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    <title>Transport Research International Documentation (TRID)</title>
    <link>https://trid.trb.org/</link>
    <atom:link href="https://trid.trb.org/Record/RSS?s=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" rel="self" type="application/rss+xml" />
    <description></description>
    <language>en-us</language>
    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
    <image>
      <title>Transport Research International Documentation (TRID)</title>
      <url>https://trid.trb.org/Images/PageHeader-wTitle.jpg</url>
      <link>https://trid.trb.org/</link>
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    <item>
      <title>Analysis of the Impact on Ride Comfort from Splitting the Unsprung
          Mass in Vehicle Modeling</title>
      <link>https://trid.trb.org/View/2761638</link>
      <description><![CDATA[The study was conducted to investigate the differences in ride comfort analysis                     between treating the unsprung mass as a whole and modeling it separately. A                     classical two-degrees-of-freedom single-wheel vehicle vibration model and a                     three-degrees-of-freedom single-wheel vehicle vibration model with split                     unsprung mass were established, with their state-space descriptions determined.                     The fundamental vibration response quantities of both models were identified,                     and time-domain simulations under random road excitation were performed using                     MATLAB/Simulink. The results indicate that the two modeling approaches exhibit                     minimal differences in ride comfort analysis for the sprung mass, but there are                     certain differences for the unsprung mass. Additionally, for the                     three-degrees-of-freedom single-wheel vehicle vibration model with split                     unsprung mass, the axle-to-wheel mass ratio was introduced to analyze the                     changes in the fundamental vibration response quantities when the unsprung mass                     increases by a fixed value and is distributed differently between the axle and                     the wheel. The results show that variations in the axle-to-wheel mass ratio have                     no significant impact on the vibration characteristics of the sprung mass.                     Reducing the mass ratio, i.e., transferring part of the unsprung mass to the                     wheel, can somewhat reduce the vertical acceleration of the unsprung mass, but                     it will slightly increase the relative dynamic load on the wheel. Finally, the                     other two models were simplified by combining the two masses connected by the                     bearings.]]></description>
      <pubDate>Wed, 19 Aug 2026 13:49:57 GMT</pubDate>
      <guid>https://trid.trb.org/View/2761638</guid>
    </item>
    <item>
      <title>Analysis and Optimization of Noise and Vibrational Performance of an Electric Axle</title>
      <link>https://trid.trb.org/View/2761845</link>
      <description><![CDATA[As the electric mobility landscape evolves, there is a growing emphasis on addressing the Noise, Vibration, and Harshness (NVH) challenges associated with electric drivetrains. The absence of an IC engine in EVs shifts the focus to other noise contributors such as gear meshing, electric machine operation, and structural vibrations. Despite the known influence of micro-geometry on gear dynamics, current optimization practices often rely on empirical adjustments or standard guidelines without fully utilizing advanced computational methods to predict and optimize NVH performance. There exists a pressing need for a systematic approach to analyze and optimize gear micro-geometry to reduce noise and vibration in high-speed e-axle applications. This research aims to bridge that gap by investigating the relationship between micro-geometry optimization and NVH characteristics of an e-axle. Through detailed modelling and optimization techniques, this research aims to identify optimal gear micro-geometry parameters that minimize transmission error and reduces noise from an e-axle. In this paper, transmission error (TE) is calculated for four different load cases based on motor’s torque-characteristic curve. Then, equivalent radiated power (ERP) is calculated at these load cases to determine major source of excitation and then acoustic analysis is done without micro-geometry optimization (MGO) to record the sound pressure level. After this, gears micro geometries are optimized and same process is repeated to measure the optimized sound pressure level. It is seen that after micro-geometry optimization, sound pressure level corresponding to first harmonic of 1st gear pair decreased by approximately 30%, 20%, 23% and 21% for load cases 1, 2, 3 and 4 respectively and the sound pressure level for same loads corresponding to first harmonic of second gear pair has decreased approximately by 58%, 36%, 23% and 20% respectively. It is also observed that sound pressure level of electric motor remains unaffected by gear micro-geometry optimization. Thus the research shows that noise and vibrations can be reduced by optimizing the micro-geometry parameters using computational tools and by optimizing the noise levels at the initial design stages we can avoid design changes and project delays at the later stages of project.]]></description>
      <pubDate>Wed, 19 Aug 2026 13:48:42 GMT</pubDate>
      <guid>https://trid.trb.org/View/2761845</guid>
    </item>
    <item>
      <title>Simulation Driven Virtual Road Load and Accelerated Duty Cycle Generation for 3-Speed eAxle Systems</title>
      <link>https://trid.trb.org/View/2761816</link>
      <description><![CDATA[The transition from Internal Combustion Engine (ICE) vehicles to Battery Electric Vehicles (BEVs) introduces significant challenges in drivetrain development, particularly when historical road load data (RLD) is unavailable This study presents a methodology for virtually generating and processing road load data (RLD) to assess the durability of a new 3-speed electric axle (eAxle) design before building a physical prototype. Using AVL Route Studio, we simulated a range of driving conditions including urban, highway, and mixed-terrain routes, covering diverse global scenarios. These simulations produced high-frequency torque and speed data representative of real-world operation. Given that the raw dataset contained millions of points, direct use for fatigue assessment was impractical. To address this, the data was imported into Romax, where it was condensed into an accelerated duty cycle while preserving the cumulative fatigue damage patterns from the original dataset. Unlike conventional binning methods, which can misrepresent load severity, our damage-matching approach maintained accurate replication of gear contact, gear bending, and bearing damage characteristics. This methodology enables early-stage durability validation of eAxle designs without dependence on physical testing or historical data. Our findings suggest a correlation between condensed and original damage profiles for transmission components, indicating that this virtual approach may be useful. The framework offers a potential method for virtual RLDA work that could help with design verification and optimisation for electric drivetrains.]]></description>
      <pubDate>Wed, 19 Aug 2026 13:48:42 GMT</pubDate>
      <guid>https://trid.trb.org/View/2761816</guid>
    </item>
    <item>
      <title>Experimental investigation of the influence of individual components on the vertical characteristics of a MacPherson strut axle</title>
      <link>https://trid.trb.org/View/2742347</link>
      <description><![CDATA[Vehicle axle vertical characteristics strongly affect ride comfort and handling, but the influence of individual components is not well quantified. It remains unclear to what extent individual components contribute to the stiffness, friction, and damping characteristics of a vehicle axle. This study aims to quantify the contribution of individual components to the axle characteristics, with particular emphasis on axle damping. To address this question, a MacPherson strut axle was tested on an axle test rig in 19 configurations. In addition to the intact axle, components were removed, deliberately degraded, or mechanically decoupled to prevent force transmission between selected components. The axle was excited quasi-statically and dynamically, using both single-sided excitation and harmonic in-phase excitation of both wheel carriers. For each axle configuration, stiffness, damping, and friction were evaluated. The results show that removing either the main springs or the anti-roll bar substantially reduced axle friction, indicating that these components introduce preload within the axle assembly that increases friction. In addition, a sand-contaminated lower ball joint significantly increased friction in the linear evaluation region. The damping analysis revealed that draining the shock absorbers of oil reduced axle damping by approximately 80% relative to the intact axle for all investigated excitations.]]></description>
      <pubDate>Wed, 19 Aug 2026 09:25:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/2742347</guid>
    </item>
    <item>
      <title>On-Board Vehicle Weighing For Intelligent Road Freight Control</title>
      <link>https://trid.trb.org/View/2579500</link>
      <description><![CDATA[Smart Enforcement of Transport Operations (SETO) is a Horizons Europe project that supports digital transformation in transportation, including access to data of interest to regulators. The goal is to provide authorities with access to relevant data so that enforcement activities become more efficient for both the enforcer and the transporter. The concept is multi-modal and includes the design of an on-board unit for ships, like what is already available for trucks, which will store data about the skipper, journey, e-documents, etc.. This innovation will be tested in a Living Lab in Belgium. For roads, a key element in the enforcement process is the vehicle weight and technologies which allow for on-board vehicle self-weighing. This paper presents the concept of an on-board tamper-proof vehicle weighing solution. Truck axles are equipped with accelerometers whose signals are indirectly affected by the road profile and the vehicle weight. If the vehicle properties, including weight, are known, the road profile can be calculated. As many trucks pass over the same profile, it is possible to compare calculated profiles and to use this to back-calculate each vehicle weight. As the road profile is part of the calculation, it is difficult for any driver to tamper with the vehicle self-weighing system.]]></description>
      <pubDate>Wed, 12 Aug 2026 17:07:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2579500</guid>
    </item>
    <item>
      <title>The Influence of Time-Varying Meshing Stiffness on the Vibration Characteristics of Gears in Electric Drive Axle Reducers</title>
      <link>https://trid.trb.org/View/2742575</link>
      <description><![CDATA[The dynamic characteristics of the electric drive axle of the new energy commercial vehicle is an important performance to evaluate its quality, and the dynamic performance of the two-stage helical gear transmission system in the electric drive axle reducer directly reflects the dynamic performance of the electric drive axle. This study focuses on the secondary gear transmission system of the electric drive axle reducer of the new energy commercial vehicle, and mainly studies the influence of the tooth surface contact stiffness with the change of meshing on the vibration performance of the transmission system. Through establishing the coupled nonlinear dynamic model of torque-begear shaft of high-speed helical gear, the dynamic equations of the system under the influence of time-variable contact mesh stiffness are derived. Taking gear error excitation and support stiffness into consideration, a 3D model software is used to build the simulation virtual model of bevel gear of electric drive axle reducer, and the dynamic simulation analysis of its transmission system is carried out. By setting different tooth contact stiffness coefficients, the variation rules of translational vibration acceleration, angular acceleration and spectrum response of transmission gears are studied systematically. Simulation results indicate that selecting the contact stiffness coefficient within 80% to 90% of the average mesh stiffness value leads to improved meshing performance in the gear transmission system of an electric drive axle reducer. This configuration results in reduced vibration amplitude, narrower sidebands, and decreased dynamic transmission error, thereby effectively enhancing the NVH performance of the transmission system. The findings also provide an important reference for optimizing the meshing behavior of electric drive axle reducers.]]></description>
      <pubDate>Mon, 03 Aug 2026 15:36:38 GMT</pubDate>
      <guid>https://trid.trb.org/View/2742575</guid>
    </item>
    <item>
      <title>Dynamic Characteristics Analysis of High-Speed Trains Considering Wheel Polygonal Wear Under Track Irregularity Excitation</title>
      <link>https://trid.trb.org/View/2579251</link>
      <description><![CDATA[Wheel polygon wear (WPW) is a common form of wheel non-circularity in high-speed trains. As the train speed increases, the WPW and track irregularity excitation become coupled, which not only excites the structural deformation of the flexible wheelset, but also aggravates the high-frequency components of the axle box’s vibration response. This paper develops a rigid-flexible coupling dynamic model using the Craig-Chang reduction method, and analyzes the coupling effect of track irregularity excitation and WPW on the axle box vibration response at 300 km/h. The study also investigates the influence of WPW wear order and depth on the amplitude of the response harmonic component, the amplitude of the wheelset modal frequency, and the safety evaluation metrics under the coupling effects. The results show that the coupling effect significantly increases the vibration level of the axle box, but reduces the amplitude of the wheel bending, torsional deformation modal frequency and the WPW excitation frequency. This study provides theoretical and technical support for the dynamic optimization of high-speed train wheel groups.]]></description>
      <pubDate>Fri, 31 Jul 2026 16:05:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/2579251</guid>
    </item>
    <item>
      <title>Effect of Stiffening Rib Location on Failure Tendency of a Heavy-Duty Rear Axle Housing</title>
      <link>https://trid.trb.org/View/2579381</link>
      <description><![CDATA[Within the scope of this work, the effect of the position of the stiffening ribs used in the arm transition regions of a heavy-duty truck rear axle housing prototype on fatigue failure tendency was examined. In the vertical fatigue tests applied to the housing prototype, it was observed that the component withstood the targeted number of load cycles, however suffered fatigue damage at the lower stiffening rib - spring support connection area above this limit. To determine the effects of rib position on stress distribution of the part, firstly the vertical loading test was simulated using Finite Element Analysis (FEA). It was determined that the stress concentration region and the area where fracture occurred in the tests overlapped. Design improvement including relocating the stiffening ribs was applied to the housing model to decrease stress concentration at the critical regions. Results indicated that it is possible to reduce the maximum stress at the crack initiation region by approximately 41%. It was also concluded that placing stiffening ribs at the upper region of the axle housing could enable a lighter design.]]></description>
      <pubDate>Mon, 13 Jul 2026 10:46:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/2579381</guid>
    </item>
    <item>
      <title>Detection of Rail Surface Defects Based on Axle Box Acceleration Measurements: A Measurement Campaign in Sweden</title>
      <link>https://trid.trb.org/View/2671108</link>
      <description><![CDATA[This work presents the results of a measurement campaign to demonstrate the effectiveness of the axle box acceleration (ABA) technology for detecting rail defects. The measurements were conducted along the Iron Ore line between Sweden and Norway for the IN2TRACK3 project. This line is mostly single-track with passenger-freight mixed traffic and heavy axle load. Historical data and track information data were not considered in this study. By analyzing data acquired from the accelerometers in vertical and longitudinal directions, rail defects were detected in near real-time using big-data analytics. For our validated sections, 100% of rail defects (including squats) were detected using time-frequency analysis and an outlier detection approach. The methodology also allows for identifying priority locations, e.g., defective welds, joints, transition zones, etc., and its use for prescriptive maintenance recommendations is being explored in the framework of the IAM4RAIL project.]]></description>
      <pubDate>Tue, 30 Jun 2026 09:45:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2671108</guid>
    </item>
    <item>
      <title>Study and Testing of Wheelset Wheel-Flat Identification Features through Axle-Box Vibration Measurements</title>
      <link>https://trid.trb.org/View/2676033</link>
      <description><![CDATA[Early detection of wheelset defects is essential for ensuring railway safety. Wheelset condition monitoring can provide continuous information about the health of the system, thus avoiding time-consuming and expensive operations such as periodic inspections. This work deals with the study of railway wheelset wheel-flat identification features based on vibration signals from axle-box measurements. The aim is to obtain a simple and straightforward solution that can be easily implemented on a complete autonomous on-board sensor for wheelset defect prediction. Numerical simulations, by coupling a multi-body model of a coach with a new approximation of a wheel-flat model, were run in order to estimate the nature of the problem and the technical acquisition characteristics needed for a sensor node to be installed on real trains. Then, experimental campaigns were carried out on a wheelset test bench with defects artificially created to validate the presented methodology based on time domain feature extraction. A signal processing technique, which does not require the aid of any other hardware to obtain the revolution speed, is proposed. The methodology allows clear detection of wheel flats starting from 30 mm, especially at lower speeds. Even when considering the influence of wear, high defect conditions remain easily distinguishable.]]></description>
      <pubDate>Mon, 08 Jun 2026 08:38:12 GMT</pubDate>
      <guid>https://trid.trb.org/View/2676033</guid>
    </item>
    <item>
      <title>HEV Transaxle Loss Estimation Using Integrated Physical and Experimental Model</title>
      <link>https://trid.trb.org/View/2674986</link>
      <description><![CDATA[In the parameter design of HEV driving control, it is important to consider not only the outputs of the engine and motor, rolling resistance, and aerodynamic drag, but also internal resistance, such as transaxle loss, especially under various operating conditions. To address this issue, an integrated loss estimation model was developed by combining a physical model, based on fundamental specifications of bearings and gears, with an experimental model that captures factors difficult to represent physically, such as oil level and lubrication conditions.]]></description>
      <pubDate>Thu, 04 Jun 2026 11:57:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/2674986</guid>
    </item>
    <item>
      <title>Research on Carbon Emission Calculation Algorithm for Trucks on
          Expressways in Xinjiang</title>
      <link>https://trid.trb.org/View/2706241</link>
      <description><![CDATA[In the field of measuring carbon emissions from road traffic, the carbon emission                     factor method has remarkable advantages in terms of standardization, operational                     simplicity, and adaptability. Backed by the IPCC international standard                     framework, this method offers convenient access to a dynamic factor database and                     incorporates an adaptive adjustment mechanism for real-world scenarios, such as                     technological advancements and regional disparities. Against this backdrop, this                     study employs the carbon emission factor method to establish refined measurement                     models based on load capacity and fuel consumption, respectively. These models                     are then applied to quantify carbon emissions from trucks on specific sections                     of the G30 highway in Xinjiang. The load-based model calculates emissions by                     integrating truck axle weight and driving distance, while the fuel-based model                     analyzes fuel consumption data in conjunction with driving mileage. A comparison                     of the two models in terms of measurement differences is also carried out in the                     research. Furthermore, it provides a granular breakdown of energy consumption                     data for fully loaded trucks exceeding 31 tons, as specified by national                     standards. This introduces a novel approach to precise carbon emission                     measurement in heavy-duty transportation in northwestern China. It also provides                     a method for establishing an emission mitigation policy that is region-specific                     on a scientific basis.]]></description>
      <pubDate>Tue, 02 Jun 2026 11:09:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/2706241</guid>
    </item>
    <item>
      <title>Dog Clutch Actuator Control to Mitigate NVH</title>
      <link>https://trid.trb.org/View/2701253</link>
      <description><![CDATA[Dog clutches have long been employed in the automotive industry across various applications, including transmission systems, transfer cases, axle disconnects, and hybrid driveline architectures. Their ability to provide direct mechanical engagement makes it ideal for torque transmission with minimal energy loss. However, the transition between engaged and disengaged states can introduce noise, vibration, and harshness (NVH), which may be perceptible to vehicle occupants and affect overall driving comfort. A typical dog clutch relies on interlocking teeth for torque transfer, and its actuation can result in NVH due to factors such as friction between mating surfaces, backlash between engagement components, teeth-on-teeth contact during synchronization, and impact forces during clutch engagement. This paper presents Stellantis’s approach to controlling the actuator system to mitigate NVH effects during clutch engagement and disengagement, focusing on strategies that enhance drivability and system refinement in electrified vehicle platforms.]]></description>
      <pubDate>Tue, 12 May 2026 09:23:09 GMT</pubDate>
      <guid>https://trid.trb.org/View/2701253</guid>
    </item>
    <item>
      <title>Efficient Multi-Parameter Optimization of a Twist Beam Rear Axle for Electric Vehicles Using TOPSIS Method for Durability</title>
      <link>https://trid.trb.org/View/2669787</link>
      <description><![CDATA[This study investigates the parameter optimization of a Rear Twist Beam (RTB) for an electric vehicle (EV) during the early stages of product development. Adapting an RTB design from an Internal Combustion Engine (ICE) vehicle platform presents several challenges, one of the challenges is accommodating increased rear vehicle load while minimizing cost, with maintaining existing rear hard points. To address this, we employed an experimental study for Computer-Aided Engineering (CAE) using the Taguchi DOE, which avoids costly physical durability tests. The key design parameters considered were the thickness and material grade of the RTB's components, specifically the cross beam, trailing arms, and reinforcements while preserving their original shapes. L8 Orthogonal array is constructed to design the experiment and identify the influence of the design parameters on durability performance, and the optimal combinations for maximizing durability are identified by using TOPSIS multi objective method. This approach offers significant cost savings by avoiding different iterative physical testing during vehicle development stage. The study found that while changes in the thickness or material of components had mere effect on the rear axle's stiffness, the thickness of the cross beam and trailing arms significantly impacted its durability under various loads.]]></description>
      <pubDate>Mon, 27 Apr 2026 15:01:13 GMT</pubDate>
      <guid>https://trid.trb.org/View/2669787</guid>
    </item>
    <item>
      <title>Stochastic assessment of residual fatigue life of railway axles considering relevant critical factors</title>
      <link>https://trid.trb.org/View/2663184</link>
      <description><![CDATA[Statistical distribution of residual fatigue life (RFL) of railway axles under given loading was computed using the Monte Carlo method by considering random variation of the selected input parameters. Experimental data for the EA4T railway axle steel, the loading spectrum, the press fit loading and the residual stress induced by surface hardening were considered in the crack propagation simulations. Usually, the material properties measured by tensile tests are considered to be the most informative source of material data. Under fatigue loading, however, the crack growth rates near the threshold are the most critical data. Two important influencing factors on these crack growth rates are presented: first, the air humidity and, second, the near-surface residual stress. The typical variation of these parameters in operation may change the RFL by one or two orders of magnitude. Experimentally obtained crack growth thresholds and residual stress profiles are highly affected by the used methodology. Therefore, the obtained input data may be located anywhere within a large scatter, while the experimenters are completely unaware of it. This can lead to dangerously non-conservative situations, e.g. when the thresholds are measured in a laboratory under humid air conditions and then applied to predictions of RFLs of axles operated in winter in low air humidity. This is significant for the topic of inspection interval optimisation. The results of experiments done on real 1:1 railway axles were close to the most frequent value found in the histogram of the numerically computed RFLs.]]></description>
      <pubDate>Fri, 24 Apr 2026 08:55:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/2663184</guid>
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