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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>Mixed-Integer Energy Management for Multi-Motor Electric Vehicles with Clutch on-Off: Finding Global Optimum Efficiently</title>
      <link>https://trid.trb.org/View/2731672</link>
      <description><![CDATA[This article introduces a novel approach to energy management in multi-motor electric vehicles, leveraging mixedinteger model predictive control (MI-MPC). First, an energy management strategy is proposed to co-optimize torque allocation and decoupling decisions, minimizing both energy consumption and frequency of clutch engagement changes. Secondly, to address computational challenge inherent in solving the resultant mixed-integer (MI) problem, a bi-level programming approach is proposed. In this approach, the torque allocation subproblem is efficiently solved at the inner level with explicit closed-form analytical solution, while the outer level optimizes clutch decisions through implicit dynamic programming (i-DP). Evaluation in a high fidelity virtual environment shows energy savings exceeding 4% compared to heuristic controllers prevalent in modern electric vehicles. The i-DP based solution process guarantees finding global optimum for the MI problem in every MPC update. The presented strategy shows an average solution time of 1 ms in a laptop, conceptually indicating its real-time potential and possible integration in multi-motor electric vehicles.]]></description>
      <pubDate>Wed, 12 Aug 2026 15:14:55 GMT</pubDate>
      <guid>https://trid.trb.org/View/2731672</guid>
    </item>
    <item>
      <title>A Novel Double Stator Consequent-Pole Transverse-Flux Motor with Trapezoidal Teeth and Permanent Magnets</title>
      <link>https://trid.trb.org/View/2735085</link>
      <description><![CDATA[As a low-speed, high-torque motor, the transverse-flux motor (TFM) holds significant potential for direct-drive applications. First, this article proposes a novel double stator consequent-pole transverse-flux motor (DSCP-TFM) to enhance torque density and motor space utilization. The DSCP-TFM features the tooth and permanent magnets (PMs) distributed on both stators and the rotor. Second, the magnetic saturation phenomenon at the tooth tips is explained using the saturation leakage-flux equivalent magnetic circuit model (SLF-EMCM). It provides a different perspective for analysis. Third, a new structure of the trapezoidal PMs and tooth is proposed. It can reduce magnetic saturation at the tooth tips, further reduce cogging torque, and flux linkage harmonics. Additionally, a 3-D finite element analysis (3D-FEA) is conducted to verify the theoretical analysis and to assess the impact of different tooth and PM shapes on motor performance. The effects of trapezoidal tooth angle and air-gap length are also evaluated. Finally, a prototype is manufactured, and experiments are conducted. The experimental results demonstrate that the DSCP-TFM exhibits higher torque output and lower harmonics in the coil flux linkage than existing TFMs, thereby validating the design and analysis.]]></description>
      <pubDate>Thu, 06 Aug 2026 09:22:23 GMT</pubDate>
      <guid>https://trid.trb.org/View/2735085</guid>
    </item>
    <item>
      <title>Quantitative Analysis of Modulation Effect of Rotor Magnetic Bridge Saturation on Electromagnetic Torque in Interior Permanent Magnet Synchronous Machines</title>
      <link>https://trid.trb.org/View/2735109</link>
      <description><![CDATA[In conventional analyses, the rotor saliency effect in interior permanent magnet (PM) synchronous motors (IPMSMs) is primarily attributed to the rotor magnetic barriers. However, the magnetic leakage from the PMs leads to magnetic bridge saturation in the rotor, which significantly distorts the air-gap flux density. This distortion resembles the virtual slotting effect and introduces an additional source of rotor saliency that is often neglected. In this article, a theoretical relationship between electromagnetic torque and tangential electromagnetic force is established, allowing the complex torque expression to be abstracted into spatial and temporal characteristics of the flux density harmonics that constitute the torque. Then, a series of analytical expressions for the tangential electromagnetic force is derived. From the perspective of the composition of spatial zeroth-order tangential force, the modulation effect of rotor magnetic bridge saturation on electromagnetic torque is quantitatively investigated. Next, based on the modulation effect, the optimization methods for IPMSM are proposed according to the load conditions. Finally, finite element (FE) and measurements are taken as verification. This study lays a foundation for the identification and mitigation of the sources of electromagnetic torque in IPMSMs for electric vehicles.]]></description>
      <pubDate>Mon, 03 Aug 2026 09:10:38 GMT</pubDate>
      <guid>https://trid.trb.org/View/2735109</guid>
    </item>
    <item>
      <title>Reinforcement Learning for Torque Vectoring in Electric Vehicles: A Review of Stability and Energy Optimization Methods</title>
      <link>https://trid.trb.org/View/2685805</link>
      <description><![CDATA[Torque vectoring can enhance dynamic stability and concurrently enable efficient energy management in electric vehicles (EVs) through optimized torque distribution. Nevertheless, conventional torque vectoring schemes often rely on fixed models and tuning, limiting their adaptability. Reinforcement learning (RL) and its model-free versions employing deep neural networks allow the development of control policies through direct interaction with the environment, making it suitable for complex and nonlinear dynamics. This paper presents a comprehensive survey of recent research on the application of RL for torque vectoring and energy optimization in EVs. An overview of conventional direct yaw control (DYC) approaches, their objectives, and common hierarchical strategies are initially studied to establish a foundation for discussing model-free RL-based torque vectoring. A description of RL in the context of stability-oriented control and energy optimization, key components, operational processes, and their classifications are studied. The primary emphasis is on RL-based torque vectoring and energy management in EVs to improve yaw stability, reduce energy consumption, and manage trade-offs under real-time constraints. Overall, RL-based controllers provide enhanced adaptability to modeling inaccuracies and facilitate more straightforward multi-objective design for simultaneous energy management and stability control, making them promising alternatives to conventional model-based methods.]]></description>
      <pubDate>Fri, 31 Jul 2026 09:23:52 GMT</pubDate>
      <guid>https://trid.trb.org/View/2685805</guid>
    </item>
    <item>
      <title>Insights into stability and control of the powerslide motion with variable drive torque distribution – applied to a driver assistance system</title>
      <link>https://trid.trb.org/View/2697848</link>
      <description><![CDATA[In this study, a theoretical investigation of the steady-state powerslide motion, or drift, is conducted to gain insight into the influence of the total drive torque and front/rear axle drive torque distribution on the powerslide dynamics of an all-wheel drive vehicle, including the case of a rear-wheel drive vehicle. The steady-state conditions and stability properties are derived, and different actuator inputs, i.e. steering angle, total drive torque and drive torque distribution, to stabilise the unstable powerslide motion are analysed and discussed with respect to different control strategies. The results indicate that the drive torque distribution is an effective control input for stabilisation and can be superior to the total drive torque input. The powerslide cannot be stabilised for particular conditions with the total drive torque input at fixed drive torque distribution. Based on these findings, a driver assistance system is presented that allows the human driver to track a desired circular path only by steering commands. The powerslide motion is stabilised automatically by a controller acting on the total drive torque and on the drive torque distribution if favourable. The characteristics, limitations in dynamics and reactions of a human driver are considered by introducing a virtual test driver model in a simulation environment. The successfully performed powerslide is shown in simulation with a basic vehicle model and in an experimental setup with a test vehicle.]]></description>
      <pubDate>Fri, 31 Jul 2026 09:23:51 GMT</pubDate>
      <guid>https://trid.trb.org/View/2697848</guid>
    </item>
    <item>
      <title>Exploring Vehicle Lateral Motion Limit: Neutral Steering Control for Dual-Motor All-Wheel-Drive Electric Vehicles</title>
      <link>https://trid.trb.org/View/2727980</link>
      <description><![CDATA[Maximizing the utilization of lateral motion limits can significantly enhance vehicle safety under extreme driving conditions. This paper presents a neutral steering chassis coordinated control scheme to extend the lateral motion limits of Dual-Motor All-Wheel-Drive Electric Vehicles (DMAWD EVs). First, an optimization model is developed using the tire friction ellipse to determine the maximum lateral force. It is demonstrated that a vehicle can fully exploit its lateral motion limits under neutral steering. Then a driving torque allocation method for the front and rear axles and a sliding mode control method for the electro-hydraulic composite anti-lock braking system are designed to fulfill the driver's driving intentions under normal driving conditions. In extreme driving conditions, a torque vectoring control strategy is proposed to coordinate the motors' driving torques and the hydraulic braking force at each wheel, while a Smith predictor-based control scheme is introduced to enhance the hydraulic braking responsiveness. Furthermore, a coordinated pitch and roll attitude controller is developed to maintain neutral steering. Finally, the proposed control scheme is verified through comprehensive testing on a Hardware-in-the-Loop platform. Results indicate that the maximum lateral acceleration increases by 18.14% under the open-loop sine steering scenario. The proposed control scheme renders DMAWD EVs to have comparable performance with four-wheel-independent-drive electric vehicles.]]></description>
      <pubDate>Mon, 27 Jul 2026 11:16:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2727980</guid>
    </item>
    <item>
      <title>Enhancing Regional Rail Efficiency and Reducing Emissions with Dual Electric Traction Machine Drivetrain</title>
      <link>https://trid.trb.org/View/2727903</link>
      <description><![CDATA[This study investigates the potential of enhancing regional rail efficiency and reducing emissions through the implementation of dual Electric Traction Machine (ETM) drivetrains. By employing two ETMs, optionally with different specifications and real-time load distribution, the research evaluates the impact on energy savings and battery longevity. The analysis is based on a comparative simulation study between single and dual ETM configurations, emphasizing energy consumption and environmental impact from both design and control perspectives. Simulation results for the Borlänge-Malung railway corridor in Sweden indicate that energy consumption can be reduced by approximately 15-20%, depending on the torque-sharing strategy and size ratio between the ETMs. The study further illustrates the operational inefficiencies inherent in single-ETM systems and highlights the performance gains of dynamic torque splitting in dual-ETM configurations. A specific control strategy is proposed: the smaller ETM is prioritized during cruising, while both machines are utilized under high-power demands such as acceleration. This approach optimizes energy usage without compromising performance, contributing to a more sustainable and cost-effective regional rail system. In terms of environmental impact, simulations based on the Swedish electricity mix show that the dual-ETM setup can reduce operational CO₂ emissions by approximately 80 tons over a 40-year service life. Moreover, improved battery utilization extends battery life, reducing manufacturing-related CO₂ emissions by an estimated 15 tons compared to the single-ETM configuration.]]></description>
      <pubDate>Mon, 27 Jul 2026 11:16:34 GMT</pubDate>
      <guid>https://trid.trb.org/View/2727903</guid>
    </item>
    <item>
      <title>A high-pole-number integral slot hub motor design: Configuration, optimization, and validation</title>
      <link>https://trid.trb.org/View/2666869</link>
      <description><![CDATA[The hub motor is an attractive propulsion source with many advantages; however, it increases the unsprung mass of vehicles, deteriorating handling performance and comfort during rides. Therefore, the mass torque density of the hub motor requires considerable improvement. In this study, a high-pole-number integral slot hub motor adopting continuous flat wire winding is designed. The design parameters are optimized by an automated design-optimization method based on a surrogate model, which can reduce the computing time. The method involves analyzing the main effect through one-factor-at-a-time (OFTA) experiments to determine the number of levels of different parameters. Subsequently, an asymmetrical design is employed for the training data to achieve a relatively high fitting accuracy with the surrogate model. Finally, the performance of the prototype machine is tested, and the rated mass torque density of the entire machine reaches 18.5 Nm/kg.]]></description>
      <pubDate>Mon, 27 Jul 2026 09:46:49 GMT</pubDate>
      <guid>https://trid.trb.org/View/2666869</guid>
    </item>
    <item>
      <title>Multi Speed – Multi Motor Torque Vectoring Control for a Commercial Electric Truck to Enhance Drivability and Performance</title>
      <link>https://trid.trb.org/View/2724705</link>
      <description><![CDATA[This paper explores the requirement of multi speed – multi motor torque vectoring in a battery electric commercial truck. The area of focus was to compare the vehicle performance and range of a BEV truck with conventional central drive single motor configuration with the same vehicle consisting of a multi speed – multi motor torque vectoring control strategy. Through this exercise, we have analysed the motor power and torque requirements to meet the vehicle performance along with the required reduction ratios. A MATLAB based vehicle model is used to simulate the effect of multi motor operation on the vehicle range. Also simulated the effect of torque vectoring control algorithm on the vehicle performance like steady state cornering (SSC), double lane change (DLC), off road drive cycle, vehicle stability and turning circle diameter (TCD).]]></description>
      <pubDate>Mon, 27 Jul 2026 09:06:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/2724705</guid>
    </item>
    <item>
      <title>Experimental Analysis of Frictional Torque from Radial Ball Bearings</title>
      <link>https://trid.trb.org/View/2579379</link>
      <description><![CDATA[In this paper a method for experimental determination of frictional torque in radial ball bearings is proposed. For this purpose, an experimental stand is designed and manufactured which allows experimental determination of the frictional torque. A mathematical model is presented which allows the determination of frictional torque in bearings, namely the torque due to liquid lubrication and the torque due to rolling. This mathematical model is processed and numerical data are obtained, by theoretical method, which are compared with those determined experimentally. The obtained results are presented and discussed in the paper.]]></description>
      <pubDate>Mon, 13 Jul 2026 10:46:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/2579379</guid>
    </item>
    <item>
      <title>Aspects of Planetary Transmissions Predesign</title>
      <link>https://trid.trb.org/View/2579372</link>
      <description><![CDATA[The paper presents some recommendations for the study of the possibilities offered by an existent kinematic scheme of a planetary transmission. First, some constructive characteristics of planetary units are obtained so that the realizable transmission ratios of the gearset to represent the best approximation of the wanted ratios for best performances. It is also presented a way to establish the magnitudes of the torques and powerflows that stress the gears, shafts, clutches and brakes.]]></description>
      <pubDate>Mon, 13 Jul 2026 10:46:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/2579372</guid>
    </item>
    <item>
      <title>Predictive modeling of BLDC motor performance in UAV systems using ensemble learning</title>
      <link>https://trid.trb.org/View/2702880</link>
      <description><![CDATA[Accurate prediction of thrust and torque is essential for optimizing the performance, energy efficiency, and control of brushless direct current (BLDC) motors in unmanned aerial vehicles (UAVs). Traditional physics-based models often struggle to capture the nonlinear relationships between motor input parameters and aerodynamic outputs, prompting the exploration of data-driven approaches. This study evaluates the predictive capabilities of six ensemble learning algorithms, including Bootstrap Aggregating (Bagging), Adaptive Boosting (AdaBoost), Gradient Boosting Machine (GBM), Extreme Gradient Boosting (XGBoost), Categorical Boosting (CatBoost), and Stacked Generalization (Stacking), in modeling thrust and torque. Experimental data were obtained using a Tyto Robotics thrust stand designed for precise static performance testing of electric propulsion systems. Among the models, CatBoost exhibited the highest accuracy in thrust prediction with a coefficient of determination of 0.9873, a root mean square error (RMSE) of 7.0506, a mean absolute error (MAE) of 6.0610, and a mean absolute percentage error (MAPE) of 2.10%. In torque prediction, AdaBoost demonstrated superior performance, achieving an R2 of 0.9713, RMSE of 0.0018, MAE of 0.0013, and MAPE of 2.60%, effectively capturing complex electromechanical dynamics. In contrast, XGBoost underperformed in thrust prediction due to hyperparameter sensitivity, while Stacking showed limited generalization in torque estimation. Bagging and GBM delivered moderate and consistent results across both outputs. The findings underscore the potential of CatBoost and AdaBoost for robust predictive modeling of UAV propulsion systems, contributing to enhanced control and system design in autonomous flight applications.]]></description>
      <pubDate>Tue, 30 Jun 2026 09:45:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2702880</guid>
    </item>
    <item>
      <title>Analytical Magnetic Circuit Modeling and Parameter Estimation of a PMSM for Spatial Harmonics and Radial Forces Characterization</title>
      <link>https://trid.trb.org/View/2717280</link>
      <description><![CDATA[This paper presents an analytical model for three-phase Permanent Magnet Synchronous Motors (PMSMs) based on Magnetic Equivalent Circuits (MECs). The approach combines a reduced magnetic network, formulated in the complex domain to simplify the mathematical development, with an offline parameter estimation procedure systematically applied for different harmonic orders. This enables the model to capture the spatial dependence of permeance variations and reproduce inductance and magnetic flux nonlinearities, while maintaining generality, physical interpretability, and computational efficiency. Numerical simulations are compared with Finite Element (FE) results to validate the model’s ability to predict current and torque harmonics and the resulting radial electromagnetic forces, demonstrating its suitability for fast Noise, Vibration, and Harshness (NVH) analysis and vibroacoustic optimization.]]></description>
      <pubDate>Tue, 30 Jun 2026 08:51:20 GMT</pubDate>
      <guid>https://trid.trb.org/View/2717280</guid>
    </item>
    <item>
      <title>Parameter optimisation of heavy-duty vehicle wet clutch based on Kriging approximation model and multi-island genetic algorithm</title>
      <link>https://trid.trb.org/View/2677530</link>
      <description><![CDATA[In the transmission system of heavy-duty vehicles, when the friction pair of the wet clutch is in the separation condition, due to the viscous effect of the oil, the relative speed difference between the friction plate and the steel disc will generate the drag torque in the clearance of the friction pair and the drag power loss in wet clutch, which will cause a decrease in the transmission efficiency of the power system and an increase in the failure rate. Therefore, the fluid model of friction pair was established with composite groove as the research object. Based on the Kriging approximation model, eight groove parameters were selected as optimisation variables, and the minimum drag torque was taken as the optimisation objective. The multi-island genetic algorithm was used to optimise the structure parameters of the friction pair groove, the results showed that the optimised friction plate effectively improved the oil circulation.]]></description>
      <pubDate>Wed, 24 Jun 2026 13:22:07 GMT</pubDate>
      <guid>https://trid.trb.org/View/2677530</guid>
    </item>
    <item>
      <title>Development of Next Generation Sustainable Electric Traction Motors</title>
      <link>https://trid.trb.org/View/2581599</link>
      <description><![CDATA[The development of traction motors with easily recyclable rare-earth permanent magnets (PMs) is studied. The primary objective is to find means and technologies that enable the reuse of the PMs without extracting their elements. Both the motor design and PM assembly need to be aligned with this target. Especially, we are focusing on metallic encapsulation of the PMs to make them strong enough to tolerate the disassembly forces. First, we discuss the design, addressing the positioning of the encapsulated PMs to balance between the mechanical and electromagnetic requirements. Second, we present the first results on the encapsulation of the PMs for intact disassembly, elaborating on the materials, manufacturing via direct energy deposition, and visual inspection of the results. We aim to contribute to the emergence of the next generation less rare-earth-element-dependent, compact, and energy-efficient electric traction motors.]]></description>
      <pubDate>Thu, 18 Jun 2026 08:54:38 GMT</pubDate>
      <guid>https://trid.trb.org/View/2581599</guid>
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