Vehicle Axle Research Articles

Influence depth of highway subgrade under heavy vehicle loads based on a theoretical model

A three-dimensional dynamic model of vehicle-road-unsaturated subgrade coupling is established. The semi-analytical and numerical solutions of three-dimensional dynamic response of highway subgrade under vehicle load are presented for the first time. Then, the accuracy of the theoretical model is verified by the field measurement data. Finally, the spatial distribution of dynamic stress and depth of working zone under different influencing factors are studied, and the calculation model of depth of working zone of highway subgrade is proposed. The results show that the dynamic stresses, σx, σy, σz, and τxz increase significantly with the increase of vehicle axle load and decrease significantly with the increase of road thickness under the same subgrade depth. In addition, with the increase of axle load and the decrease of road thickness, the peak values of dynamic stress σx, σy, σz, and τxz decrease more obviously along the depth of roadbed. In the process of vehicle movement, the traditional subgrade working area can be divided into a sensitive area and an influence area of dynamic load. The depth of these two areas is positively correlated with the axle load of the vehicle and negatively correlated with the thickness of the road surface. The advantage of the model in this paper is that the semi-analytical solution of the total stress component of the soil element in the course of traffic load is given.

Optimal tongue weight selection criteria for light vehicle-trailer combinations

When towing a trailer, proper weight distribution between the vehicle and trailer axles is crucial for system stability and manoeuvrability. Therefore, drivers are strongly recommended to keep the tongue weight, the downward force applied by the trailer at the hitch, within 10–15% of the trailer's gross weight. Despite extensive searches, the current academic and technical literature appears to lack quantitative analyses justifying the standard tongue weight recommendations. This paper presents comprehensive analyses of the lateral behaviour characteristics of light vehicle-trailer combinations influenced by variations in tongue weight. Subsequently, it proposes two novel selection criteria for determining the optimal tongue weight from the perspectives of stability and consistency. The optimal tongue weights for the stability and consistency of the nominal vehicle-trailer system are identified as 22.61% and 48.61% of the trailer weight respectively. Finally, the effectiveness of the proposed criteria is verified through CarSim simulation experiments, assessing 3% settling time and Root-Mean-Square error of vehicle yaw rate.

Dynamic characteristics and damage identification with interface damage of slabs in movable point crossing

As the operating density of China’s high-speed railway increases, the phenomenon of interlayer debonding in movable point crossing (MPC) is becoming more prevalent, which can lead to failure of the frog’s slab track. Meanwhile, vehicle impacts and interlayer debonding can exacerbate abnormal vibration of the vehicle and even lead to derailment. Therefore, based on the theory of rigid-flexible coupling dynamics, a vehicle-turnout-slab coupling dynamics model is established for the first time. In this model, the crossing rails with variable cross sections is considered and the interlayer debonding between turnout slabs is modelled by nonlinear springs. Then, the characteristics of the debonding is identified by applying a wavelet transform to the dynamic response of the vehicle. Finally, different types and sizes of debonding between the layers are considered. The results show that different debonding can lead to two types of contact, partial contact and complete voiding, which can further lead to detrimental effects on vehicle safety. And the limit of the defect size that causes the track slab to void is 1 mm. On this basis, it was found that when MPC’s slab tracks were voided, longer debonding can cause high frequency vibration acceleration of approximately 700 Hz in the vehicle axle box. The new insights obtained by this study could provide guidance for the maintenance period and avoid the development of the damage. This study not only obtained a mechanism for the effect of interlayer debonding on the dynamic response of the vehicle-track system, but also provides a theoretical basis of detecting interlayer debonding for future study.

Deflections and frequencies of long-span steel railroad truss bridges under passenger train excitation using laser Doppler vibrometer

ABSTRACT Given the critical challenge of aging infrastructure, it is imperative to adopt novel techniques that utilize modern technology to assess the structural integrity of existing bridges. This study presents a methodology to estimate the loading frequency of the train passing over the bridge and bridge dynamic responses, such as the acceleration and displacement response of long-span open-deck steel railroad truss-type bridge under the passenger train excitation using a Laser Doppler Vibrometer. The selected bridges for this study were the Cos Cob and Devon Railroad bridges in southern Connecticut, both in the Northeast Corridor. The structural response of the bridge floor system was collected during the field test using a single-point laser Doppler vibrometer and uniaxial accelerometers for reference under passenger trains, such as Metro-North M8, Amtrak Regional, and Amtrak Acela. The recorded data were analyzed using the moving load theory, interpreted, and discussed in the time and frequency domain. The study findings indicate that the bridge response and displacement align with the theoretical and vehicle axle loads. Also, it should provide valuable information about the behavior of the considered bridges under typical operating conditions.

Implementing innovation in project-based learning in electro-mechanical engineering education

This study investigates the implementation of project-based learning (PBL) in electro-mechanical engineering education, emphasizing the modeling and application of an innovation process to enhance student engagement, motivation, and employability. Initially, the innovation process was systematically modeled using Structured Analysis and Design Technique (SADT) to manage and organize skills, knowledge, and resources effectively. This model was subsequently applied in an educational experience focused on highly technical aspects such as energy conversion modeling, mechanical improvements, material science, and efficiency analysis. These aspects were primarily applied in the context of permanent magnet synchronous machines employed in electric vehicle (EV) axles. The SADT modeling allowed for a clear delineation of the innovation phases, ensuring a structured approach to project execution. Statistical analysis of the PBL approach indicated significant improvements in student performance, with a 25% increase in problem-solving skills and a 30% enhancement in critical thinking abilities. The case study demonstrated that industry-oriented projects significantly boost student satisfaction, particularly in problem definition and solution identification, leading to a more engaging and effective learning experience.

Application of ultra-weak fiber Bragg grating sensing array to road vehicle detection

Road vehicle detection is a significant task for tackling traffic issues in intelligent transportation systems (ITS). In this paper, we introduce ultra-weak fiber Bragg grating (UWFBG) sensing technology for road vehicle flow, vehicle axle and wheelbase detection. We carry out pilot installation of UWFBG sensing optic cables in the asphalt base of the road in a new-built expressway. As opposed to the conventional linear installation along the road running direction, the deployment of cables is mainly perpendicular to the road. Using the acquired vehicle data, we analyze signal characteristics and propose real-time data processing algorithms based on identification and classification of peaks/valleys of vehicle waveforms as well as cross-correlation calculation. We test the proposed method in different scenes. Test results show that the calculated wheelbases achieve good accuracy (relative errors are <1 %) and the algorithms can well distinguish individual vehicle in complex vehicle conditions.

Deep Learning–Based Detection of Vehicle Axle Type with Images Collected via UAV

Deep Learning–Based Detection of Vehicle Axle Type with Images Collected via UAV

Drive-By Identification of Joint Bridge Damage and Surface Roughness Based on Sensitivity Analysis of Residual Contact Point Deflections

Drive-by inspection of bridge damage using a passing vehicle’s dynamic response has great potential in bridge damage identification. Among the current drive-by methodologies, the methods based on bridge modeling have been proposed for the quantitative identification of bridge damage and bridge surface roughness. However, the coupling of bridge damage and unknown surface roughness increases the difficulty of the identification problem and most previous studies conduct the identification task of bridge damage or bridge surface roughness separately. In this paper, a novel method is proposed for the identification of joint bridge damage and bridge surface roughness based on the residual bridge deflections from the front and rear wheels contact points of an instrumented passing vehicle. The vehicle–bridge interaction is analyzed using a half-car model of a four degrees of freedom (4-DOF) with front and rear vehicle wheels. First, the vehicle–bridge unknown forces and displacement of the vehicle axles are identified by the generalized Kalman filter under unknown input (GKF-UI) proposed by the authors. The sensors can be installed conveniently on the vehicle body due to GKF-UI. Then, the residual bridge deflections from the front and rear vehicle wheels contact points are utilized to eliminate the effect of road surface roughness. Afterward, bridge structural damage is identified based on the sensitivity analysis of residual bridge deflections from the front and rear contact points with [Formula: see text]1-norm regularization. Finally, bridge road surface roughness is estimated based on the identified unknown forces and updated bridge model with damage. The results of numerical identification examples demonstrate the effectiveness of the proposed method for the identification of joint bridge damage and surface roughness.

Versatile Lamellar Wrap-Structured PVDF/PZT/CNTs Piezoelectric Sensor for Road Traffic Information Sensing, Monitoring, and Energy Harvesting

Active monitoring and accurate sensing of road traffic information provide crucial data for road managers and traffic law enforcement. However, current sensors and monitoring systems struggle to capture comprehensive vehicle information simultaneously. In the study, a novel piezoelectric sensor using PVDF/PZT/CNTs composites was developed for actively monitoring road traffic information and explored for energy harvesting suitability. Piezoelectric composites with a lamellar wrapped structure and excellent localized conductive networks were prepared through solution blending, non-solvent-induced phase separation, and layered hot pressing. The results revealed that this structural design improves the proportions, crystallinity, and content of the β-phase crystals in the composites, while significantly enhancing their piezoelectric properties, dielectric properties, and electronegativity. When the content of CNTs was 3.0 wt%, the proportion and content of β-phase crystals in the composites reached the highest values (91.36 % and 62.34 %), respectively. Additionally, the open-circuit voltage (Voc) and the short-circuit current (Isc) were 3.36 and 6.16 times higher, respectively, than those of the undoped CNTs composites. The developed piezoelectric sensor shows a wide pressure monitoring range (0.1 MPa–2.1 MPa), excellent sensitivity (6.94 MPa−1 at (<0.6 MPa) and 12.35 MPa−1 at (0.6–2.1 MPa)). As a vehicle non-stop weighing sensor, it presents extremely fast response (15 ms) and recovery (16 ms) speeds with long-term stability of 500,000 cycles. The most important feature of the developed piezoelectric sensor is its dual function as both a sensor and an energy harvester. Furthermore, the developed piezoelectric sensor can actively monitor vehicle axle weight, speed, and wheelbase while capturing energy from vehicle movement. This work opens up innovative solutions for road traffic monitoring and vehicle movement energy harvesting, with promising applications in intelligent transportation.

Development and Performance Analysis of Commercial Vehicle Axle Shaft

Axle shafts, which are an important part of the vehicle's powertrain system, transfer the torque to the wheels and enable the vehicle to move. In this respect, the design of the axle shaft to be used in a new vehicle is of great importance for vehicle manufacturers. When a cylindrical shaft is torsionally loaded, the shear stress is highest at the surface of component and zero at the center. Therefore, these axle shafts are exposed to an induction hardening process that enables only this superficial case to have its properties changed, remaining the core zone with its material original characteristics. Current study presents the results of a project aimed at developing and evaluating the fatigue life of axle shaft that belongs to a commercial vehicle. Developments were made on the existing axle and the results were examined using experimental tests and finite element analysis method. In line with the improvements made, the developed axle shaft has 331.7% more fatigue life than the existing axle, while the cost is 24% lower. According to these results, more attention must be paid to material selection, induction hardening process, stress concentration and surface condition of axle shaft in the design. This study involves many disciplines such as design, manufacturing, analysis, testing, etc. It is very important to ensure communication between all these disciplines in the production of the product. The output obtained from one discipline becomes the input of another discipline. In the cumulative sum of all these inputs, the optimum level of parts is obtained. For this reason, this study, which processes all these disciplines together, is very valuable.

Track–bridge interaction effects in the acceleration and displacement response of high-speed railway bridges: Simplified vs refined modelling

The prediction of structural vibrations induced by high-speed trains is crucial for designing bridge structures, as well as for the assessment of the dynamic compatibility between bridges and rolling stock in large railway networks. The computational effort involved in such dynamic compatibility checks is also large. However, obtaining an accurate prediction of the dynamic response is challenging due to numerous uncertain factors still under research. Interaction phenomena like vehicle–bridge (VBI), soil–structure (SSI), and track–bridge (TBI) interactions are crucial but complex to model, given the multitude of input parameters and the computational cost required. Therefore, the choice of a modelling approach for simulating the dynamic response of a train crossing a bridge will depend on the focus of analysis. For the purpose of sensitivity analyses – typical in early design stages –, compatibility checks (screenings), and also in non-deterministic analyses, computational cost becomes crucial. Consequently, for practical purposes interaction mechanisms are often simulated by means of simplified and conservative approaches, usually aligned with some design code recommendations. Moreover, traditional physical models, where the problem is idealised as a beam traversed by constant moving loads (travelling load model, TLM), have been commonly employed for such purposes. However, they neglect the load distributive effect of the track on the vehicle axle loads, which has proven to be relevant and beneficial, especially for short bridge spans. The main purpose of this work is thus to investigate the influence of the load spreading effect exerted by the ballasted track on the displacement and acceleration response of single-track, simply-supported (S-S) railway bridges of short-to-medium span lengths under operating conditions, since these structures are prone to experience inadmissible vibration levels under more demanding traffic conditions. A comprehensive analysis of several simplified approaches proposed by regulations and researchers is performed, plus a subsequent comparison vs. a finite element (FE) strategy to consider TBI in a refined manner. Conclusions about the adequacy of the simplified approaches are provided, along with a new data-driven formula for the prediction of the vertical displacement response in resonant conditions, that can be exploited to reduce significantly the computational effort.

A case study on scenario-based optimization for axle load survey data selection for flexible pavement design in Vietnam

The unique traffic patterns in Vietnam, characterized by a mix of vehicle types, axle configurations, and overloading, pose challenges to current flexible pavement design methods. This study investigates how selecting different vehicle axle load survey data scenarios impacts the accuracy of pavement design and rehabilitation for roads in Vietnam. Evaluation of various data selection methods and their influence on pavement response using the current flexible pavement calculation procedure in Vietnam. By comparing the pavement design criteria calculated under each scenario, this research aims to provide clear guidelines for engineers choosing appropriate axle load data for pavement design. This, in turn, will lead to the design and maintenance of more durable and sustainable pavements, ultimately promoting a more efficient and resilient transportation infrastructure in Vietnam. The research approach involves analyzing various axle load survey data scenarios, including those representing typical traffic conditions, overloaded vehicles, and specific vehicle types. The calculated pavement responses under each scenario are then compared to assess the impact of data selection on design outcomes. This study's findings are expected to provide valuable insights for pavement engineers in Vietnam, enabling them to select appropriate axle load data for accurate pavement design and rehabilitation. This will contribute to building more durable and sustainable road infrastructure, resulting in a more efficient and resilient transportation network

Contact-point response reconstruction for indirect bridge monitoring via Bayesian expectation-maximization based augmented Kalman filter

The drive-by bridge dynamic measurement using an instrumented vehicle during its passage over the bridge can be an indirect bridge structural health monitoring system. The identification of the contact-point (CP) responses between vehicle wheels and bridge structure from vehicle responses offers an efficient and economical way for the modal identification and condition assessment of short- to mid-span road bridges. This paper proposes a novel method for the contact-point displacement response reconstruction of the vehicle-bridge interaction (VBI) system in a joint input-state estimation manner based on Bayesian Expectation-Maximization (BEM). An analytical model of VBI including the road approach in front of a simply-supported bridge is presented firstly. Then the augmented state-space model of the vehicle with the contact-point responses included as variables along with vehicle states is established. A new method by integrating the augmented Kalman filter (AKF) with a BEM strategy is proposed to solve the state estimation problem without knowing the vehicle axle responses. The vehicle states and CP displacement responses are identified simultaneously. The effects of the measurement noise, road surface roughness and vehicle speed on the identified results are investigated using numerical simulations. The experimental tests are used to further verify the feasibility and accuracy of the proposed method. The results show that the proposed method has potential for drive-by bridge condition assessment using on-board vehicle response measurements for a large population of short- to mid-span bridges.

Machine Learning and Signal Processing for Bridge Traffic Classification with Radar Displacement Time-Series Data

This paper introduces a novel nothing-on-road (NOR) bridge weigh-in-motion (BWIM) approach with deep learning (DL) and non-invasive ground-based radar (GBR) time-series data. BWIMs allow site-specific structural health monitoring (SHM) but are usually difficult to attach and maintain. GBR measures the bridge deflection contactless. In this study, GBR and an unmanned aerial vehicle (UAV) monitor a two-span bridge in Germany to gather ground-truth data. Based on the UAV data, we determine vehicle type, lane, locus, speed, axle count, and axle spacing for single-presence vehicle crossings. Since displacement is a global response, using peak detection like conventional strain-based BWIMs is challenging. Therefore, we investigate data-driven machine learning approaches to extract the vehicle configurations directly from the displacement data. Despite a small and imbalanced real-world dataset, the proposed approaches classify, e.g., the axle count for trucks with a balanced accuracy of 76.7% satisfyingly. Additionally, we demonstrate that, for the selected bridge, high-frequency vibrations can coincide with axles crossing the junction between the street and the bridge. We evaluate whether filtering approaches via bandpass filtering or wavelet transform can be exploited for axle count and axle spacing identification. Overall, we can show that GBR is a serious contender for BWIM systems.

Deep learning-based identification of vehicular moving forces for bridges without axle configurations

This study proposes a novel moving force neural identifier (MFNI), a deep neural network designed for accurately estimating dynamic vehicular axle loads without knowing the vehicle speed and axle configurations (i.e., axle number and spacing). The MFNI architecture comprises a multi-time resolution encoder/decoder (MRED) and a dynamic moving force correction block (DMF-corr block). Firstly, the MRED with hierarchical resolution is developed to adapt to the complex dynamic inverse problem-solving. It can capture the multi-time resolution features of bridge responses and dynamic moving forces, and perform stably under various lengths of identification sampling windows. Then, the DMF-corr block limits the range of identified values by assuming that the vehicular excitation on the bridge is unidirectional, which enables the MFNI model to better determine the axle number, vehicle speed, as well as whether the axle is acting on the bridge. Numerical studies are implemented to confirm the accuracy and efficiency of the proposed MFNI approach, and a parametric sensitivity analysis is conducted to evaluate the robustness of the approach. Finally, a laboratory experiment confirms the practicability of the MFNI in detecting vehicular moving forces with a limited number of sensors and training samples. Both numerical and experimental results demonstrate the potential of the proposed method to serve as a nothing-on-road bridge weigh-in-motion system in practical engineering.

Development of a Mechanistic-Empirical-Based Highway Cost Allocation Model for Flexible Pavements

Construction, operation, and maintenance of a pavement network requires funding, partially sourced from road user taxes. Recent studies showed that lightweight vehicles are typically taxed higher compared with heavy trucks that damage the roads the most. To facilitate the equity and fairness of the allocated costs to different vehicles in the United States (U.S.), Highway Cost Allocation Studies (HCAS) were performed using various pavement performance prediction models. Reviewed literature showed the lack of mechanistic-empirical (ME)-based HCAS models for the flexible pavement network. In this study, a national-level ME-based HCAS model was developed, and the damage shares of different vehicle classes have been estimated for 67,583 pavement sections in the U.S. Highway Performance Monitoring System (HPMS) database. The proposed HCAS model was compared with the existing Federal Highway Administration (FHWA) HCAS model (i.e., National Pavement Cost Model [NAPCOM]). The analysis of the traffic data showed that two-axle single-unit trucks (SU2) and tractor-semitrailers with two tandem and one single axle (CS5T) were the most frequent users of the pavement network. The results showed that the damage share of SU2 is dominant in minor roadways, while the damage share of the heavier vehicles in the CS5T class is dominant in major arterials and interstates. In addition, it was found that, although the geographical location and environmental condition of the pavement section affects the magnitude of the pavement distresses, the distribution of the damage shares remains almost the same. This can be attributed to the similarities in the traffic data, for example, vehicle class distribution and axle load spectra.

Monitoring bearing damage in bridges using accelerations from a fleet of vehicles, without prior bridge or vehicle information

This paper describes a novel method for detecting bridge damage that uses a partially instrumented vehicle fleet, each vehicle being instrumented with just one accelerometer. Importantly, no prior knowledge of the bridge or individual vehicle properties is required. Firstly, a model simplification concept is proposed to calculate the displacement under the vehicle wheel from single acceleration measurements on a half-car model. Then, optimisation is used to find individual vehicle properties using simulated noisy measurements from a fleet of vehicles. Finally, accelerations from the fleet are used to find the ‘apparent profile difference’, which contains bridge deflection data. The difference is found to be independent of surface profile but dependent on vehicle axle weight differences and a moving reference influence function (MRIF). When the axle spacings and the relative axle weights are reasonably consistent in a subset of the fleet, the MRIF can be simplified into a compound MRIF. Even when the MRIF and individual axle weights are not available on-site, the shape of the compound MRIF can be determined through an iterative process and used to monitor bridge health condition. Bearing damage is represented in this paper as an increase of rotational resistance of the bearings. The numerical results show that the damage severity and location can be identified.

Návrh koľajového adaptéra typu guma-koľajnica pre ľahké nákladné vozidlo

The article is focused on design of a tyre-rail adapter to be mounted on a light road-rail vehicle. The novelty of the design consists in its possibility to change the wheelbase of the vehicle axles for different railway tracks gauges. Then, the considered light vehicle could fulfil various working tasks in a country, where more railway tracks gauges occur. The modified vehicle is a light lorry, which is intended to be used as a versatile and utility vehicle for maintenance purposes and repairing purposes.

The influence of weight control parameters of cargo vehicles on their performance

The article examines the problem of incomplete use of the carrying capacity of vehicles due to regulatory restrictions on the permissible weight of the vehicle and the permissible load on the axle of the vehicle, analyzes the conditions under which the vehicle becomes heavy, and their owners may be subject to fines for violating current legislation in the field of weight control of vehicles, an example of the results of calculating the coefficient of utilization of the carrying capacity of a specific vehicle with axle loads not exceeding permissible is given for a highway with a standard load of 6, 10 and 11.5 tons, proposals are formulated for the effective use of vehicles in terms of carrying capacity under the conditions of normatively established weight restrictions. Keywords heavy vehicle, weight control, standard road loads, vehicle axle load

Terminological clarification of the concept of truck overload

The article analyzes the concept of overload in relation to freight vehicles in conditions of weight control of vehicles. Based on the results of the analysis of a number of publications in this area, including scientific ones, it is indicated that the term "overload" used in them is identified with exceeding the normatively established permissible mass and (or) loads on the axles of the vehicle, which, in the reasonable opinion of the author, is incorrect. Based on knowledge in the field of terminology theory and guided by existing dictionary definitions of overload in railway and maritime transport, it is proposed to give the term "overload" in truck transport a similar meaning. Keywords freight vehicles, weight control, standard road loads, overload, vehicle axle loads, transport terms