Vehicle Dynamic Load Research Articles

Stress intensity factor analysis for multiple cracks in orthotropic steel decks rib-to-floorbeam weld details under vehicles loading

In recent years, it has been found that multiple cracks coexist in the existing steel bridge orthotropic steel decks (OSDs) longitudinal rib-to-floorbeam (RF) details. The synergistic expansion mechanism of multiple cracks in the orthotropic steel bridge deck panel is still unclear. This paper proposes a multiscale extension finite element method based on ABAQUS and FRANC 3D interactive technology to simulate the fatigue crack propagation behavior of steel bridge RF details under dynamic vehicle loading. The effectiveness of this method is verified by comparing experimental data. The crack propagation behavior of longitudinal rib weld toes, transverse diaphragm weld toes, and transverse diaphragm arc notches is studied, and the influence of fatigue crack length and angle on the initial crack stress intensity factor (SIF) of adjacent details is discussed.

Optimization on the peroxide ratio control strategy of PEMFC system based on immune algorithm

The air supply system is an essential component of a proton exchange membrane fuel cell (PEMFC), and proper control of the oxygen stoichiometry ratio(λo2) is crucial to prevent oxygen starvation in the PEMFC while maintaining efficient and stable performance output. In response to the issues of poor dynamic performance and slow response in traditional λo2 control strategies, this study was conducted to establish a dynamic oxygen flow model of the PEMFC and proposed a λo2 control strategy based on an immune algorithm-fuzzy PID (IAFPID). The performance of the IAFPID control strategy in λo2 control was analyzed under different load requirements, simulated vehicle dynamic loads, and temperature disturbances. The results demonstrate that the IAFPID control strategy has advantages such as fast convergence speed, strong robustness, and good dynamic performance. The efficiency of achieving the optimal stoichiometry ratio for high power output in PEMFC under disturbances was nearly 50% higher with IAFPID control compared to traditional PID, Fuzzy-PID, Genetic Algorithm PID, and Immune Algorithm PID strategies. Furthermore, this method ensures a lower average error in maintaining stable λo2 under dynamic disturbances compared to the IAPID and PID control strategies, with reductions of 12.93% and 37.75%, respectively.

Bond performance of freeze-thaw damaged concrete and reinforcing bars subjected to high-cycle fatigue loading

Concrete bridges are susceptible to the detrimental effects of freeze-thaw cycles (FTCs) and dynamic vehicle loading in cold regions, compromising the bond between reinforcing bars and concrete. After high-cycle fatigue loading using eccentric pull-out tests, an experiment on the bond performance of freeze-thaw damage specimens was carried out. The investigation focused on the impact of FTCs, fatigue load cycles (FLCs), and concrete strengths on the bond behaviour. The test results showed that eccentric pull-out specimens of reinforced concrete with freeze-thaw damage under high-cycle fatigue loading were more susceptible to experiencing splitting failure. As the number of FTCs increased, the peak and the residual bond strength decreased continuously. Fatigue loading had a slight improvement effect on the peak bond strength, but it significantly reduced the residual bond strength when the specimens suffered from higher fatigue damage. The peak slip initially increased and subsequently decreased with FTCs, showing minimal sensitivity to the number of FLCs. Considering the stiffness degradation of the ascending section, a bond-slip model for freeze-thaw damaged concrete and reinforcing bars under high-cycle fatigue loading was established, and verified through experimental results.

A deep learning method for heavy vehicle load identification using structural dynamic response

The identification of dynamic vehicle loads is crucial for bridge health monitoring. Currently, bridge weigh-in-motion (BWIM) system and image recognition methods are extensively used for vehicle load identification. However, BWIM systems are costly, while single image recognition methods struggle to accurately identify vehicle weight. Hence, an improved approach is proposed to address the above issues, which employs a Bidirectional Long Short-Term Memory (BiLSTM) network model to establish the mapping relationship between vertical deflection of bridges and vehicle loads. Firstly, based on practical engineering, the Grey Wolf Optimization-Variational Mode Decomposition (GWO-VMD) method is employed to address the influence of temperature effects on deflection response data. Then, through a time matching algorithm, the sliced deflection data and the corresponding BWIM system vehicle load information are paired to form the dataset for the deep learning models. The results of the models demonstrate that the optimal BiLSTM model exhibits better robustness and generalization performance. It achieves high accuracy of 97.9% in load identification. The method significantly reduces the economic cost and improves the accuracy of vehicle load identification.

The self-tuning fuzzy sliding mode control method for the suspension system with the LSTM network road identification

As an important component of semi-active suspension (SAS) systems, the built-in solenoid valve adjustable damper (BSVAD) is now widely used in the field because of its advantages of fast response, continuously adjustable damping, and lightweight design. However, only a few studies have discussed the BSVAD-modeling method. Hence, this study proposes a method for constructing an agent model using a feedforward neural network (FNN) for an equivalent BSVAD regulation mechanism. Meanwhile, a new control strategy, i.e., a fuzzy sliding mode control method based on road conditions (RC-FSMC), is proposed for calculating the required damping force. The proposed method identifies and analyzes unsprung mass acceleration characteristics using a long short-term memory network to obtain the road condition of the moving vehicle and inputs the output results into the designed fuzzy rules to adjust the sliding mode switching gain and finally realize road condition-based adaptive control. Finally, through simulation test analysis, the results show that the designed RC-FSMC strategy can effectively reduce vehicle body acceleration and vehicle dynamic load under different road conditions to improve the adaptability of the vehicle to different roads.

A Design Method on Durable Asphalt Pavement of Flexible Base on Anti-Rutting Performance and Its Application.

To solve the durability of flexible base asphalt pavement, especially its anti-rutting problem, a design method on durable asphalt pavement of flexible base on anti-rutting performance was put forward in the paper, based on many experiments and calculations. Firstly, a method that asphalt could be selected according to penetration and the anti-rutting factor of its base asphalt was found, which solved the problem of the asphalt selection of the flexible base asphalt mixture design. Meanwhile, a method of skeleton-density structure gradation design was proposed based on the fractal void ratio of coarse aggregate, fractal volume of fine aggregate in coarse aggregate, penetration, fractal dimension of gradation particle size, and rutting tests, which effectively solved in advance the rutting and fatigue performance of flexible base asphalt mixtures. Then, on the basis of the fatigue damage, a calculation method of fatigue life was suggested, which solved the problem that the fatigue damage of asphalt mixtures rarely considered the combined effects of creep damage and fatigue damage. In addition, a calculation method of rutting was formulated based on vehicle dynamic load and ANSYS 16.0 software. Lastly, the feasibility of the design method on durable asphalt pavement of flexible base on anti-rutting performance was verified combining with the real engineering of a supporting project and several numerical calculations and tests.

Performance Analysis of Multiple Steel Corrugated Pipe Arch Culvert under Construction and Periodic Vehicle Load

The arrangement of multiple culverts has gradually increased in road engineering. However, the arrangement will face a series of risks in both the construction and operation stages. A numerical model was established to analyze the construction and operation safety of multiple steel corrugated pipe arch culverts by using a fully fluid–solid coupling two-dimensional (2D) model of a highway project. The sensitivity of factors affecting the settlement of the composite foundation such as modulus and depth of ground reinforcement was discussed. Based on the results of the 2D model, a fully fluid–solid coupling three-dimensional (3D) model was established to study the influence of dynamic cyclic vehicle load on the mechanical properties of multiple steel corrugated pipe arch culverts. The ground deformation, soil stress and pore pressure, structure stress, and deformation were analyzed. The results show that the maximum settlement of the soil in the arch culvert area is at the junction of the two different arch culverts after construction. The maximum vertical deformation of the structure appears at the vault, and the arch waist is prone to stress concentration. Under cyclic vehicle dynamic load, the ground deformation, structural stress, and arch culvert subgrade deformation showed a rapid growth stage, and then tended to be stable. The weak points in the structure during the construction and operation stages were revealed, which can provide a useful reference for the design and construction of multiple steel corrugated pipe arch culverts.

Novel Weigh-in-Motion Pavement Sensor Based on Self-Sensing Nanocomposites for Vehicle Load Identification: Development, Performance Testing, and Validation.

The development of the transportation industry has led to an increasing number of overloaded vehicles, which reduces the service life of asphalt pavements. Currently, the traditional vehicle weighing method not only involves heavy equipment but also has a low weighing efficiency. To deal with the defects in the existing vehicle weighing system, this paper developed a road-embedded piezoresistive sensor based on self-sensing nanocomposites. The sensor developed in this paper adopts an integrated casting and encapsulation technology, in which an epoxy resin/MWCNT nanocomposite is used for the functional phase, and an epoxy resin/anhydride curing system is used for the high-temperature resistant encapsulation phase. The compressive stress-resistance response characteristics of the sensor were investigated by calibration experiments with an indoor universal testing machine. In addition, the sensors were embedded in the compacted asphalt concrete to validate the applicability to the harsh environment and back-calculate the dynamic vehicle loads on the rutting slab. The results show that the response relationship between the sensor resistance signal and the load is in accordance with the GaussAmp formula. The developed sensor not only survives effectively in asphalt concrete but also enables dynamic weighing of the vehicle loads. Consequently, this study provides a new pathway to develop high-performance weigh-in-motion pavement sensors.

Prediction of ground-borne vibration from random traffic flow and road roughness: Theoretical model and experimental validation

With the densification and closer distance to buildings of road traffic network in urban areas, the assessment and control of environmental vibrations becomes the focus of attention, in which the prediction of traffic flow-induced ground vibration is very critical. However, few studies have been reported on the theoretical prediction method of traffic flow-induced ground vibration from the perspective of stochastic theory. The present work contributes to the perfection and innovation of the current methodologies for the prediction of traffic flow-induced ground vibration. In this paper, a semi-analytical and semi-numerical method for predicting traffic flow induced ground vibrations is developed, in which the random effect generated from traffic flow and road roughness is considered by establishing the vehicle-road-soil coupling model. Aiming to predict the long-term vibration and transient vibration induced by road traffic flow, the average and the adverse velocity levels are used as the evaluation indicators. The effectiveness of the proposed method is validated by an on-site experiment, and the characteristics of ground vibrations are investigated in time and frequency domains, respectively. The results demonstrate that the proposed method can effectively predict the road traffic flow-induced ground vibrations, and the randomness of both traffic flow and road roughness cannot be neglected. For the experimental site, the main frequency band of ground vibrations concentrates on 7–25 Hz, and the predominant center frequency is 12.5 Hz, resulting from the resonance between the overlapping dominant frequency bands of the dynamic vehicle loads and the natural frequency of the soil.

Design and Simulation of Two Stage Reduction Wheel-Edge Drive System

The distributed driving system with electric wheel as key feature has become a major research issue in new energy automobile. However, wheel-edge driving system with reducing gear may cause significant increase of unsprung mass due to introduction of motor and reducer, which is negative to the vehicle maneuverability. As a result, this paper proposed a structural design of two stage reduction wheel-edge driving system which can convert unsprung mass into sprung mass, and established 1/4 three degree-of-freedom vertical vibration system model. Through simulation analysis, the effectiveness of such design was verified. Results showed that two stage reduction wheel-edge driving system can effectively suppress vertical vibration amplitude of automobile body, reduce vehicle dynamic tire loads, and increase riding comfort and tire ground adhesion.

Numerical analysis of interface damage in ballastless track on simply supported bridge due to thermal and vehicle dynamic load

The stiffness, mass and damping matrix of 17 degree of freedom (DOF) vehicle model are derived on the basis of Lagrange equation. The bilinear discrete cohesive zone model (DCZM) is utilized to simulate the bonding performance of the interface between the track slab and the CA mortar layer. The ballastless track-bridge element model is proposed by the direct stiffness method, and the vehicle-ballastless track-simply supported bridge vertical-longitudinal coupled model with consideration of interface damage is established. In addition, based on the ballastless track-bridge element model, the ballastless track continuous welded rail (CWR) model on multi-span simply supported bridge is proposed. The ballastless track CWR model is employed to obtain the initial longitudinal relative displacement of track slab-CA mortar layer interface under bridge thermal load. The displacement response of ballastless track-bridge structure is taken as the initial displacement field of vehicle-track-bridge coupled dynamic model. The vehicle-track-bridge coupled model is adopted to obtain the interface damage of ballastless track under the action of bridge thermal load and vehicle dynamic load. Then, the effects of bridge temperature and longitudinal stiffness of the DCZM on the longitudinal relative displacement of ballastless track-bridge structure are investigated in detail. The mechanism and distribution law of interface damage of ballastless track under different running speeds, CA mortar layer gap length and DCZM parameters are discussed. The conclusions obtained in this paper could provide a technical guide for the formulation of maintenance standards for interface damage of ballastless track on simply supported bridge. Then, some parametric studies are presented based on the model in this paper. The analysis indicates that the longitudinal relative displacement of the track slab-CA mortar layer becomes large at both ends and small in the middle within the range of a simply supported bridge. When there is CA mortar layer void, the ballastless track interface is in the stress state of tension + shear mixed mode. The recommended threshold of void length of CA mortar layer is 0.65 m. More attention shall be paid to the construction quality of interface between the track slab and the CA mortar layer.

Design and Computer Analysis of a Road Load Detection Machine

In this paper, an experimental device is designed for measuring vehicle dynamic load,the structure and stress of the equipment are analyzed by computer technology. The device design mainly includes vehicle, road surface, vehicle transmission, and control [1]. The vehicle is designed based on a 2-DOF vehicle model, the road is designed based on the Pasternak foundation model, and the control mainly uses a single-chip microcomputer. The dynamic response of vehicles to the road at different speeds is analyzed through the experiment.

Damping transformation modeling on wheel suspension using pneumatic cylinder thrust force as a substitute for vehicle weight

This study aims to produce a vertical dynamic load transformation model, FDV of medium weight vehicles that burden the road structure, the form of suspension work characteristics on vehicle wheels that experience disturbances and vertical loading, and the relationship between vehicle vertical dynamic loads and road structure strength, FA0 in the form of a dimensionless parameter. The experiment was carried out at the Pneumatic and Hydraulics Laboratory of the State Polytechnic of Ujung Pandang using pneumatic actuators as a substitute for vehicle weight. The dynamic load fluctuation of the medium weight category vehicle is equivalent to a pressurized air setting from 1 bar to 6 bar which puts a direct load on the suspension system on the vehicle’s wheels. The deviation, Y (cm) that occurs when there is compression on the Spring and Shock Absorber can be measured using a distance sensor, while the vertical dynamic load, FDV which burdens the road surface using a Load Cell. The data were analyzed using the vehicle dynamic load equation with pressure variable, P2 (bar), spring constant, k2 and damping fluid coefficient, c. A mathematical study of the vibration characteristics of the vehicle suspension was obtained using the Mat Lab program. The results showed that the vibration characteristics of the vehicle body experienced an overshot at a deviation of Y is 0.534 m for 0.131 seconds. The role of the shock absorber in the suspension mechanism can reduce 26.43 % of the vertical dynamic load FDV (N), and in the time interval, t is 3 seconds with acceleration deviation, is 0.25 m/s2 begins to feel comfortable. The relationship between vehicle dynamic load, FDV and road structure strength, FA0 is 0.0178. The data from the comparative analysis is then recommended as a consideration for road construction planners to determine the strength and service life of the road.

Effects of welding residual stresses on fatigue reliability assessment of a PC beam bridge with corrugated steel webs under dynamic vehicle loading

Residual stresses are inevitable during welded fabrication of corrugated steel webs (CSWs), resulting in a structure with high stress fields that are difficult to predict and may cause catastrophic failures in structures. Thus, the influence of residual welding stress on the fatigue life of CSWs cannot be ignored. In this study, a numerical simulation method of welded residual stress in CSWs has been proposed. The effect of bending angle, welding path, and the number of welds on the residual stress field distribution has also been analyzed. Then, the distribution characteristics of welded residual stress in CSWs were shown. Six types of vehicle load models were established based on the weight-in-motion system. The stress-time history of the weld details for CSWs under the dynamic moving loading was calculated using the transient analysis method. Based on the stress-time history, the fatigue limit state equation for CSWs considering the combined action of residual welding stress and vehicle loading was derived. Further, the influence of twist angles, welding processes, and traffic growth rates on the fatigue reliability index was discussed. The fatigue reliability of CSWs considering the coupling effect of vehicle load and residual stress has been comprehensively analyzed, providing a theoretical basis for practical design.

Sparrow search algorithm applied to temperature control in PEM fuel cell systems

Working temperature is a critical parameter that influences the performance of proton exchange membrane fuel cells (PEMFCs). Appropriate thermal management can improve the efficiency of PEMFCs and prevent irreversible internal damage such as membrane degradation. To solve the slow response and poor dynamic performance of traditional temperature control strategies, the dynamic temperature mode of PEMFCs is established and a temperature control strategy based on the sparrow search algorithm-proportional integral differential (SSA-PID) is proposed in this study. The performance of the SSA-PID temperature control is verified by the simulations of current step change, vehicle dynamic load, and working parameter variation. The results show that the proposed method has the advantages of fast convergence, better dynamic performance, and anti-disturbance ability. The maximum power density of the SSA-PID temperature controller is 6.58% and 12.94% higher than GA (genetic algorithm)-PID and traditional PID controllers, respectively. Moreover, the proposed method can ensure temperature fluctuations within 0.5 K under dynamic disturbance.

Durability estimation and short-term voltage degradation forecasting of vehicle PEMFC system: Development and evaluation of machine learning models

Proton exchange membrane fuel cell (PEMFC) systems are emerging as one of the most promising solutions for carbon neutrality in transportation, however, durability problem remain a major obstacle to their large-scale commercialization. Developing an accurate model to predict the short-term aging state and long-term durability level of PEMFC is conducive to formulating optimal measures in time and further to improving durability. In this paper, the short-term voltage degradation and long-term durability level are predicted and evaluated by combining machine learning (ML) methods with time-series voltage degradation data obtained under vehicle dynamic load. In the short-term forecasting stage, the long short-term memory (LSTM) model, the support vector regression (SVR) model, and the LSTM-SVR combination model are developed respectively, and the prediction results of the three models are compared and evaluated. The LSTM-SVR combined model achieved the best short-term prediction accuracy of 96.6%, followed by LSTM model (95.5%). Considering the difficulty of model deployment and the feasibility of quickly assessing long-term durability in practical application, a LSTM-based model rolling prediction mechanism is proposed to rapidly evaluate the long-term durability index of the developed PEMFC system, the results show that the proposed forecasting model and method can accurately predict the voltage degradation trend and quickly evaluate the long-term durability level, which not only makes contributions to greatly saving the durability R&D costs, but also provides the possibility to adjust the optimization measures in real-time to further improve the durability according to the prediction results.

Effect of Temperature on the Fatigue Life Assessment of Suspension Bridge Steel Deck Welds under Dynamic Vehicle Loading

The present study proposes a novel fatigue life prediction considering the temperature load, which may be neglected in the traditional assessment of suspension bridge steel deck welds under dynamic vehicle load. Vehicle fatigue, pavement temperature, and temperature gradient models are developed based on the test data from the weight-in-motion system, U-rib welds, pavement temperature, and environment temperature. The U-rib-to-deck and U-rib-to-U-rib welds fatigue stresses are obtained considering both vehicle and temperature loads with transient analysis method in ANSYS package. Then, the temperature gradient fatigue stress spectra are calculated. After that, the fatigue life of two weld types is predicted considering the coupled vehicle-temperature loads. The results indicate that the fatigue stress varies linearly with the temperature of the asphalt concrete. The effect of the temperature on the weld’s fatigue life decreases as the distance increases between the welds and the pavement. The dynamic vehicle load results in a higher fatigue stress than the temperature gradient, indicating that the vehicle load contributes mainly to the bridge’s fatigue damage. Finally, it is calculated that the fatigue damage of two weld types is magnified 5.06 and 1.50 times when the temperature effect is considered after 100-year service of Nanxi Yangtze River Bridge.

Field experiment and numerical investigation on the mechanical response of buried pipeline under traffic load

The acceleration of global urbanization and an increasing intersection of roads and buried pipelines pose a certain threat to the operation safety of pipelines. In this paper, the mechanical response of the X65 pipeline under empty-load, half-load, and full-load traffic loads is investigated via field experiments. The numerical model considering the nonlinear interaction between the pipe and the soil is established. Moreover, an accurate simulation of dynamic vehicle load is achieved by Dload user-defined subroutine. The error between the numerical calculation results and the field experiment results is less than 5 %. On this basis, the influence of five important factors, such as vehicle mass and buried depth, on the axial stress of pipelines is further explored. The results show that the traffic load leads to vertical bending deformation of the pipeline and local deformation of the wheel rolling position. The axial tensile stress generated at the bottom of the pipe is superimposed on the axial tensile stress generated by the internal pressure Poisson effect. The vehicle mass most significantly affects the axial stress of the pipeline, which is generally less than 100 MPa. Furthermore, the operating conditions of the pipeline with large coverage in service are calculated based on Python and ABAQUS co-simulation calculation of 1280 working conditions. The particle swarm optimization-support vector regression (PSO-SVR) hybrid machine learning model is used to accurately predict the axial stress of the buried pipeline under traffic load, and the corresponding correlation coefficient reaches 99.77 %. The research results reveal the mechanical response law of buried pipeline under traffic load, which can provide a basis for the applicability evaluation of buried pipeline in service under traffic load, and accurately evaluate the safety state of buried pipeline.

Design selection and dynamic response analysis of CFG pile composite foundation in soft soil areas

The construction of roads along rivers plays a crucial role in the construction of economic belts and social and economic development along rivers. Roadbeds are the foundation of highway construction, while the soft soil foundation is widely distributed on both sides of rivers, resulting in some difficulties for roadbed construction and highway use. Despite diverse technical methods for the treatment of general roadbeds, the treatment of soft soil roadbeds should be further explored. In this paper, various advantages of applying CFG (Cement Fly-ash Gravels) pile treatment to the soft foundation in Bailinhe Road, Yichang are investigated. Specifically, the soft soil roadbed treated by CFG pile is numerically simulated, the changes in engineering index response before and after foundation treatment are analyzed, and then the dynamic analysis under vehicle dynamic load is performed. The results demonstrate that the reinforcement effect of the CFG pile significantly weakens the influence of vehicle dynamic load on roadbeds.

State of charge and state of health diagnosis of batteries with voltage-controlled models

The accurate diagnosis of state of charge (SOC) and state of health (SOH) is of utmost importance for battery users and for battery manufacturers. State diagnosis is commonly based on measuring battery current and using it in Coulomb counters or as input for a current-controlled model. Here we introduce a new algorithm based on measuring battery voltage and using it as input for a voltage-controlled model. We demonstrate the algorithm using fresh and pre-aged lithium-ion battery single cells operated under well-defined laboratory conditions on full cycles, shallow cycles, and a dynamic battery electric vehicle load profile. We show that both SOC and SOH are accurately estimated using a simple equivalent circuit model. The new algorithm is self-calibrating, is robust with respect to cell aging, allows to estimate SOH from arbitrary load profiles, and is numerically simpler than state-of-the-art model-based methods.