<rss version="2.0" xmlns:atom="https://www.w3.org/2005/Atom">
  <channel>
    <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>
    </image>
    <item>
      <title>Dynamic charging optimization for electric buses under photovoltaic-storage-grid energy supply mode</title>
      <link>https://trid.trb.org/View/2663714</link>
      <description><![CDATA[With the growing emphasis on sustainable transportation, the photovoltaic-storage-grid energy supply (PSG-ES) mode has been adopted in electric bus (EB) systems, showing promising performance and strong potential. However, environmental uncertainties cause random fluctuations in both solar output and energy demand, posing challenges to stable system operation. Most existing studies use static or low-frequency dynamic models based on day-ahead forecasts. These methods struggle to adapt to real-time changes, limiting the economic and environmental benefits of the PSG-ES mode. To address this issue, we propose a minute-level dynamic charging scheduling method for multi-route EB systems under the PSG-ES mode. The problem is formulated as a Markov Decision Process, with a penalty function and an action correction mechanism introduced to handle complex operational constraints. To improve learning and adaptability, we develop a deep reinforcement learning algorithm, featuring multi-head networks and composite experience replay to address distribution shifts and policy conflicts. Experiments using real-world EB data show that the proposed method effectively manages supply–demand uncertainties and generates more cost-efficient and environmentally sustainable charging plans. Compared to static scheduling with day-ahead forecasts, it reduces charging costs by 7.48% and carbon emissions by 2.99%.]]></description>
      <pubDate>Thu, 14 May 2026 17:04:32 GMT</pubDate>
      <guid>https://trid.trb.org/View/2663714</guid>
    </item>
    <item>
      <title>Resilience-based post-earthquake restoration scheduling for urban interdependent transportation-electric power network</title>
      <link>https://trid.trb.org/View/2691674</link>
      <description><![CDATA[As critical lifeline systems, transportation network (TN) and electric power network (EPN) are highly susceptible to natural hazards, such as earthquakes during their service life. At the same time, restoration of damaged TN and EPN is essential to support the post-earthquake reconstruction and emergency rescue in affected areas. Restoration strategies were traditionally developed for TN or EPN separately. However, neglecting the potential interconnection between these two networks in the recovery phase may lead to detrimental consequences, as in real-world scenarios, the obtained strategy may be less efficient or even unfeasible given that recovery of one system is usually dependent on the others for service provision. Accordingly, this paper presents a resilience-based framework for post-earthquake restoration of interdependent transportation-electric power networks. In this framework, restoration independencies and functionality dependencies are introduced to represent the interaction between TN and EPN. Then, a bi-level optimization model with the objective of maximizing seismic resilience is established to characterize the network recovery problem. Furthermore, a solution algorithm that incorporates a genetic algorithm and a chromosome validity test operator is designed to obtain the near-optimal solution. Finally, the proposed framework is illustrated through two numerical examples.]]></description>
      <pubDate>Tue, 05 May 2026 13:15:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/2691674</guid>
    </item>
    <item>
      <title>Hydrogen Energy: Technologies Offer Potential Benefits but Face Challenges to Widespread Use</title>
      <link>https://trid.trb.org/View/2697841</link>
      <description><![CDATA[Hydrogen is a versatile chemical with many potential uses, including vehicle fuel cells, aviation fuel, and power generation. For decades, interest in hydrogen energy technologies to augment or replace diesel, natural gas, and electricity has garnered billions of dollars in research and development. The U.S. could produce hydrogen in vast quantities from domestically abundant resources. However, hydrogen energy is generally more costly than alternatives and infrastructure is lacking, so whether it will replace incumbent technologies is unclear. This report examines: (1) current and emerging technologies for hydrogen production, transport, storage, and use; (2) potential benefits and challenges to developing or using these technologies; and (3) possible policy options. To conduct this technology assessment, the Government Accountability Office (GAO) searched the relevant literature; reviewed documents and reports; interviewed stakeholders from government, industry, academia, and nonprofits; conducted site visits; attended a conference; and convened a 3-day meeting of 18 experts from government agencies, industry, academia, and federally funded research and development centers. GAO is identifying policy options in this report.]]></description>
      <pubDate>Tue, 05 May 2026 10:18:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/2697841</guid>
    </item>
    <item>
      <title>Impact of electric vehicles on low-voltage distribution networks: A critical review</title>
      <link>https://trid.trb.org/View/2697198</link>
      <description><![CDATA[The integration of electric vehicles (EVs) into low-voltage power distribution networks (LVDNs) introduces a new class of mobile, high-power, and behaviorally uncertain loads. This review article systematically analyzes the existing literature to assess how EV charging affects transformer and cable loading, voltage deviation, phase unbalance, power losses, and harmonics. Unlike existing reviews that assess the impact of EVs alongside other distributed technologies, or those that focus primarily on medium-voltage networks, this paper provides a targeted synthesis of EV impacts specifically within LVDNs. The analysis shows that the types and severity of impacts are influenced by grid topology: rural networks are more prone to voltage deviations due to long feeders, urban networks face transformer overloading from dense residential demand, and suburban networks are vulnerable to both. Moreover, user-centric charging strategies, especially when applied uniformly across many EVs, can aggravate grid issues by synchronizing demand. Conversely, EVs hold significant potential as flexible grid assets, provided that local flexibility solutions and coordination mechanisms are in place. To this end, the review identifies key opportunities to strengthen research and practice, including clearer methodological reporting, standardized baseline scenarios, and more realistic modeling approaches that reflect the heterogeneity of charging behaviors and EV types. While simulation remains a powerful tool, expanding empirical validation through field studies is essential to ground findings in operational reality. Such studies can also demonstrate how improved observability in LVDNs is critical for unlocking EV flexibility and enabling proactive grid integration.]]></description>
      <pubDate>Tue, 05 May 2026 09:26:41 GMT</pubDate>
      <guid>https://trid.trb.org/View/2697198</guid>
    </item>
    <item>
      <title>Predicting the Impact of FIA 2026 Power Unit Regulations on the Performance of Formula 1 Car</title>
      <link>https://trid.trb.org/View/2691995</link>
      <description><![CDATA[This work investigates the impact of the forthcoming 2026 FIA Formula 1 power unit regulations on vehicle track performance. This new regulation introduces a rebalanced power distribution between the internal combustion engine and the Motor Generator Unit-Kinetic (MGU-K), with each unit contributing up to 350 kW. This transition nearly triples the previous 120 kW output of the MGU-K while constraining the internal combustion engine through newly imposed fuel energy limits. A full vehicle powertrain model was developed in GT-Suite following the 2026 FIA technical directives. Particular attention was given to Articles 5.4.7 to 5.4.10, which define key constraints on hybrid operation: a maximum variation of 4 MJ in battery state of charge, up to 9 MJ of recoverable energy per lap, and a peak MGU-K electrical power output of 350 kW. The model includes updated architecture specifications, active aerodynamic modules, energy deployment logic, and component-level constraints. Telemetry data from the 2024-2025 qualifying sessions was employed for model development, validation, and benchmarking, enabling performance comparisons under realistic track conditions. Analysis results reveal notable deviations in powertrain response and vehicle performance across a range of circuits, establishing a correlation between the powertrain performance and track layouts. The model enables the decomposition of overall system effects into discrete contributions from specific regulatory requirements and individual component limitations. This paper will propose a justification and scheme for developing circuit-specific strategies based on maximum energy constraint and vehicle performance.]]></description>
      <pubDate>Thu, 30 Apr 2026 16:39:45 GMT</pubDate>
      <guid>https://trid.trb.org/View/2691995</guid>
    </item>
    <item>
      <title>Energy-Efficient Train Control for Metro Considering the Power Propagation in the Traction Power Supply System</title>
      <link>https://trid.trb.org/View/2659193</link>
      <description><![CDATA[When optimizing driving strategies of metro with the target of reducing energy consumption of the substations, traditional methods require frequent power flow calculations of the traction power supply system (TPSS), which inevitably leads to a dramatic increase in computational time. In this article, we define an external power for metro based on the principle of maximizing the utilization of other trains output power during its propagation in the TPSS, which can be predicted prior to optimization. Consequently, we obtain the quasi-optimal solution to the original problem indirectly by solving the energy-efficient train control (EETC) problem considering the external power utilization. For this new EETC problem, we propose three fundamental optimal control strategies for metro and develop numerical algorithms. The results are compared with the optimal solution obtained through 3-D dynamic programming (3DDP) that directly addresses the original problem. The comparison demonstrates that while achieving comparable energy-saving performance, our proposed method can reduce computation time from hours level to seconds level.]]></description>
      <pubDate>Wed, 29 Apr 2026 16:50:11 GMT</pubDate>
      <guid>https://trid.trb.org/View/2659193</guid>
    </item>
    <item>
      <title>Well-to-Wheel Analysis of the Emissions from the Electric Buses Used in Poland and Czechia</title>
      <link>https://trid.trb.org/View/2646840</link>
      <description><![CDATA[Road transport is one of the major sources of pollution. To solve this problem, alternative fuels with a lower environmental impact are sought. Therefore, it is important to determine the impact of the life cycle of transport fuels in order to assess, which of them are more environment-friendly by taking into account the emissions generated during fuel production and vehicle operation. Electric Vehicles (EVs) are becoming increasingly popular. This article discusses a life cycle approach to the assessment of transport fuels intended for electric buses. It presents a comparative Well-To-Wheel (WTW) analysis of the emissions from the buses used in Poland and Czechia by analysing their life cycle, with particular consideration of the production of the electricity required to charge electric batteries. Furthermore, a comparative analysis of an electric bus and a conventional diesel bus has been performed. The results of the analysis are expressed as Greenhouse Gas (CHG) emission ratios across the life cycle of the buses operated in Poland and Czechia.]]></description>
      <pubDate>Mon, 27 Apr 2026 14:59:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/2646840</guid>
    </item>
    <item>
      <title>Optimizing Terminal and Vessel Selection for Shore Power Deployment: Case Study at the Port of Houston</title>
      <link>https://trid.trb.org/View/2694547</link>
      <description><![CDATA[The maritime industry has a substantial impact on the environment and public health, particularly through ship operations and port-related activities. Shore power (SP) offers a promising solution by allowing docked ships to connect to local electrical grids, thereby reducing auxiliary engine usage during hotelling. One of the key challenges to SP adoption is the substantial amount of investment required from both port authorities and ship owners or operators. In this study, an optimization framework is developed to allocate a limited budget for SP deployment at terminals and subsidies, to encourage commercial ship retrofitting to maximize the environmental and economic benefits of SP. The framework takes account of the perspectives of ship owners and operators, port authorities, and the government to reflect the interactions in their decision-making. The framework is applied to the Port of Houston, based on commercial ship hotelling activities at its public terminals in 2022. The results demonstrate that, with an annualized budget of $5.5 million, up to 50% of SP-eligible hotelling activities can be powered by SP; this can generate substantial environmental and economic benefits. Additionally, the results indicate that the cost of SP electricity to ship operators plays a critical role in balancing economic incentives between ports and ship owners in the adoption of SP. Sensitivity analysis confirms the framework’s robustness to several key environmental and economic factors and assumptions. The proposed framework can serve as a practical decision-support tool for coordinate between stakeholders and ensure that limited resources generate the greatest possible environmental and economic benefit.]]></description>
      <pubDate>Thu, 23 Apr 2026 09:10:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/2694547</guid>
    </item>
    <item>
      <title>EMR-Based Study of Simulink Technologies of Metro Power Supply System</title>
      <link>https://trid.trb.org/View/2113893</link>
      <description><![CDATA[With the development of the power supply system of metro, in particular the application of energy recovery and storage technologies, the system composition has changed significantly. However, given the lack of an effective approach for inter-system simulation in this respect, the optimal allocation of power supply can hardly be achieved. Using the method of Energetic Macroscopic Representation (EMR), the paper builds up the simulation model of energy coupling, reflecting the energy relations among vehicles, power supply systems and energy conservation systems. It then verifies the model using Simulink software. The results indicate that the model presents a valid tool for the inter-system simulation of energy transmission among the power supply systems, providing reference to the optimization of the power supply and energy conservation performances of metro.]]></description>
      <pubDate>Wed, 22 Apr 2026 16:38:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/2113893</guid>
    </item>
    <item>
      <title>Did transportation electrification help to reduce transportation sector CO₂ emissions? A study considering the dynamic electricity carbon emission factor</title>
      <link>https://trid.trb.org/View/2647717</link>
      <description><![CDATA[Transportation electrification is a key strategy for achieving carbon neutrality goals. However, the contributions of transportation electrification to carbon emissions (CRE) depend on the degree of power grid decarbonization. This study employed the Kaya Identity, the Logarithmic Mean Divisia Index (LMDI) model, and Moran's Index to examine CRE and its spatial clustering characteristics across China's seven power grid regions from 2004 to 2022, covering 30 provinces. Results indicated that the transportation electrification rate (EE) remained stable in the early years but increased gradually after 2016, reaching 12.35 % by 2022. Transportation electrification primarily impacts carbon emissions through three aspects: electricity substitution, electricity decarbonization, and energy efficiency improvement. Transportation electrification resulted in an additional 9.94 Mt of carbon emissions from 2004 to 2022, with the electricity substitution effect being the primary contributing factor. Most provinces have not achieved carbon reductions through transportation electrification. This outcome is mainly because these provinces have placed greater emphasis on the quantity of transportation electrification (rapid EE increase) rather than its quality (lagging grid decarbonization). Furthermore, regarding spatial distribution, CRE exhibits a clear pattern of “high in the north and low in the south”, indicating spatial clustering. This study provides valuable insights for advancing transportation electrification strategies.]]></description>
      <pubDate>Wed, 22 Apr 2026 16:15:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2647717</guid>
    </item>
    <item>
      <title>Two-Stage Optimal Dispatch Strategy for PV and HESS Co-Phase Traction Power Supply System Considering Prediction Uncertainty</title>
      <link>https://trid.trb.org/View/2659186</link>
      <description><![CDATA[To further improve the utilization of regenerative braking energy (RBE), perform peak shaving and valley filling for traction load, address power quality issues, and reduce carbon emissions, integrating photovoltaic (PV) and hybrid energy storage system (HESS) into the co-phase traction power supply system (TPSS) has become a key development trend for future smart railways. However, the uncertainties of traction load can impact the safe and economic dispatch of TPSS. To enhance the operational efficiency of TPSS and compensate for short-term supply-demand imbalances, a traction load ultra-short-term power prediction method and a two-stage optimization dispatch method are proposed. The latter consists of an offline stage and an online stage. The offline stage, considering HESS degradation and performing global optimization, provides a reference for the next day’s dispatch to avoid myopic decision-making. The online stage is divided into a model predictive control (MPC) process and a real-time decision. The MPC optimizes based on the predicted values and dispatch reference values, while the real-time decision adjusts the MPC outcomes based on real-time observational data and predefined rules to address the impact of prediction uncertainty. Finally, the accuracy and effectiveness of the proposed prediction method and dispatch strategy are validated using actual electrified railway data, while a StarSim hardware-in-the-loop (HIL) platform is adopted to validate its practical deployment capability.]]></description>
      <pubDate>Wed, 22 Apr 2026 14:04:05 GMT</pubDate>
      <guid>https://trid.trb.org/View/2659186</guid>
    </item>
    <item>
      <title>Enhancing the Resilience of Coupled Power Distribution and Transportation Networks Using Multiperiod Robust Dynamic Planning</title>
      <link>https://trid.trb.org/View/2659182</link>
      <description><![CDATA[To safeguard modern energy systems against the increasingly frequent extreme events, this article proposes a multiperiod planning model for the resilience enhancement of coupled power distribution networks (PDNs) and urban transportation networks (UTN). The proposed planning model determine the location and capacity expansion of electric vehicle (EV) charging stations, alongside the hardening of power lines, to effectively accommodate variable resource, demand and potential extreme events over multiple planning periods. A dynamic programming (DP) formulated multistage robust optimization (RO) model is proposed to address multiple uncertainties over the planning duration, in which the investment decisions are made sequentially by using the present-period information for adhering to non-anticipative constraints. To efficiently solve the planning model, the multistage RO problem is decomposed by a developed robust dual DP (RDDP) based method, where approximate convex hulls and Lagrangian hyperplanes are utilized to iteratively refine the cost-to-go functions until convergence. Numerical experiments conducted on both a 33-bus PDN with a 12-node UTN and a larger 54-bus PDN with a 25-node UTN demonstrate the efficacy and applicability of the proposed planning model and solution technique.]]></description>
      <pubDate>Wed, 22 Apr 2026 14:04:04 GMT</pubDate>
      <guid>https://trid.trb.org/View/2659182</guid>
    </item>
    <item>
      <title>Railway Virtual Power Plant: Synergistic Integration of Grid-Friendly Traction Power System and Markets Into a Sustainable Development Path for Green Railways</title>
      <link>https://trid.trb.org/View/2659169</link>
      <description><![CDATA[The relatively poor power quality and low capacity utilization in the existing railway traction power supply systems (TPSSs) are the pain points for the power system and railway sectors. To address this issue, this article proposes a railway virtual power plant (VPP) based on a multiphase flexibly interconnected TPSS (FITPSS) integrated with multiple photovoltaics (PVs) and energy storage systems (ESSs). First, the concept of railway VPP is introduced. Then, carbon emission reduction (CER), peak load shifting (PLS), and frequency modulation (FM) regulation modes tailored for this railway VPP are proposed, in order to effectively achieve the multifunctional demand response of an ac electrified railway to the electricity and carbon markets. To adapt to the real-time dispatching requirements of the railway VPP, a rolling scheduling approach is designed, incorporating a composite prediction error (PE) in the system and an adaptive sliding window. To achieve real-time determination of each reference power for controllable devices, the railway VPP scheduling models are developed for the optimal power flow control of the FITPSS. Finally, the effectiveness and feasibility of the proposed method are verified based on data from an actual electrified railway. A comparative assessment highlights the technical-economic advantages of the proposed strategy over literature methods.]]></description>
      <pubDate>Thu, 16 Apr 2026 13:54:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/2659169</guid>
    </item>
    <item>
      <title>Dynamic Power Flow Tracing in Urban Rail Transit Based on Circuit Theory and State Variable Method</title>
      <link>https://trid.trb.org/View/2659163</link>
      <description><![CDATA[A prerequisite for regenerative braking energy recovery in urban rail transit is to clarify how power flows between sources and loads in the system. Different from power flow calculation, which focuses on specific voltage and current values of each branch, power flow tracing emphasizes the contributions of sources to a specific load (upstream tracing) and the corresponding dual problem (downstream tracing). Considering the time-varying characteristics of urban rail transit, a dynamic current tracing approach based on circuit theory and the state variable method is proposed to describe the current distribution relationship between sources and loads. Thereafter, by applying fundamental circuit laws, the disaggregation result of current is straightforwardly extended to power tracing, and thus the power share that each source provides to each load (and the dual problem) can be determined. A rigorous mathematical proof is given for the derivation of tracing coefficients. Finally, a case study is implemented to verify the applicability of the proposed method. Through power flow tracing, the quantified and intuitive description of the current and power distribution relationship between sources and loads is demonstrated, which can provide a theoretical basis for future research on the optimal design and coordinated control of various braking energy recovery devices.]]></description>
      <pubDate>Wed, 15 Apr 2026 11:32:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/2659163</guid>
    </item>
    <item>
      <title>Novel Air System for 300 kW Heavy Duty Fuel Cell</title>
      <link>https://trid.trb.org/View/2692249</link>
      <description><![CDATA[Hydrogen fuel cell powered vehicles for heavy duty trucking are a promising path for reducing future vehicle emissions due to their reduced mass for storage and faster refueling compared to battery electric trucks. These benefits come at the cost of increased system complexity stemming from the fact that fuel cells generate electricity through a chemical reaction which must be tightly controlled. The air handling system delivers the proper amount of air (oxygen) to react with fuel (hydrogen) in the fuel cell to produce power. Air delivery requires significant power and is the largest parasitic loss for a 300 kW fuel cell. Today’s systems use an electric motor driving an air compressor to supply pressurized air to the fuel cell stack. By operating at elevated pressure levels, fuel cells can achieve higher power density, which is important for vehicle powertrains. In addition to parasitic power loss, hydrogen fuel cell systems often have reliability issues associated with the air handling system. Reliability is of significant concern for heavy duty applications (especially long-haul applications). This project aims to improve both the electrical power consumption and reliability of hydrogen fuel cell air handling systems to meet the needs of heavy duty on-highway vehicle applications. The air handling is provided by a twin vortices series (TVS) compressor in addition to adding a TVS expander to recover waste heat energy back into the compressor. The final configuration includes a 600 V, 39 kW motor connected with a single shaft to the compressor and expander. This configuration reduced the total electrical power consumption from 48.6 kW to 37 kW at full load, 13.1 kW to 9 kW at half load and 0.44 kW to 0.22 kW at idle. The response time requirement was to be less than 2 sec while the final demonstration yielded 0.62 sec. Additional design changes, including water dosing into the compressor, addition of a recuperator, and elimination of the intercooler, were made to increase the energy efficiency of the air system.]]></description>
      <pubDate>Tue, 14 Apr 2026 15:11:25 GMT</pubDate>
      <guid>https://trid.trb.org/View/2692249</guid>
    </item>
  </channel>
</rss>