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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" />
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    <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>Proposal of a Modeling Method for Vehicle Longitudinal Behavior Resulting from Clutch Engagement Based on Actual Vehicle Driving Data</title>
      <link>https://trid.trb.org/View/2630459</link>
      <description><![CDATA[This study proposes a systematic method for creating a model of vehicle behavior during driver accelerator and clutch pedal operation. The model can be used in vehicle development, especially for improving vehicle drivability. A clutch model was introduced to model the vehicle behavior resulting from clutch engagement, and the difference between the engine and transmission revolution speeds were taken into account. In addition, the position of the center of gravity of engine block was estimated. The proposed method successfully expressed vehicle behavior resulting from clutch engagement using the 7-degrees of freedom model constructed in this research.]]></description>
      <pubDate>Mon, 09 Feb 2026 08:43:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2630459</guid>
    </item>
    <item>
      <title>Model Based Design of Gear Shift Control for Twin Clutch AMT</title>
      <link>https://trid.trb.org/View/2663334</link>
      <description><![CDATA[Model Based Design (MBD) uses mathematical modelling to create, test and refine systems in simulated environment, primarily applied in control system development. This paper discusses an approach to control gear shifting using shift logic on vehicle level for twin clutch transmission using prototype controller. Twin clutch transmission is a concept with two clutches, one at input end of the transmission called primary clutch and the other at output end of the transmission called secondary clutch. This concept is proposed to counter the challenges with conventional transmission which include increased gear shift time and effort in lower gears, potential rollback of vehicle in uphill condition and chance of missed shifts. The advantages of this concept include reduced gear shift effort and improved synchronizer life with potential for reducing the size of the synchro pack. This paper proposes a methodology to develop shift logic, integrate hardware with software, flashing and calibration on vehicle using prototype controller. The shift logic is implemented using state machines in ASCET. The state machine uses vehicle speed, accelerator pedal position, gear shifter input, shift maps and current gear to determine most optimal gear shift in real-time. This control logic is then converted into c-code and integrated with hardware using INTECRIO, which is a build environment where inputs and outputs are mapped accordingly for shift actuation. In the next step, .a2l and .cod files are generated, which are flashed onto rapid prototyping hardware from ETAS using INCA. The same is used to actuate shift solenoids of transmission to change the gear. Use of rapid prototyping hardware has significantly reduced the number of iterations required for integrating software with ECU from specific supplier, thus reducing overall development time. Final vehicle level calibration is done using INCA, followed by validation process to ensure optimal performance.]]></description>
      <pubDate>Mon, 02 Feb 2026 16:36:54 GMT</pubDate>
      <guid>https://trid.trb.org/View/2663334</guid>
    </item>
    <item>
      <title>A data-driven approach to evaluate emission impacts of manual and automatic transmission vehicles</title>
      <link>https://trid.trb.org/View/2572645</link>
      <description><![CDATA[Understanding and identifying patterns in driver behavior can yield insights on how to enhance road safety and decrease vehicular emissions. This work focuses on providing a data-driven analysis of the driving behavior in an urban area, in which each one of the 30 volunteers drives both a manual and automatic transmission vehicle in a simulation experiment. Conducting experiments using a driving simulator can be more cost-effective compared to real-world testing. Different variables are collected (e.g., speed, acceleration, pedal position) and computed or estimated (e.g., vehicle-specific power), and the analysis seeks to explore the patterns in the operational and environmental performance. First results show automatic transmission driving can effectively reduce pollutant emissions, while on the other hand, it can also entail higher and sharper accelerations, more evident at lower speed operating regime.]]></description>
      <pubDate>Fri, 05 Dec 2025 17:12:08 GMT</pubDate>
      <guid>https://trid.trb.org/View/2572645</guid>
    </item>
    <item>
      <title>Development of an SSP-180 Synchronizer Durability Test</title>
      <link>https://trid.trb.org/View/2608418</link>
      <description><![CDATA[Synchronizers are designed to provide smooth, efficient and safe transfer of torque between mechanical gears. Friction level, durability, and consistency of the fluid / friction lining system are crucial to ensuring crisp gear engagements without clashing and noise, vibration and/or harshness (NVH) for the life of the transmission. Excellent wear control of gears, synchronizer ring and cone surfaces is also critical to protecting the life of moving mechanical parts. The SSP-180 synchronizer rig measures friction durability and wear up to 100,000 engagements, using a variety of fluids and friction materials. Methodology for the development of a synchronizer durability procedure using the SSP-180 rig is presented for qualifying fluids for dry dual clutch (DCT) and manual transmission (MT) applications for General Motors. It will be shown that the new DEXRON® SSP-180 Synchronizer Durability Test in Appendix C of the GMW 16612 fluid specification [1] satisfies four key conditions for new mechanical test methods: discrimination, repeatability, effective failure mode analysis, and reasonable test duration.]]></description>
      <pubDate>Tue, 14 Oct 2025 10:35:52 GMT</pubDate>
      <guid>https://trid.trb.org/View/2608418</guid>
    </item>
    <item>
      <title>Start-stop Gradeability Simulation and Methodology Development for Manual Transmission Vehicles</title>
      <link>https://trid.trb.org/View/2571644</link>
      <description><![CDATA[Grade climbing capacity establishes a vehicle's distinguishing attribute of handling uneven roads and terrains thereby enhancing its overall performance capability. Vehicle availability and the testing procedure to determine gradeability requires a lot of time and effort. Aiming for the prediction of maximum start-stop gradeability of a vehicle and reducing the testing time and resources, a methodology is established representing the test procedure. A vehicle model is developed in GT Suite having dedicated modules of engine, clutch, transmission, vehicle and a driver. The vehicle is having weight of 2999 kg and a 1499 cc of engine with 80 hp power and 210 Nm torque. In simulation, the driver targeted the engine's launching speed profile, which progressively engaged the clutch to prevent engine stalling. The target is to ascend a specified distance in a predetermined amount of time without stalling the engine. Upon reaching the maximum grade the vehicle can climb, the engine will not be able to provide enough torque to maintain required acceleration, resulting in the engine stalling. This process is repeated with different vehicle parameters for validation. The simulated results indicated the gradeability of 15.1° as compared to the measured gradeability of 15.0° on the same vehicle and intended loading configuration. This strong co-relation with delta < 1% established the confidence to explore gradeability potential with further combinations of engine torque, gear ratio, clutch and transmission. This paper explains in detail how clutch modulation time plays an important role to explore the gradeability potential further.]]></description>
      <pubDate>Tue, 08 Jul 2025 10:45:50 GMT</pubDate>
      <guid>https://trid.trb.org/View/2571644</guid>
    </item>
    <item>
      <title>Research on Shift Sound Quality Control Strategy for Active Sound Generation System in Automobile</title>
      <link>https://trid.trb.org/View/2552104</link>
      <description><![CDATA[The active sound synthesis system of electric vehicles plays an important role in improving the sound perception and transmission of working condition information inside the vehicle. Nowadays, the active sound synthesis system inside the vehicle has become standard equipment in electric vehicles of major electric vehicle manufacturers to meet the user groups' demand for driving and riding experience. In order to enrich the driving experience of electric vehicles and automatic transmission vehicles, the sound performance should be close to the immersiveness and dynamic feedback brought by traditional manual transmission fuel vehicles. Based on the active sound synthesis algorithm in the car, this paper proposes an adaptive shift sound quality control strategy suitable for complex and changeable working conditions, with the aim of simulating the real shift sound of the engine. First, the motor speed offset is accurately calculated based on the transmission ratio of each gear of the gearbox, and then fitted with the real-time motor speed to generate a highly simulated virtual speed for the sound synthesis algorithm. Secondly, linear interpolation is used to optimize the speed connection between complex and variable working conditions to ensure smooth transition of sound waves between multiple working conditions; Then, in order to improve the accuracy of system response, a constant compensation factor is introduced so that the virtual speed can sensitively follow the fluctuation of the actual motor speed, thereby achieving constant consistency of the gear shifting sound effect; Finally, the CAN signal of the actual vehicle driving condition is used as input to synthesize the shifting sound based on simulation. The conclusion shows that the shifting sound quality control strategy is suitable for multiple working conditions of electric vehicles, and can accurately and effectively simulate the acceleration sound of fuel vehicles with shifting, thus improving user experience and comfort.]]></description>
      <pubDate>Tue, 13 May 2025 10:11:05 GMT</pubDate>
      <guid>https://trid.trb.org/View/2552104</guid>
    </item>
    <item>
      <title>Global Vehicle Vibration Enhancement Using Circular Force Technology</title>
      <link>https://trid.trb.org/View/2552103</link>
      <description><![CDATA[In addition to providing safety advantages, sound and vibration are being utilized to enhance the driver experience in Battery Electric Vehicles (BEVs). There's growing interest and investment in using both interior and exterior sounds for pedestrian safety, driver awareness, and unique brand recognition. Several automakers are also using audio to simulate virtual gear shifting of automatic and manual transmissions in BEVs. According to several automotive industry articles and market research, the audio enhancements alone, without the vibration that drivers are accustomed to when operating combustion engine vehicles, are not sufficient to meet the engagement, excitement, and emotion that driving enthusiasts expect. In this paper, we introduce the use of new automotive, high-force, compact, light-weight circular force generators for providing the vibration element that is lacking in BEVs. The technology was developed originally for vibration reduction/control in aerospace applications, has been recently tested in various vehicles, and demonstrates the effectiveness for providing a real haptic feel across the entire vehicle. Shaking the vehicle globally provides a unique capability for BEVs, including Hybrid Electric Vehicles and for helping to create a smooth transition between Gas and Electric power, for example. The technology can be used to generate and emulate high-performance, high power, combustion engine feel, including idle, engine run-up/acceleration, simulated gear shifts, and Advanced Driving Assistance and Systems (ADAS) haptic indicators. The optional and customizable vibration can also mask road vibration which becomes very noticeable in otherwise smooth BEVs and can provide the perfect supplement to existing audio enhancements and gear shifting features. Additionally, the paper describes how the force generating device can be packaged in a light weight, compact, low-power manner. The technology will be compared to other force generating methods, and discuss its pros and cons.]]></description>
      <pubDate>Tue, 13 May 2025 10:11:05 GMT</pubDate>
      <guid>https://trid.trb.org/View/2552103</guid>
    </item>
    <item>
      <title>Trends in the Automated and AutomaticTransmission Systems for Two Wheeled Vehicles</title>
      <link>https://trid.trb.org/View/2547846</link>
      <description><![CDATA[The two-wheeler industry features a diverse range of transmission systems catering to varied riding preferences and market demands. Manual transmissions offer direct gear control, favored by enthusiasts for its precision and customizable performance. Automatic transmissions simplify riding, especially in urban settings, eliminating manual gear shifts and reducing rider fatigue.Understanding the dynamics of transmission systems in the two-wheeler space is crucial for manufacturers, engineers, policymakers, and riders alike. It informs product development, regulatory compliance efforts, and market positioning initiatives in an increasingly competitive and innovation-driven industry landscape.DCT (Dual Clutch Transmission) and manual transmissions represent extremes in rider engagement, automation, and cost. While DCT offers seamless gear changes and convenience at a higher price point, manual transmissions provide direct control and a tactile experience with lower initial costs. Riders weigh these factors when choosing between technological innovation and traditional engagement.Between these two extremes, certain transmissions systems provide manual gear selection with automatic clutch operation, appealing to riders seeking control without the complexities of manual clutch manipulation like the E-Clutch. Continuously Variable Transmission (CVT) systems represent a notable innovation, offering seamless gear ratio adjustments and optimized engine output across riding conditions, enhancing ride quality and rider comfort, particularly in urban environments and have gained a lot of traction in the past decade.Each transmission system presents distinct advantages and challenges, influencing rider preferences and manufacturer strategies. Understanding the dynamics of transmission systems in the two-wheeler space is crucial for manufacturers, engineers, policymakers, and riders alike. It informs product development, regulatory compliance efforts, and market positioning initiatives in an increasingly competitive and innovation-driven industry landscape.The introduction of Semi-Automated Manual Transmission (SMT) stands as a bridge, blending the precision of automated gear shifts with the visceral engagement of manual control.SMT enables clutch less gear shifts, providing riders with a unique synthesis of technological innovation and the hands-on experience enthusiasts cherish. Beyond preserving the art of manual transmission, SMT addresses challenges associated with manual gear changes, mitigating issues like gear grinding and missed shifts. Positioned at the intersection of automated efficiency and the enduring appeal of manual engagement, SMT represents a blend of conventional mechanics and modern-day power electronics.]]></description>
      <pubDate>Tue, 29 Apr 2025 15:53:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/2547846</guid>
    </item>
    <item>
      <title>Modeling and Validation of Driving Performance of Electric Vehicle Converted From Internal Combustion Engine Vehicle</title>
      <link>https://trid.trb.org/View/2511328</link>
      <description><![CDATA[The conversion of internal combustion engine (ICE) vehicles into electric vehicles (EVs) is being explored as an alternative solution for addressing environmental pollution. In this study, the authors converted an ICE vehicle equipped with manual transmissions (MTs) into an EV and developed an EV dynamics model to predict its performance. The accuracy of the model was validated through actual performance tests, including driving range, maximum velocity, and acceleration tests, which demonstrated high similarity between the predicted and observed results. Additionally, an optimization framework was developed to determine the optimal number of battery cells and connections necessary to achieve the desired mileage performance by including a gear shift schedule. Because of the lack of MTs in most new EVs, previous studies have not fully considered gear shift schedules. To the best of the authors' knowledge, this study is the first to incorporate a shift schedule into battery optimization simulations. By employing the optimization framework, the authors estimated the optimal number of batteries required for conversion to an EV that meets the target mileage and acceleration performance. This provides valuable guidelines for reducing costs and weight while satisfying customer requirements for the converted EV.]]></description>
      <pubDate>Tue, 25 Mar 2025 16:57:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/2511328</guid>
    </item>
    <item>
      <title>Dynamic characteristics analysis of gear tooth modification in a three-stage gear system</title>
      <link>https://trid.trb.org/View/2521749</link>
      <description><![CDATA[Gears serve as vital elements in high-efficiency mechanical transmissions, playing a pivotal role in vehicles. Employing gear modification has the capacity to significantly enhance the dynamic properties of the Planetary Gear Transmission (PGT) systems. In this study, the investigation has been directed toward a three-stage PGT model system with a comprehensive consideration of various vibration-related factors that affect the dynamic behavior of the system. These factors are encompassed by Time Varying Mesh Stiffness (TVMS), torsion and bending forces experienced by connecting shafts, dynamic Transmission Error (TE), impact of gear meshing eccentric load forces, inherent flexibility in the supporting shaft structure, and influence of torque and power fluctuations originating from a multi-cylinder engine. The estimation of TVMS is carried out for both external-external and external-internal teeth meshing pairs, utilizing the Potential Energy Method (PEM). Subsequently, this study employs the lumped parameter method to establish a model with a specific objective of investigating the lateral-torsional-coupling behavior within adopted PGT model system. The lateral vibration displacement characteristics of the PGT model system is deeply analyzed, revealing the influence of speed on lateral vibration and displacement frequency domain characteristics through a 3D waterfall diagram. Furthermore, a Tooth Profile Modification (TPM) method is applied utilizing two distinct parameters namely Δ TPM parameter and ϑ TPM parameter. The objective is to mitigate vibrations and evaluate the performance of the adopted PGT model after employing each TPM parameter through both TVMS and Root Mean Square (RMS).]]></description>
      <pubDate>Fri, 21 Mar 2025 09:03:38 GMT</pubDate>
      <guid>https://trid.trb.org/View/2521749</guid>
    </item>
    <item>
      <title>Improved Mode Switching and Gear Shift Control Strategy of Parallel
                    Hybrid Electric Vehicle Based on Dynamic Programming</title>
      <link>https://trid.trb.org/View/2511004</link>
      <description><![CDATA[
                
                Parallel hybrid commercial vehicles equipped with automated manual transmissions
                    are extensively utilized in the commercial vehicle sector due to their minimal
                    configuration changes, high energy efficiency, and multi-mode driving
                    capabilities. The key to enhancing the fuel economy of these vehicles lies in
                    the mode switching and gear shift control strategy. To meet the driving
                    requirements of these vehicles and optimize their fuel efficiency, this study
                    introduces a mode switching and gear shift control strategy based on dynamic
                    programming for a parallel hybrid commercial vehicle. First, dynamic programming
                    is applied to the energy management strategy of the hybrid electric vehicle to
                    determine the optimal fuel-efficient power output. Subsequently, the results
                    from dynamic programming simulations are utilized to establish the mode
                    switching boundaries and gear shift patterns. An improved mode switching and
                    gear shift control strategy is then proposed and compared with the control
                    strategy based on optimal efficiency. The findings indicate that the fuel
                    consumption per 100 km with the dynamic programming improvement strategy was
                    5.64% lower than that of the control strategy based on optimal efficiency, under
                    the conditions of the Chinese heavy-duty commercial vehicle test cycle for heavy
                    trucks. This underscores the superior fuel efficiency of the improved control
                    strategy compared with the control strategy based on optimal efficiency.
            ]]></description>
      <pubDate>Tue, 18 Feb 2025 14:55:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/2511004</guid>
    </item>
    <item>
      <title>Rolling Optimization Shift Strategy of Heavy Truck Considering Power
          Interruption in Shift Process</title>
      <link>https://trid.trb.org/View/2505872</link>
      <description><![CDATA[The optimization of gear shifting is a critical process in heavy-duty trucks for                     adjusting engine operating points, enabling a multi-objective balance between                     power, fuel efficiency, and comfort. However, this process is challenged by the                     nonlinear characteristics of engine fuel consumption, power interruptions during                     AMT (Automated Manual Transmission) shifts, and uncertainties in driving                     conditions. This study proposes a rolling optimization shift strategy for heavy                     trucks equipped with AMT, based on a multi-scale prediction of internal                     combustion engine fuel consumption on the road.Firstly, a predictive model for the energy efficiency and dynamics of heavy-duty                     trucks with AMT was developed, accounting for the engine’s engine’s operating                     condition points and power interruptions during shifting. Secondly, a future                     power demand, vehicle speed, and fuel consumption prediction algorithm was                     designed, iterating based on accelerator pedal position forecasts and dynamic                     modeling. Finally, integrating the predicted future conditions, fuel                     consumption, and road characteristics, a cloud-assisted optimal gear rolling                     optimization algorithm was established, achieving a compromise between fuel                     consumption, shift frequency, and vehicle performance.Simulation results on the GT-SUITE platform indicated that, compared with the                     rule-based shifting strategy in the ECU (Electronic Control Unit), the proposed                     method reduces fuel consumption by 2.1 % and shift frequency by 15.9 % under the                     C-WTVC. (C-WTVC refers to a driving cycle based on the World Transient Vehicle                     Cycle (WTVC) for heavy-duty commercial vehicles. It is modified by adjusting                     acceleration and deceleration to create a driving profile.) Road tests on                     heavy-duty trucks demonstrated fuel savings of 10.52 % in a 2-kilometer full                     acceleration scenario with 20%pedal, 7.26%savings with 90%pedal, and 4.32 %                     savings under free driving conditions. These results confirmed the effectiveness                     of the proposed method.]]></description>
      <pubDate>Thu, 06 Feb 2025 15:48:49 GMT</pubDate>
      <guid>https://trid.trb.org/View/2505872</guid>
    </item>
    <item>
      <title>Heavy-Duty Vehicle Transmission Benchmarking Volvo I-Shift 12-Speed Automated Manual Transmission</title>
      <link>https://trid.trb.org/View/2488139</link>
      <description><![CDATA[The objective of this project was to evaluate and characterize the Volvo I-Shift 12-speed AMT (automated manual transmission) available for use in heavy-duty vehicles produced for the North American market. The evaluation of this transmission consisted of in-gear efficiency mapping, torque converter mapping, torque converter engagement strategy characterization, oil pump testing, parasitic loss determination, shift schedule identification with laden versus unladen shift algorithm mapping, characterization of ratio spread, and packaging envelope. The transmission benchmarking efforts undertaken as part of this project sought to provide NHTSA with powertrain data that improves vehicle modeling and standard writing activities. This report details the technological advancements of the I-Shift transmission and the empirical data collected as part of the project.]]></description>
      <pubDate>Tue, 14 Jan 2025 13:43:41 GMT</pubDate>
      <guid>https://trid.trb.org/View/2488139</guid>
    </item>
    <item>
      <title>An Innovative Method to Measure Tapered Roller Bearing Preload in Manual Transmission &amp; Identification of Crucial Influencing Parameters</title>
      <link>https://trid.trb.org/View/2483015</link>
      <description><![CDATA[In manual transmission, bearing preload is a vital factor for optimum durability and performance of tapered roller bearings (TRB). To achieve better optimization of bearing preload, a precise measurement method is a minimum requisite. This technical paper investigates multiple ideas and develops a novel methodology for accurate bearing preload measurement, overcoming the challenges produced by the complexity of transmission design.This paper provides a systematic approach to bearing preload measurement in manual transmission along with identification of key parameters responsible for influencing bearing preload, such as rigidity and fit of the components. A comprehensive experimental study at both part level and system level was conducted to quantify the effects of above-mentioned parameters on preload and transmission performance. Furthermore, the paper explores the effect of bearing preload optimization on the durability performance of the transmission unit.]]></description>
      <pubDate>Mon, 30 Dec 2024 11:54:23 GMT</pubDate>
      <guid>https://trid.trb.org/View/2483015</guid>
    </item>
    <item>
      <title>A Multibody Dynamics Approach to Assess Auto Pull Behavior of Gear Shift System</title>
      <link>https://trid.trb.org/View/2483115</link>
      <description><![CDATA[Gear shift system in a gearbox is used to shift the power flow from one gear set to another gear set which enables manual transmission to maintain different torque and speed combination. Shift quality is determined by the response of the gear shift lever while changing the gears. Shift force over the entire travel event of engagement and disengagement for multiple gear sets is the key factor influencing gear shift quality. If the shift forces are higher, the effort required for shifting will also increase resulting in uncomfortable shifting. On the other hand, with lower shifting force, sudden jerk, vibration or change in vehicle condition may also cause shifting which is undesirable and may lead to safety issue. One of the important features of shift system is auto pull behavior observed while shifting. While shifting, driver starts displacing the shift lever and after threshold point the transmission itself pulls the shift lever to the end point, reducing driver effort. In the present study multibody dynamic (MBD) approach is used to evaluate auto pull behavior of gear shift system. Detailed rigid body dynamic modelling of the gear shift system along with its subsystems, power trains is developed in the virtual environment. Different geometric and non-geometric parameters affecting the auto pull behavior of shift system are studied. The results from MBD analysis are correlated with analytical calculation and validated with experimental measurement. Virtual engineering approach helps in establishing the design parameters and their optimization through use of simulation methodology even before physical prototype is built and thus reduces the prototype building and testing cost. This study can further be utilized to automate the design process as per shift system requirement.]]></description>
      <pubDate>Mon, 30 Dec 2024 11:52:59 GMT</pubDate>
      <guid>https://trid.trb.org/View/2483115</guid>
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