluated. The pavement structure exhibited similarities in strength for both models subjected to impact. The presence of the geogrid reinforcement (Z1) showed structural index values ranging between 0.17 and 0.54, while the layer without geogrid (Z2) presented structural index values in a range of 0.23 to 0.78. In addition, the dynamic stiffness modulus presented a difference of 10 kN/mm between the maximums of the models in favor of reinforcement with glass fiber geogrid. Therefore, low structural index values are associated with the interaction between RAP and geogrid, highlighting this combination as an innovative and functional system for road surfaces, while the dynamic stiffness modulus indicates the stability and structural integrity of sustainable pavement, which has the potential to extend its lifespan. Full article

The problem of quantifying prestress loss in the external tendons of in-service bridges is of immense practical importance, and the development of reliable, cost-effective methods is a commendable goal. Based on the principle of static equilibrium, this paper proposes a direct method for determining the effective stress in external prestressed tendons using the variation principle, whose calculation accuracy was validated by conducting experimental and theoretical analysis considering the prestressed tendon arrangement form. A transverse tensioning experiment of the prestressed tendons was carried out under four tension conditions of 50 kN, 80 kN, 110 kN and 170 kN at the anchorage end, and the theoretically calculated internal force of the prestressed tendons gradually approached the measured value as the transverse tension increased. Once the appropriate level of transverse tension was reached, stable and reliable results could be obtained. Ultimately, the error between them will stabilize below 5%. This method was used to detect stress loss in the external prestressed tendons of 20 m, 40 m and 50 m T-beams affected by both internal and external uncertain factors simultaneously, and the probability distribution hypothesis test of the stress loss rate was carried out, the results of which reveal that they all follow normal distribution. The ratio of stress at the bottom edge of the T-beam under self-weight and prestressed load to that under vehicle load is defined as the compressive stress reserve coefficient, which is a verified and reliable index for evaluating the external prestressed stress loss on the reinforcement effect of the bridge. Full article

Noise barriers are commonly used to reduce the adverse effects of traffic noise in both urban and suburban settings. While conventional systems constructed from concrete and steel provide reliable acoustic and structural performance, they raise sustainability concerns due to high embodied energy and carbon emissions. Glued-laminated (glulam) timber has emerged as a sustainable alternative, offering a reduced carbon footprint, aesthetic appeal, and effective acoustic performance. However, the crashworthiness of timber-based noise wall systems remains under investigated, particularly with respect to the safety criteria established in the 2016 edition of the American Association of State Highway and Transportation Officials (AASHTO) Manual for Assessing Safety Hardware (MASH). This study presents the full-scale crash testing and evaluation of glulam rubrail and noise wall systems under MASH Test Level 3 (TL-3) impact conditions. Building on a previously tested system compliant with National Cooperative Highway Research Program (NCHRP) Report 350, modifications were made to increase rubrail dimensions to meet higher lateral design loads. Three full-scale vehicle crash tests were conducted using 1100C and 2270P vehicles at 100 km/h and 25 degrees, covering both front- and back-mounted wall configurations. All tested systems demonstrated acceptable structural performance, effective vehicle redirection, and compliance with MASH 2016 occupant risk criteria. There was no penetration or potential for debris intrusion into the occupant compartment, and all measured occupant risk values remained well below allowable thresholds. Minimal damage to structural components was observed. The results confirm that the modified glulam noise wall system meets current impact safety standards and is suitable for use along high-speed roadways. This work supports the integration of sustainable materials into roadside safety infrastructure without compromising crash performance. Full article

In this work, bemotrizinol (BMTZ), a broad-spectrum UV-filter, was loaded into nanostructured lipid carriers (NLC) whose lipid matrix contained different oils (isopropyl myristate, decyl oleate, caprylic/capric triglyceride) to assess the effects of the lipid core composition on the properties of the resulting NLC. Subsequently, the effects of incorporating different concentrations of optimized BMTZ-loaded NLC on the technological properties of O/W emulsions (pH, viscosity, spreadability, occlusion factor, in vitro BMTZ release, skin permeation, and in vitro sun protection factor) were assessed. The optimized BMTZ-loaded NLC contained 3.0% w/w of isopropyl myristate and showed mean size = 190.6 ± 9.8 nm, polydispersity index = 0.153 ± 0.013, ζ-potential = −10.6 ± 1.7 mV, and loading capacity = 8% w/w. The incorporation of increasing concentrations (5, 10, 20% w/w) of optimized BMTZ loaded into emulsions provided a slight increase in spreadability, lower viscosity, and no change in pH, occlusion factor, and BMTZ release compared to emulsions containing free BMTZ. No BMTZ skin permeation was observed from all formulations. About a 20% increase in sun protection factor values was obtained for vehicles containing BMTZ-loaded NLC compared with formulations incorporating the same amount of free BMTZ. Therefore, incorporating BMTZ-loaded NLC into emulsions could be a promising strategy to develop safer and more effective sunscreen formulations. Full article