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    <title>Transport Research International Documentation (TRID)</title>
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    <atom:link href="https://trid.trb.org/Record/RSS?s=PHNlYXJjaD48cGFyYW1zPjxwYXJhbSBuYW1lPSJkYXRlaW4iIHZhbHVlPSJhbGwiIC8+PHBhcmFtIG5hbWU9InN1YmplY3Rsb2dpYyIgdmFsdWU9Im9yIiAvPjxwYXJhbSBuYW1lPSJ0ZXJtc2xvZ2ljIiB2YWx1ZT0ib3IiIC8+PHBhcmFtIG5hbWU9ImxvY2F0aW9uIiB2YWx1ZT0iMCIgLz48L3BhcmFtcz48ZmlsdGVycz48ZmlsdGVyIGZpZWxkPSJpbmRleHRlcm1zIiB2YWx1ZT0iJnF1b3Q7UmFpbHJvYWQgd2hlZWxzJnF1b3Q7IiBvcmlnaW5hbF92YWx1ZT0iJnF1b3Q7UmFpbHJvYWQgd2hlZWxzJnF1b3Q7IiAvPjwvZmlsdGVycz48cmFuZ2VzIC8+PHNvcnRzPjxzb3J0IGZpZWxkPSJwdWJsaXNoZWQiIG9yZGVyPSJkZXNjIiAvPjwvc29ydHM+PHBlcnNpc3RzPjxwZXJzaXN0IG5hbWU9InJhbmdldHlwZSIgdmFsdWU9InB1Ymxpc2hlZGRhdGUiIC8+PC9wZXJzaXN0cz48L3NlYXJjaD4=" rel="self" type="application/rss+xml" />
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    <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>
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      <link>https://trid.trb.org/</link>
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    <item>
      <title>Research on the generation mechanism for typical out-of-round wear of locomotive wheels based on wheel-rail slip contact</title>
      <link>https://trid.trb.org/View/2706325</link>
      <description><![CDATA[The current study aims to examine how wheel-rail slip affects the formation of typical out-of-round wear of locomotive wheels. The locomotive wheelset-track system (LWTS) was modelled using finite elements, and the friction-induced vibration (FIV) of the system under the condition of wheel-rail slip contact (WRSC) was predicted. Furthermore, the multi-body dynamics model of the locomotive vehicle-track system (LVTS) was established to simulate the fluctuation of the wheel-rail normal contact force (WRNCF) under the excitation of wheel flats. Then, wheel uneven wear was analysed and compared with the field measurements. Additionally, the effects of wheel-rail friction state, axle load, stiffness and damping of the fastener rubber pad (FRP), flat distribution, flat length and vehicle speed on wheel out-of-round wear were studied. At a locomotive speed of 70 75 km/h, the results demonstrate that the WRSC excites the unstable FIVs of 83 Hz and 122 Hz, which leads to wheel 17th 24th order polygonal wear. Wheel out-of-round wear may occur more frequently as a result of an increase in the instability tendency of the LWTS under the WRSC. The wheel-rail impact excited by the flats can lead to small peaks after the maximum peak of the WRNCF, resulting in wheel 6th 7th order polygonal wear.]]></description>
      <pubDate>Tue, 18 Aug 2026 14:11:38 GMT</pubDate>
      <guid>https://trid.trb.org/View/2706325</guid>
    </item>
    <item>
      <title>Influence of wheel hollowness and gauge widening on wheel–rail interaction and damage in heavy haul operations</title>
      <link>https://trid.trb.org/View/2691635</link>
      <description><![CDATA[Heavy haul railway operations present significant maintenance challenges, particularly accelerated wear and Rolling Contact Fatigue (RCF) of wheels and rails. Measures like tighter maintenance limits, optimized wheel–rail profiles, and advancing maintenance technologies have helped mitigate RCF on tangent tracks, large-radius curves, and high (outer) rails of small radius curves. However, these efforts have been less effective in mitigating RCF on low (inner) rails of small-radius curves. Given a fixed infrastructure design, rolling stock fleet, and optimized wheel–rail profiles, variations in operational conditions and the progressive degradation of wheels and track significantly influence wheel–rail interaction. The literature highlights that wheel hollowness and track gauge widening are the primary contributors. Therefore, this study focuses on an in-depth examination of how variations in these two factors influence wear and RCF development. A multibody dynamic model of an iron ore wagon is developed using the GENSYS software. Measured track irregularities, and rail and wheel profiles representing various degraded conditions, are incorporated into the simulations. The results reveal that wear number and RCF index trends differ significantly between the two rails (high and low rails) of a curved track, with degradation in wheels and rails. Consequently, maintenance strategies primarily designed to address high rail wear, since it is typically more severe, do not fully mitigate issues on the low rail.]]></description>
      <pubDate>Mon, 10 Aug 2026 16:51:32 GMT</pubDate>
      <guid>https://trid.trb.org/View/2691635</guid>
    </item>
    <item>
      <title>The influence of different worn wheel profiles on vehicle dynamic performance and wear under traction conditions</title>
      <link>https://trid.trb.org/View/2691047</link>
      <description><![CDATA[To investigate the impact of worn wheel profiles on wheel-rail contact and vehicle dynamic performance under traction conditions, this study tracked and tested the wheel profiles of a subway vehicle with operational mileages of 0 km, 50,000 km, 80,000 km, and 140,000 km. The influence of different worn wheel profiles on wheel-rail contact characteristics under traction conditions was then analyzed. By integrating a vehicle dynamics model, a traction and resistance calculation model, and a wheel wear and fatigue damage model, a dynamics co-simulation model was developed in SIMPACK and MATLAB. Two traction characteristics were set: both with a starting torque of 1000 N・m and respective speeds of 70 km/h and 80 km/h at the end of the constant power section. The effects of four worn wheel profiles on vehicle dynamics, wheel wear, and rolling contact fatigue (RCF) under traction conditions were thoroughly studied. The results show that as the operation mileage increases, the wheel profile changes, leading to a deterioration in the wheel-rail contact relation. This results in an upward trend in the stability index, wheel-rail lateral/vertical forces, derailment coefficient, and wheel unloading rate. Additionally, the vibration acceleration of the vehicle body and frame gradually increases. The wheel wear range expands gradually, with wear depth and area initially decreasing and then increasing, while the surface fatigue index (SFI) first rises and then falls. The 80,000 km profile emerges as the optimal choice for wheel re-profiling based on a comprehensive evaluation of dynamic performance, wear, and fatigue. This study provides a scientific basis for formulating wheel maintenance strategies.]]></description>
      <pubDate>Mon, 13 Jul 2026 10:45:19 GMT</pubDate>
      <guid>https://trid.trb.org/View/2691047</guid>
    </item>
    <item>
      <title>A review of thermal railway wheel modelling – Applicability and limitations</title>
      <link>https://trid.trb.org/View/2691046</link>
      <description><![CDATA[Finite element analysis (FEA) of heat transfer (thermal) in railway wheels is important for understanding temperature distributions that may otherwise be extremely difficult or impossible to collect while wheels are in service on rail vehicles. Obtaining the temperature field with respect to time allows the determination of the stress field which can be applied in a wide range of damage prediction modelling. To create an accurate heat transfer analysis, the thermal load, both going into and out of the wheel, must be well defined. At the same time, parameters such as wheel dimensions, analysis type and axisymmetric assumptions are important to improve accuracy and computational speed. This paper presents a review of the thermal loads used for heat transfer analysis of railway wheels, particularly during heat treatment and frictional braking. A review of past heat transfer analysis was conducted, and four key takeaways have been provided.]]></description>
      <pubDate>Mon, 13 Jul 2026 10:45:19 GMT</pubDate>
      <guid>https://trid.trb.org/View/2691046</guid>
    </item>
    <item>
      <title>The effect of wheel wear on rail rolling contact fatigue and curve negotiation performance on heavy haul lines</title>
      <link>https://trid.trb.org/View/2691037</link>
      <description><![CDATA[With the increase in train load and longer train formations, wheel-rail wear and contact fatigue issues in heavy-haul trains continuously emerge. However, the impact mechanisms of wheel wear in heavy-haul trains on rail Rolling Contact Fatigue (RCF) remain unclear. Therefore, this paper establishes a dynamic model of a C80 freight vehicle, and the advanced discrete elastic contact method is used to calculate the contact parameters. Then, the fatigue index with shakedown diagrams and damage function is used to evaluate the contact fatigue of the rail. This approach analyzes the extent of rail RCF damage under various levels of wheel wear and different wheel diameter differences (WDD), along with its lateral distribution on the rail. Finally, the paper analyzes curve resistance through a curve resistance model. The results showed that the fatigue index and damage under discrete elastic contact are larger than the equivalent elasticity. For worn wheels, the damage to both inner and outer rails increases sharply when the wear depth exceeds 2 mm. Under different WDD values, the maximum damage amount on the larger wheel side increased from 1.42 × 10⁻⁵ to 4.33 × 10⁻⁵. Wheel wear increased the probability and amount of rail RCF, with a more significant increase on the outer rail than the inner rail. The curve resistance increases with wheel wear and decreases with the increase of curve radius, with particularly significant changes between 300 m and 500 m. The findings provide a reference for train operation and the mitigation of rail fatigue.]]></description>
      <pubDate>Mon, 13 Jul 2026 10:45:19 GMT</pubDate>
      <guid>https://trid.trb.org/View/2691037</guid>
    </item>
    <item>
      <title>Wheel polygonal wear of metro vehicles caused by wheel-rail P2 force resonance</title>
      <link>https://trid.trb.org/View/2688593</link>
      <description><![CDATA[Wheel polygonal wear significantly affects vibration performance of rail vehicles. In this study, dynamic track test is carried out and dynamical modelling for a vehicle-track vertical coupling system is developed. Results show that the wheel polygonal wear of order 7-9 occurs in the measured vehicle, resulting in the forced vibration with frequencies of 50-70 Hz, which is close to the resonant frequency of wheel-rail P2 force under vehicle-track coupling conditions. The polygonal vibration of the wheel on floating slab track is caused by the wheel-rail P2 force resonance, the frequency is consistent with the wheel polygonal characteristic frequency around 60 Hz, and it is the periodic irregular rail welded joints in a line that trigger the P2 force resonance mode. This paper explores the mechanism of metro wheel polygonal wear formation in terms of vehicle-track coupling effects.]]></description>
      <pubDate>Thu, 09 Jul 2026 13:31:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2688593</guid>
    </item>
    <item>
      <title>Wheel-rail thermo-mechanical coupling characteristics of different positional vehicles in heavy-haul train under emergency braking</title>
      <link>https://trid.trb.org/View/2683126</link>
      <description><![CDATA[To investigate the effects of material temperature variation on wheel-rail contact behavior of different positional vehicles in heavy-haul trains, this study established two train-track coupling dynamic models: one incorporating wheel-rail thermo-mechanical coupling and the other ignoring thermal effects. The thermo-mechanical model accounts for material’s temperature-dependent properties and three-dimensional creepage, enabling more realistic simulation of wheel-rail interactions. Dynamic responses of locomotives and wagons under the emergency braking conditions are compared between varying cross and vertical sections. Results show that under emergency braking, higher braking force and the wheelset yaw angle lead to greater locomotive temperature rise. Wheel-rail contact temperatures of front wagon are 12.8%-16.6% higher than that of middle/rear wagons due to braking force saturation. Longitudinal creep force differences between two models drop from 8 kN (locomotive) and 2.5 kN (front wagon) to less than 1 kN with curve radius increasing, while lateral creep force differences for front wagons reach 52% due to wheelset yaw angle and braking force distribution. It is recommended to strengthen rail inspection and maintenance in sections with high traction/braking frequency and small curve radii. Prioritizing the wheel-rail materials of locomotives and front wagons will be helpful to avoid damage hazards and safety incidents caused by abnormal temperature rise. These findings provide a theoretical basis for engineering applications of thermo-mechanical dynamic models in heavy-haul trains.]]></description>
      <pubDate>Tue, 30 Jun 2026 17:02:36 GMT</pubDate>
      <guid>https://trid.trb.org/View/2683126</guid>
    </item>
    <item>
      <title>Research on abnormal flexible vibrations of intercity rail vehicle car bodies and its control based on modal force decomposition</title>
      <link>https://trid.trb.org/View/2683121</link>
      <description><![CDATA[Abnormal flexible vibrations of railway vehicle car bodies frequently occur due to lightweight design, leading to degraded ride comfort. This study systematically investigates the formation mechanism and control strategies for such abnormal flexible resonance in an intercity train, combining experimental testing and simulation modeling. Results show that first-order wheel out-of-roundness (OOR) excites the car body diamond deformation mode via frequency matching, inducing vertical-dominant resonance that impairs ride quality. A validated rigid-flexible coupled dynamics model was developed, and a modal force decomposition method and modal vibration decomposition were proposed to quantify the suspension forces’ contributions to modal excitations, revealing the resonance mechanism. To address the resonance of the diamond deformation mode of the car body, four control schemes were comparatively analyzed: optimizing air spring vertical stiffness, optimizing secondary vertical damper damping, adjusting air spring installation positions, and wheel reprofiling. Feasible measures meeting control requirements were proposed finally.]]></description>
      <pubDate>Tue, 30 Jun 2026 17:02:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2683121</guid>
    </item>
    <item>
      <title>A Fully Automated Detection System for Surface Defects of Rail Transit Wheelsets Based on Multi-Sensor Fusion</title>
      <link>https://trid.trb.org/View/2710844</link>
      <description><![CDATA[Surface defects on rail transit wheelsets directly affect train operation safety and maintenance costs. To address the issues of insufficient sensitivity of single-sensor detection and difficulties in identification under complex operating conditions, a fully automated wheelset surface defect detection system based on Multi-Sensor Fusion (MSF) is constructed. The system integrates data from a laser profile sensor, a phased array ultrasonic testing (PAUT) system, and a high-definition industrial camera. A time synchronization module aligns the multi-source heterogeneous information, and a modified Kalman filter and a convolutional neural network (CNN) are used for feature-level fusion and defect prediction. In the detection process, the laser and vision modules first rapidly identify geometric anomalies in the wheel flange and tread, then the PAUT module performs depth imaging of internal cracks, and finally, the fusion decision network outputs the defect location and type results. The experiment was conducted on a CRH380A high-speed wheelset. Compared with manual inspection and a single sensor system, the fusion system achieved a surface crack recognition rate of up to 99.1% at a detection speed of 5 m/s, with a false alarm rate reduced to 1%, and maintained a stable recognition performance of 92.8% for a minimum crack depth of 0.3 mm.]]></description>
      <pubDate>Tue, 30 Jun 2026 09:45:05 GMT</pubDate>
      <guid>https://trid.trb.org/View/2710844</guid>
    </item>
    <item>
      <title>DAS-Accelerometer Data Fusion With Semi-Supervised Graph Variational Autoencoder for In-Service Train Wheel Flat Detection</title>
      <link>https://trid.trb.org/View/2672818</link>
      <description><![CDATA[Wheel flats (WF) are a common defect in railway systems, posing risks to operational safety, passenger comfort, and the longevity of infrastructure. Existing detection methods face significant challenges, including sparse labeled data, high noise interference, and limited adaptability to complex operational conditions. To address these issues, this study introduces a semi-supervised learning workflow integrating multi-sensor data from Distributed Acoustic Sensing (DAS) and accelerometers, with a novel Graph Vector-Quantization Variational AutoEncoder (GVQVAE) as the core component. The model combines time-frequency analysis for feature extraction, a graph-based architecture for data fusion, and a vector quantization mechanism to effectively leverage both labeled and unlabeled data. Experimental results from an operational subway system demonstrate the model’s robustness and high accuracy, with an average detection accuracy of 97.08%. These findings highlight the potential of the proposed DAS-accelerometer fusion and GVQVAE model as an effective, scalable solution for enhancing WF detection in modern railway systems.]]></description>
      <pubDate>Wed, 24 Jun 2026 11:31:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/2672818</guid>
    </item>
    <item>
      <title>Analysis of the impact of wheel diameter reduction due to wheel wear on high-speed train</title>
      <link>https://trid.trb.org/View/2683169</link>
      <description><![CDATA[Wheel wear is an unavoidable consequence of high-speed train operation, and the life of a wheel depends on its maximum wear limit. The regular turning of wheels in order to counteract wear results in a progressive reduction in wheel diameter. A comprehensive understanding of the temporal pattern of wheel tread wear and the consequent changes in wheel performance following diameter reduction is fundamental to reducing the wear limit value and thereby extending wheel life. This thesis focused on the wheels of CRH3 high-speed trains, with an analysis of the distribution characteristics of tread wear over a distance of 100,000 km in service. A wheel refinement simulation model was developed to calculate and discuss the stress variation laws during the wheel diameter reduction process. Furthermore, the study investigated the change in metallographic organization and hardness on the tread surface during the diameter reduction process. The results indicate that the average tread wear over 100,000 km is around 0.25–0.4 mm, with no clear pattern of increase over the years. As the diameter of the wheel decreases, the strength factor of the wheel decreases at a significantly accelerated rate. Meanwhile, the microstructure of the tread material undergoes significant changes, with the ferrite strengthening effect essentially diminishing. This observation is confirmed by subsequent hardness tests on the tread.]]></description>
      <pubDate>Tue, 23 Jun 2026 13:53:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2683169</guid>
    </item>
    <item>
      <title>Numerical investigation of thermo-mechanical behavior of railway wheel treads under contact variation and brake-force failure during long-slope braking</title>
      <link>https://trid.trb.org/View/2680683</link>
      <description><![CDATA[This study investigates the thermal response of railway wheels under complex operating conditions, such as long downhill gradients, focusing on potential brake system failure modes. Specifically, it quantitatively analyzes how abnormal variations in brake cylinder pressure and wheel–brake shoe misalignment during steady braking amplify normal contact force, reduce contact patch area, and cause axial shifts in the contact location—ultimately affecting wheel tread temperature rise and thermal stress distribution. Based on theories of dynamics, heat transfer, and tribology, a novel modeling approach is proposed by parameterizing “contact patch area–position” into a tabular heat source. A 1/6 circumferentially symmetric indirect thermal–structural coupled finite element model of the wheel–brake system is established in ANSYS APDL. The model incorporates temperature-dependent material properties and considers convective effects during braking. Its accuracy and convergence are validated against experimental data from the literature. Key findings include: (i) When the normal force triples, the maximum tread temperature and thermal stress increase linearly, with gradients of approximately 11.7 ℃ and 17 MPa per 0.25× increment, respectively; (ii) The tread temperature displays an approximately quadratic increase with the reciprocal of the contact-area ratio, whereas the thermal stress grows in a near-exponential manner. A 25% reduction in contact area results in an average increase of 18 ℃ in temperature and 34.5 MPa in thermal stress, showing an accelerating nonlinear trend; (iii) Field-side axial shifts in the contact patch add 6.8% to temperature rise, with minimal stress impact; (iv) Under extreme coupled conditions, the wheel tread undergoes a 4.9-fold increase in peak temperature and a 7.5-fold increase in thermal stress compared to normal braking. At this stage, the material enters the elastic–plastic regime and becomes vulnerable to irreversible deformation and the development of tensile residual stress zones. This work is to couple the abnormal braking force, contact-patch area, and contact-patch position within a unified numerical framework, thereby elucidating the superposition of thermal-mechanical responses on the tread. This study offers theoretical foundations and data support for the thermal safety design and fault risk assessment of railway vehicles operating on long downhill gradients and in extreme environments such as severe cold and high altitudes.]]></description>
      <pubDate>Thu, 18 Jun 2026 08:54:59 GMT</pubDate>
      <guid>https://trid.trb.org/View/2680683</guid>
    </item>
    <item>
      <title>Development and evaluation of an optimized wheel design for tram-train wear and derailment performance</title>
      <link>https://trid.trb.org/View/2669703</link>
      <description><![CDATA[The rising demand for dual-operation vehicles capable of seamless transitions between urban tramways and heavy rail networks has intensified global interest in tram-train systems. These systems offer improved operational efficiency, reduced infrastructure costs, and enhanced passenger convenience. However, geometric disparities across rail types present a critical technical challenge. This study addresses the issue through an optimized wheel design compatible with six distinct rail configurations. A baseline wheel profile is proposed, incorporating a specialized geometry and unique rim structure to support smooth transitions at crossings and turnouts. A validated multi-physics simulation model is developed to assess dynamic performance across ten representative rail combinations. Derailment risk and wear number are defined as key quantities of interest (QoIs) and analyzed across three rail categories. Six geometric parameters, selected from a practical design perspective, are evaluated, with three screened out via the Morris sensitivity method. Based on algorithmic benchmarking, the Elliptical Basis Function (EBF) is selected to construct a surrogate model. The resulting meta-model captures multidimensional sensitivities and supports iterative optimization to yield optimal wheel profiles for each QoI. Beyond simulation—including dynamic response and cumulative wear prediction—full-scale experiments are performed on a newly constructed tram-train testbed featuring a dedicated transition lane. The optimized designs demonstrate superior dynamic stability, reduced wear, and decreased derailment risk, with good agreement between numerical and experimental results. This study contributes to the advancement of hybrid rail transit by integrating surrogate-based optimization with comprehensive computational and experimental validation, laying a foundation for safer, more efficient tram-train operations.]]></description>
      <pubDate>Tue, 26 May 2026 09:41:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/2669703</guid>
    </item>
    <item>
      <title>PDC-SWM-LPF: A novel feature extraction method for on-board detection of wheel polygonal wear</title>
      <link>https://trid.trb.org/View/2669699</link>
      <description><![CDATA[Wheel polygonal wear often leads to a decrease in vehicle ride comfort, causes fractures in vehicle components, and can result in serious accidents. Therefore, monitoring the fault state of polygonal wheel in real time is particularly important. Currently, quantitative analysis of polygonal wheels mainly adopts a big data-driven approach. However, in practical engineering scenarios, there is not always an abundance of data, posing challenges for the amplitude recognition of polygonal wheels. This paper employs an Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN) to determine the order of polygonal wheel wear. On this basis, a feature extraction method (SWM-LPF) for the probability density curve (PDC) vibration acceleration of axle box was proposed, enabling the generalized regression neural network (GRNN) to predict the amplitude of polygonal wheel with limited sample support. In ablation experiments, Residual Neural Network (ResNet) and 1D-CNN were used as the baseline models. The experiments show that using only 16.7% of the training samples required by the baseline models, SWM-LPF enabled GRNN to achieve comparable accuracy in estimating the amplitude of polygonal wheel. With the assistance of SWM-LPF, the iteration rounds of ResNet and 1D-CNN were reduced by 80%, significantly improving the accuracy of amplitude detection for polygonal wheel.]]></description>
      <pubDate>Tue, 26 May 2026 09:41:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/2669699</guid>
    </item>
    <item>
      <title>Multi-parameter optimization based on a surrogate model for improving vehicle dynamics and reducing wheel wear in high-speed EMUs</title>
      <link>https://trid.trb.org/View/2659285</link>
      <description><![CDATA[With the continuous development of China's high-speed railways, the problems of vehicle dynamics and wheel wear in high-speed electric multiple units (EMUs) are becoming increasingly prominent, and the suspension parameters of these vehicles have a significant effect on improving vehicle dynamics performance and reducing wheel wear. This paper first establishes a vehicle dynamics model using the Ultra-Latin Hypercube sampling method to select suspension parameters, and targets the improvement of vehicle dynamics performance and the reduction of wheel wear, and finally a Kriging Surrogate Model-Compression Particle Swarm Optimization (KSM-CPSO) model used to optimise the suspension parameters. The vehicle dynamics and wheel wear of the before and after optimisation are analysed. The results showed that the use of optimised suspension parameters effectively increased the vehicle's critical speed. The optimised parameters further improved the vehicle's ride index, safety index, and reduced the lateral force of the wheel axle. In addition, the optimised parameters suppressed the lateral vibration of the vehicle. When the wear mileage reached 200,000 km, the wheel wear depths before and after optimisation were 1.086 and 0.9806 mm, respectively. Therefore, the optimisation of the suspension parameters can effectively improve the vehicle dynamics performance and subsequently reduce wheel wear.]]></description>
      <pubDate>Tue, 14 Apr 2026 10:11:23 GMT</pubDate>
      <guid>https://trid.trb.org/View/2659285</guid>
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