Technical Tracks

Track 1: Off-Road, Rail, and Marine Engine Systems

This track spotlights innovations shaping the next generation of non-road propulsion. Authors are invited to showcase breakthroughs that push performance, durability, and emissions boundaries in off-highway, rail, marine, agricultural, power-generation, mining, and other heavy-duty applications.

Topics include:

• Advanced ignition, combustion, diagnostics, and emissions-control technologies
• Prototype, field-testing, and real-world demonstrations
• Engine architectures for demanding duty cycles and sustainability goals

Track 2: Fuels, Lubricants, and Carbon Management

This track invites cutting-edge research advancing sustainable fuels, next-generation lubricants, and carbon-mitigation strategies.

Topics include:

• Alternative fuels (e-fuels, synthetic fuels, biofuels)
• Lubricant impacts on durability, friction, and efficiency
• Carbon capture, onboard conversion, and low-carbon pathways
• Life-cycle analysis (cradle-to-grave, WTW, TTW)

Track 3: Advanced Combustion, Flows, and Sprays

This track seeks papers pushing the frontier of combustion and fluid-dynamics understanding.

Topics include:

• IC engine fundamentals: thermodynamics, extreme compression, in-cylinder flows
• Advanced concepts: RCCI, GCI, LTC, dual-fuel
• Optical, laser-based, pressure-based diagnostics
• Spray physics, droplet behavior, injection strategies

Track 4: Powertrains, Hybridization, Engine Controls, and Engine Design

This track showcases innovations in integrated engine–powertrain systems.

Topics include:

• Controls modeling (combustion, subsystem, HiL, sensors)
• HiL testing, rapid prototyping, novel test rigs
• Calibration and transient control strategies
• Next-generation sensors and actuators
• Hybrid-powertrain engine design and control
• Mechanical design and thermal management

Track 5: Emissions Control

This track features advances in emissions-control science aimed at meeting aggressive global standards.

Topics include:

• Catalyst materials and system architectures
• Aftertreatment thermal management and durability
• Effects of alternative fuels
• Reductant delivery innovations
• Real-world and drive-cycle emissions

Track 6: Modeling and Simulation

This track highlights advances in numerical modeling, high-fidelity simulation, and AI-enabled frameworks.

Topics include:

• Tool and workflow development
• Multiphase, turbulence, reacting-flow modeling
• Chemical kinetics
• System-level modeling
• AI/ML for model acceleration and hybrid modeling

Track 7: Small Engine Systems

This track features developments in small-engine research for handheld equipment, recreational vehicles, and compact industrial systems.

Topics include:

• Advanced ignition, combustion, and diagnostics
• Prototype and field demonstrations
• Emissions and fuel-variability challenges

Track 8: Light-Duty Engine Systems

This track explores next-generation propulsion for passenger vehicles.

Topics include:

• Downsized/boosted SI engine advances
• Cold-start performance and emissions
• Advanced combustion, ignition, and diagnostics
• Prototype and drive-cycle demonstrations

Track 9: Medium- and Heavy-Duty On-Road Engine Systems

This track focuses on innovations for commercial-vehicle engines.

Topics include:

• Alternative-fuel-enabled engine systems
• Ultra-low NOx strategies
• Advanced combustion, diagnostics, and emissions-control
• Drive-cycle and field demonstrations

Track 1: Batteries and Light-Duty Full Electric Vehicles

This track spotlights innovations advancing battery technologies for transportation electrification. Authors are invited to showcase breakthroughs in battery chemistries, design, manufacturing, and operation that improve performance, durability, and safety. Track also explores the engineering challenges and emerging technologies enabling fully electric road light-duty vehicles, with emphasis on battery-electric propulsion systems.

Topics include:

• Advanced battery chemistries, cell and pack design, and manufacturing technologies
• Experimental and physics-based modeling modeling/AI approaches for battery degradation, diagnostics, and battery state/health management
• Experimental and physics-based modeling/AI approaches for battery thermal management, thermal runaway prevention and mitigation, and battery safety testing
• Electric Powertrain Architectures, Electric Machines and Drives, Vehicle/Powertrain-level Thermal and Energy Management, Modeling, Simulation, and Validation: Digital twins, hardware-in-the-loop (HiL) testing, and field data analysis

Track 2: Electrification of Heavy-Duty and Off-Road Vehicles

This track explores the unique engineering challenges of electrifying high-power sectors, ranging from on-highway commercial freight and transit buses to off-highway machinery in construction, agriculture, and mining. Unlike light-duty vehicles, these applications demand solutions for extreme duty cycles, thermal management, and long-term durability.

Topics include:

• Components: High-torque electric motors, power electronics, electrified pumps/valves, and advanced battery chemistries for heavy duty cycles.
• Systems & Architectures: Hybrid/fuel cell powertrains for long-haul freight, electro-hydrostatic actuators (EHAs) for implements, and energy recovery from braking or lowering.
• Thermal Systems: Cooling system and strategies for high-sustained loads, battery thermal management
• Vehicle & Fleet Integration: Megawatt charging systems (MCS), fleet recharging strategies, fleet-level TCO modeling, and grid-interaction for depots and remote sites.
• Modeling, Simulation, and Validation: Digital twins, hardware-in-the-loop (HiL) testing, and field data analysis for durability and reliability.

Track 3: Hybrid and Alternative Electric Powertrains

This track spotlights innovations advancing hybrid and alternative electric powertrains across light-duty and heavy-duty applications. Authors are invited to showcase breakthroughs and challenges in propulsion architectures, energy management, and system integration that improve efficiency, performance, durability, and sustainability in hybrid electric, plug-in hybrid, range-extended electric, and fuel-cell electric vehicles.

Topics include:

• Advanced hybrid powertrain architectures, component sizing, and system integration
• Energy-management strategies, supervisory controls, and power distribution.
• Fuel-cells, electric drives, and non-conventional electric powertrains

This track is co-sponsored by the Electrification and the Internal Combustion Engine technical communities.

Track 4: Electrification in Rail and Marine

This track explores the opportunities and engineering challenges associated with electrifying transportation beyond road vehicles, with a focus on rail and marine applications. These sectors present unique requirements in power, energy, range, weight, safety, infrastructure, and operational duty cycles. The track examines how electric propulsion, onboard energy systems, power electronics, thermal management, and system-level optimization can enable efficient and low- or zero-emission transportation across these demanding applications.

Topics include:

• Rail Electrification: Electric locomotives and multiple-unit propulsion, battery and fuel-cell trains, onboard and wayside energy storage, regenerative braking and energy recovery, traction motors and drives, catenary and third-rail systems, charging/refueling infrastructure, and energy-efficient railway operations.
• Marine Electrification: Battery-electric and fuel-cell vessels, electric and hybrid-electric propulsion architectures, integrated electric power systems, propulsion motors and drives, onboard power and energy management, thermal management, and electrification of auxiliary systems.

Track 1: Life Cycle Assessment (LCA) of Transport Modes and Components

This track focuses on the identification, assessment, and optimization of the environmental impacts of transport modes and vehicles throughout their lifecycle, from raw material extraction and manufacturing to vehicle operation and end-of-life. It covers LCA of passenger cars, medium- and heavy-duty vehicles, and other transport modes, including shipping, rail, and non-road machinery. Attention is also given to the lifecycle impacts of critical vehicle components, such as tires, brakes, batteries, and electric motors, as well as critical automotive materials and minerals. Additional topics include LCA modelling approaches, the development of lifecycle emission factors, and the methods and databases used to quantify the midpoint and endpoint environmental impacts of transport technologies. Furthermore, the track explores the application of LCA in transport emissions policies and regulatory frameworks across all transport modes.

The track welcomes papers that model, assess, and compare the environmental performance of transport technologies; explore pathways for reducing transport emissions; and identify opportunities to improve the sustainability of transport systems. Contributions addressing regulatory aspects are also welcome.

Topics include:

• LCA of passenger cars
• LCA of medium-and heavy-duty vehicles (trucks and buses)
• LCA of other transport modes (shipping, rail) and non-road machinery
• LCA of critical components (tires, brakes, batteries, electric motors)
• LCA of critical automotive materials and minerals
• LCA modelling and emission factor (EF) development
• LCA in emissions policy and regulation

Track 2: LCA of Low-Carbon Fuels and Energy Carriers

This track focuses on assessing the environmental performance of low-carbon fuels and alternative energy carriers for all transport modes throughout their lifecycle, from production and energy conversion to transportation, distribution, and use. It covers a wide range of pathways, including biofuels, e-fuels, synthetic fuels, hydrogen, methanol, ammonia, and renewable and low-carbon electricity. The track also addresses the development and application LCA methodologies, WTT modelling approaches, and emission factors for different fuel and energy pathways. It also examines the role of renewable energy, carbon capture, utilization and storage (CCUS), and emerging technologies in reducing the lifecycle greenhouse gas emissions of transport energy supply. Trade-offs involving air pollutant emissions generation from the low-carbon fuels use may also be examined.

This track welcomes contributions that characterize, evaluate, and compare conventional and alternative fuel pathways, improve the modelling and assessment of their environmental impacts, and identify opportunities to reduce emissions across energy supply chains.

Topics include:

• Low-carbon fuels (biofuels, alternative fuels, synthetic/e-fuels)
• Decarbonization of electricity generation and distribution
• Carbon capture and its role in low-carbon fuel pathways
• Well-to-Tank (WTT) modelling and emission factor (EF) development
• Trade-offs between GHG and air pollutant emissions from low-carbon fuel use

Track 1: AI/ML for Internal Combustion Engines and Powertrains

This track focuses on the application of data-driven methods, machine learning, physics-informed AI, and advanced data analytics to accelerate research, engineering workflows, and product development across ICE-related technologies, encompassing both fundamental methodology development and industrial applications.

Topics of interest include:

• Data-driven and AI-enhanced engine modeling
• Physics-informed and hybrid AI methodologies
• Simulation acceleration and surrogate modeling
• AI-enabled calibration, controls, and optimization
• Digital twins, virtual sensing, and predictive diagnostics
• Workflow automation and engineering productivity tools
• AI applications in fuel injection, sprays, combustion, aftertreatment, and engine systems
• Generative AI and intelligent engineering assistants

Track 2: AI/ML for Advanced Vehicle and Mobility Systems

This track invites work where artificial intelligence and machine learning are used to advance how vehicles and mobility systems are designed, assessed, and operated, from component models through fleet- and life-cycle-scale analysis.

Topics of interest include:

• Surrogate, reduced-order, and physics-informed data-driven models for vehicle system design and analysis
• Foundation models, LLMs, and generative methods in engineering design and analysis workflows
• AI/ML for life-cycle assessment and techno-economic analysis
• Data infrastructure, curation, and harmonization for large heterogeneous vehicle and mobility datasets
• Digital twins and AI-enabled integration of simulation with experimental and field data
• AI for fleet operations, charging, and vehicle–grid integration
• Benchmarking, uncertainty quantification, explainability, and verification of ML in engineering practice

Track 3: AI-driven Control and Energy/Health Management for HEVs/PHEVs/BEVs

This track focuses on learning-based and data-driven methods for optimal energy split, thermal coordination, and power electronics control across HEV, PHEV, and BEV architectures. Topics cover Deep Reinforcement Learning (DRL), adaptive/data-driven Model Predictive Control (MPC), stochastic speed/route prediction, and hybrid AI-physics algorithms designed to maximize powertrain efficiency, extend battery lifetime, and ensure safe, real-time vehicle execution.

Track 4: AI/ML for Vehicle Aerodynamics and Thermal Management

This track focuses on AI/ML applications for predicting and improving vehicle aerodynamic and thermal performance. Contributions are invited on advanced machine learning methods that draw on simulation, testing, or engineering knowledge to accelerate and improve vehicle development.

Topics include:

• Scientific ML and Physics AI: data-driven or physics-enhanced AI modeling of vehicle aerodynamics and heat transfer
• Data efficiency and reliability: learning from limited simulation and test data, uncertainty quantification, and robustness across diverse vehicle designs and operating conditions
• Generative AI: generative models for design studio styling, aerodynamic shapes, and underbody, underhood, or cooling-system layouts
• Agentic AI: tool use and automated workflows supporting CFD simulation, physical testing, design exploration, optimization, and cross-functional collaboration

Track 5: AI/ML for Intelligent and Connected Vehicle Systems (Co-sponsored with the Connected & Automated Systems Technical Community)

This track highlights emerging artificial intelligence and machine learning technologies that advance vehicle intelligence, connectivity, and automation. Topics include deep learning, reinforcement learning, federated learning, foundation models, generative AI, self-supervised learning, and edge AI for automotive applications. Research addressing AI-enabled prediction, adaptive vehicle intelligence, and data-driven control is encouraged. The track also welcomes contributions on explainable and trustworthy AI, model generalization, efficient onboard inference, continuous learning, and deployment of machine learning models in production vehicle systems. This track is co-sponsored by the AI and Connected & Automated Systems technical communities.

Track 1: Connected and Cooperative Vehicle Systems

This track explores advances in connected and cooperative vehicle technologies that enhance transportation efficiency, safety, and mobility through real-time information exchange and coordinated vehicle operations. Topics include vehicle-to-everything (V2X) communication, cooperative adaptive cruise control, connected infrastructure, vehicle-to-cloud integration, cooperative perception, and intelligent transportation systems. The track also welcomes research on human factors, driver trust, communication reliability, interoperability, and real-world deployment of cooperative mobility solutions. Contributions addressing connectivity-enabled applications for passenger vehicles, commercial vehicles, and mixed traffic environments are encouraged.

Track 2: Autonomous and Connected Vehicle Intelligence, Systems, and Infrastructure

This track focuses on intelligent decision-making, autonomous driving technologies, and the secure digital infrastructure enabling connected and automated vehicle operations. Topics include autonomous driving architectures, behavior prediction, motion planning, trajectory optimization, intelligent vehicle control, and decision-making under uncertainty.

The track also addresses automotive cybersecurity, secure V2X communication, cloud-edge computing, connected vehicle data platforms, privacy-preserving data sharing, and secure over-the-air communication. Contributions exploring the integration of autonomous driving intelligence with scalable, secure, and reliable connected vehicle architectures are encouraged.

Research addressing real-world deployment challenges, system interoperability, communication reliability, cybersecurity, and intelligent transportation applications is particularly welcome.

Track 3: Advanced Driver Assistance Systems and Vehicle Safety

This track addresses the development and advancement of driver assistance technologies and active safety systems designed to improve vehicle safety and driver awareness. Topics include adaptive cruise control, automatic emergency braking, collision avoidance, lane-keeping assistance, driver monitoring, human-machine interfaces, and intelligent safety interventions. The track welcomes research on driver behavior, human-machine interaction, driver assistance personalization, and safety-critical control architectures. Contributions demonstrating innovative ADAS features, integration of intelligent sensing and control, and improvements in safety, driver comfort, and system reliability across passenger and commercial vehicles are encouraged.

Track 4: Predictive Vehicle Control and Energy Optimization

This track focuses on advanced predictive control and optimization strategies that improve vehicle energy efficiency, performance, and operational sustainability. Topics include model predictive control, predictive cruise control, eco-driving, route-aware energy management, intelligent powertrain optimization, and integrated vehicle control strategies. The track also explores connectivity-enabled predictive optimization using road grade, traffic, weather, and route information. Contributions addressing multi-objective optimization of fuel consumption, energy efficiency, trip time, drivability, and powertrain performance are encouraged. Applications spanning conventional, hybrid, electrified, and heavy-duty commercial vehicles are particularly relevant.

Track 5: Vehicle Perception, Localization, and Sensor Technologies

This track explores sensing, perception, and localization technologies essential for connected and automated vehicle operation. Topics include camera, radar, LiDAR, sensor fusion, object detection and tracking, environmental understanding, simultaneous localization and mapping (SLAM), and high-definition mapping. Particular emphasis is placed on robust perception under challenging operating conditions, including adverse weather, poor lighting, sensor degradation, and complex road environments. The track welcomes advances in multimodal perception, uncertainty estimation, sensor calibration, and real-time perception algorithms. Contributions addressing the reliability, computational efficiency, and deployment of perception systems in production vehicles are encouraged.

Track 6: Intelligent Commercial Vehicles and Freight Transportation

This track focuses on emerging intelligent and connected technologies for medium- and heavy-duty commercial vehicles, freight transportation, and logistics operations. Topics include automated trucking, connected freight systems, fleet intelligence, cooperative truck platooning, intelligent transportation operations, and commercial vehicle automation. The track also welcomes research on fleet-level optimization, vehicle-to-infrastructure integration, driver assistance for commercial vehicles, and operational efficiency improvements. Contributions addressing commercial vehicle deployment challenges, regulatory considerations, system reliability, and real-world demonstrations are encouraged. Particular emphasis is placed on technologies that improve safety, productivity, sustainability, and operational performance in commercial transportation.

Track 7: Automated Driving Safety, Testing, and Validation

This track addresses methodologies, technologies, and frameworks for verifying, validating, and assuring the safety and performance of automated driving and advanced driver assistance systems. Topics include scenario-based testing, operational design domain evaluation, safety metrics, simulation-based validation, software-in-the-loop and hardware-in-the-loop testing, and physical vehicle testing. The track also welcomes research on automated test generation, digital testing platforms, regression testing, challenging operating conditions, and human-automation interaction during critical events. Contributions addressing testing data pipelines, safety assurance frameworks, regulatory requirements, and scalable validation methodologies for production deployment are encouraged.

Track 8: Predictive Thermal Management and Optimization for Connected and Automated Vehicles

This track explores advanced thermal management and optimization technologies that improve vehicle efficiency, range, reliability, and operational performance. Thermal constraints and auxiliary energy demands are increasingly important for battery-electric, hybrid, and autonomous vehicles, particularly those equipped with high-performance computing platforms and advanced sensor systems. Topics include predictive battery thermal management, route-aware battery preconditioning, intelligent cabin climate control, thermal energy storage, data-driven thermal modeling, and advanced refrigerant system optimization. The track welcomes research on connectivity-enabled thermal prediction, machine learning-based thermal control, and hierarchical model predictive control frameworks that coordinate vehicle operation, propulsion energy management, and thermal systems.

Track 9: Software-Defined Vehicles and Next-Generation E/E Architectures

This track focuses on software-defined vehicle technologies and next-generation electrical/electronic architectures that enable flexible, scalable, and continuously evolving vehicle functionality. Topics include centralized and zonal computing architectures, automotive middleware, service-oriented architectures, software platforms, over-the-air updates, and vehicle software lifecycle management. The track welcomes research on embedded computing, real-time operating systems, software virtualization, cloud-native automotive development, and hardware-software integration. Contributions addressing scalable vehicle computing platforms, software portability, functional safety, continuous integration and deployment, and emerging architectures supporting connected and automated vehicle applications are encouraged.