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CONNECTOR RECEPTACLE, BAYONET COUPLING, IN LINEAS95234/1A (Current)To be published on 06/01/2103
AE-8C1 Connectors Committee
Characterisation of Brake Wear PM2.5 and PN10 Emissions Across Pad/Disc Technologies, Vehicle Types and Braking Behaviours, Under Real World Conditions2026-24-0022To be published on 09/21/2026
This paper summarises targeted brake emissions investigations undertaken as part of the Department for Transport’s Non Exhaust Emissions programme. The work was carried out to improve understanding of particulate mass and particle number emissions from friction braking and to assess the influence of component selection, vehicle technology, operating conditions, and control measures on those emissions. Starting from a pre-developed brake enclosure and sampling system methodology, these were further refined to improve airflow management, reduce leakage, and minimise sampling artefacts. The updated system was integrated with a suite of particulate measurement instruments, including MPEC (hot and cold), APC10, DMS500, and eFilter, enabling simultaneous measurement of volatile and non volatile PN10 plus PM2.5. A matrix of nine brake pad formulations and two disc types was tested on a common C segment vehicle platform across chassis dyno and on road cycles, together with controlled braking
Andersson, Jon
Simulation-based comparison of powertrain layouts for light commercial vehicle application2026-24-0032To be published on 09/21/2026
The transition towards cleaner solutions in the mobility and transport sector calls for new powertrain configurations. Besides the passenger vehicle segment, this also applies for the transportation of goods in road traffic. The most popular options are the electrification of vehicles and the utilization of renewable fuels. Hybrid powertrain configurations which allow the combination of the two solutions are also discussed. This paper focusses on light commercial vehicles (LCV) which can be used in a variety of transportation applications. Besides the reduction of CO2 emissions, other requirements apply for a powertrain for this type of vehicle. To ensure cost efficient transportation of goods overall weight of the powertrain should not negatively affect the maximum payload of the vehicle. Time-consuming refueling processes should be kept at a minimum to enable a high uptime. Therefore, optimized solutions must always represent a compromise between those constraints. To give an
Weimer, Niko, Knaup, Lars, Lavall, Philipp, Beidl, Christian, Rass, Florian, Barth, Sebastian
Tailoring ICEs towards future global market requirements – Multi-Fuel Capability to ensure next decade market success2026-24-0030To be published on 09/21/2026
The entire mobility industry is actually according to the Paris agreement and the corresponding initiatives facing enormous regulatory demands to eliminate the business sector-related GHG emissions. A major focus is hereby set on wide-spread electrification of all kinds of applications, but from current perspective it is obvious that a quick and complete shift is highly unlikely, especially with view a heavy and challenging industrial and commercial applications. In line with this, it’s apparent, that ICEs maintain to play an important role in the overall propulsion system line-up. For compliance with the engaged CO2 reduction policies and efficiency improvement demands, a fast and broad replacement of fossil fuels needs to be realized. Due to the specific properties of carbon-neutral fuels and as well the variety of the range of industrial applications, different types of alternative fuels are considered, subdivided in preferred solutions for smaller or on-highway applications vs
Koerfer, Thomas
Structural Robustness and Regime-Dependent Uncertainty in a Reduced-Order Physics Model for Vehicle Fuel Consumption Using Monte Carlo Analysis2026-24-0015To be published on 09/21/2026
Accurate prediction of vehicle fuel consumption typically relies either on simplified empirical correlations or on high-fidelity simulations that are computationally expensive. However, the structural robustness of reduced-order physics-based models under parametric uncertainty has not been systematically quantified. In particular, the interaction between model simplifications and uncertainty in vehicle and fuel properties across different operating regimes remains insufficiently investigated. This study presents a reduced-order physics-based framework derived from fundamental force and energy balances to estimate fuel consumption in L/100 km. The model includes aerodynamic drag, rolling resistance, inertial effects, drivetrain efficiency, and fuel lower heating value. Unlike purely empirical formulations, the proposed structure preserves physical interpretability while remaining computationally efficient. Monte Carlo simulations are employed to propagate simultaneous uncertainties in
Gutierrez, Marcos, Taco, Diana
Global–Regional Energy Balance Climate Modeling Framework for Country-Level Temperature Projections Based on CO₂ Radiative Forcing2026-24-0021To be published on 09/21/2026
This study presents a computational framework for estimating country-level temperature projections based on global radiative forcing from CO₂ emissions. The methodology integrates a carbon-cycle accumulation module, a logarithmic radiative forcing formulation, and a dynamic one-box energy balance model (EBM) to simulate global mean temperature evolution. Atmospheric CO₂ concentration is computed from cumulative global emissions using an airborne fraction parameter. Radiative forcing is then determined using the established logarithmic relationship between concentration and forcing. The global temperature response is calculated dynamically by solving the transient energy balance equation, incorporating effective heat capacity and climate sensitivity parameters. To regionalize projections without relying on high-resolution General Circulation Models (GCMs), an empirical regional amplification factor is introduced. This coefficient is derived from historical regression between observed
Gutierrez, Marcos, Taco, Diana, Sampietro-Saquicela, Jose, Bermudez-Herrera, Leandro
Adaptive Neural Network Fuel Mass Correction for Structural Model Error Compensation in Diesel Engines with Variable Biodiesel Properties2026-24-0023To be published on 09/21/2026
Compression-ignition engines operating with biodiesel blends often exhibit variability in fuel properties, such as density, viscosity, and cetane number, which can lead to systematic deviations in injected fuel mass when using conventional physics-based models. These deviations can reduce combustion efficiency and increase brake-specific fuel consumption (BSFC). This study proposes a lightweight neural network–based approach to compensate for structural errors in baseline injection models, using a single-layer perceptron trained on the relative error (delta) between actual and modeled injected mass. By normalizing engine and fuel parameters and introducing a small amount of measurement noise, the network learns to predict a corrective factor that adapts the injected mass to match the desired target under varying fuel conditions. Simulation results demonstrate that the neural correction significantly reduces systematic bias: in test cases with intentionally introduced structural error
Gutierrez, Marcos, Taco, Diana, Sampietro-Saquicela, Jose, Bermudez-Herrera, Leandro
Electrical waveform analysis of spark discharge for monitoring conditions inside prototype prechambers2026-24-0013To be published on 09/21/2026
Using renewable fuels like hydrogen in internal combustion engines requires new combustion strategies and ignition systems like pre-chamber sparkplugs. This necessitates novel measurement and monitoring techniques to gain insights into the phenomena arising from the use of new fuels and components. For understanding the phenomenon of pre-chamber ignition, it is important to observe how sparks behave inside them. The spark-elongation under certain conditions inside a particular pre-chamber, its location at a given time during discharge, and the flow conditions during spark discharge are all significant factors in gaining insight into this phenomenon. However, such information is difficult to obtain from inside a pre-chamber due to the difficulty of gaining optical access. In such cases, the electrical waveform analysis could prove useful. During this study, the electrical parameters are used to calculate the spark length, providing information about the igniting volume inside a pre
Kottakalam, Saraschandran, Nenzel, Markus, Rottenkolber, Gregor
Thermal Effects and Combustion Behaviour of Hydrogen and Natural Gas in a Heavy-Duty Gas Engine2026-24-0003To be published on 09/21/2026
To accelerate the usage of renewable fuels in the heavy-duty transportation sector, a conventional diesel heavy-duty engine was retrofitted for gaseous fuel operation. The aim of this approach was to support the transition from diesel to renewable energy carriers while maximizing the reuse of existing engines in the field. A direct conversion from liquid to gaseous fuel usage does not guarantee stable or efficient engine operation. Gaseous fuels require an external ignition source to initiate combustion. Hydrogen exhibits a low minimum ignition energy and a wide flammability range in air. These characteristics lead to high demands on combustion development. In spark-ignited internal combustion engines, port fuel injection (PFI) is widely used due to its simpler system integration and lower fuel pressure level compared to direct injection (DI). PFI is associated with several inherent disadvantages, including lower volumetric efficiency and an increased sensitivity to abnormal combustion
Rößlhuemer, Raphael, Fitz, Patrick, Fellner, Felix, Prager, Maximilian, Jaensch, Malte
Data-Driven System Dynamics and Chauvenet-Based Outlier Detection for Assessing Global CO₂ Emissions under Fossil Energy and Electric Vehicle Transition Scenarios2026-24-0020To be published on 09/21/2026
Understanding the structural drivers of global CO₂ emissions requires integrated analysis of fossil fuel production, total energy consumption, and electric vehicle (EV) deployment trends. This study presents a data-driven modeling framework combining system-dynamics formulation with statistical outlier detection implemented in Python to evaluate emission trajectories over a ten-year historical period. The methodology incorporates historical datasets of global CO₂ emissions, primary energy consumption, fossil fuel production, and EV manufacturing volumes. A computational routine developed in Python applies the criterion proposed by William Chauvenet to identify statistically inconsistent observations within the dataset, ensuring robustness prior to regression and correlation analyses. Carbon intensity (CO₂ per unit of energy) is calculated to assess decoupling behavior, while correlation matrices and elasticity indicators quantify the relative influence of fossil production and EV
Gutierrez, Marcos, Taco, Diana, Bermudez-Herrera, Leandro
Cost and Emission aware strategic optimization: a fleet-level tool to support scenario-oriented design2026-24-0034To be published on 09/21/2026
The transition toward low-emission transport systems requires not only technologically optimized Battery Electric Vehicles (BEVs) but also integrated methodologies capable of supporting industrial stakeholders throughout the deployment phase. In particular, for logistics operators, fleet sizing and charging infrastructure planning are tightly coupled with vehicle configuration and mission scheduling. Therefore, decision-support tools are required to minimize total operational costs and environmental impact while ensuring service continuity. Building upon a previously developed two-level BEV design framework, this work introduces a higher-level optimization tool aimed at extending powertrain design outcomes toward fleet-level decision-making, providing an integrated methodology capable of determining not only the optimal vehicle configuration but also the optimal number of vehicles and charging stations required to satisfy operational scheduling constraints. The proposed tool performs
Bartolucci, Lorenzo, Cennamo, Edoardo, Cordiner, Stefano, Donnini, Marco, Grattarola, Federico, Lombardi, Simone, Mulone, Vincenzo, Tribioli, Laura
Business approach to cope with automotive market uncertainty2026-24-0024To be published on 09/21/2026
The global automotive industry is facing an unprecedented convergence of uncertainties driven by geopolitical tensions, evolving trade policies, emissions related regulations, and increasingly volatile consumer demand. Shifting emissions legislation, including the EU’s tightened CO2 targets and long term plans to phase out internal combustion engines, is imposing strategic and financial pressures on automakers and suppliers as they navigate divergent regional regulatory trajectories. Demand side volatility further complicates the landscape. Consumer preferences are fluctuating due to economic pressures, infrastructure constraints, and uneven EV adoption patterns. While some markets show stagnation in battery electric vehicle uptake, hybrids are rising as consumers seek cost efficient alternatives amid uncertain energy and regulatory environments. Within this unstable context, the transition toward Software Defined Vehicles (SDVs) is emerging as a critical strategic response. SDVs
Cavanna, Filippo, Potenza, Luca
Computational Electro-Thermal and Degradation Modeling Framework for Lithium-Ion Batteries in Electric Vehicles2026-24-0011To be published on 09/21/2026
This paper presents a mathematical modeling framework for lithium-ion batteries used in electric vehicles (EVs). The model is implemented using Python. At the cell level, the model describes charge and discharge behavior, state of charge (SOC), terminal voltage, internal resistance losses, and heat generation. An energy balance equation is used to estimate temperature variation during operation. Temperature-dependent resistance and capacity are included to represent nonlinear battery behavior under different load conditions. At the system level, feedback relationships between SOC, temperature, state of health (SOH), and degradation rate are modeled using system dynamics. Battery aging is represented through mathematical functions that relate capacity loss to temperature and usage cycles. This allows simulation of long-term performance under different driving scenarios. The model enables parametric and sensitivity analyses to evaluate the effects of discharge rate, ambient temperature
Gutierrez, Marcos, Taco, Diana
A computational study of high efficiency Wankel rotary engines using a passive pre-chamber2026-24-0001To be published on 09/21/2026
Wankel rotary engines are renowned as compact machines with high power-to-weight ratios, which make them suitable for use as range extenders for battery electric vehicles or as propulsion systems for unmanned aerial vehicles. However, their overall efficiency and emissions still need significant improvement to make them compliant to make them stringent regulations and comparable with classical reciprocating 4-stroke engines. With the aim of improving these shortcomings, this work focuses on the application of a passive pre-chamber in order to enhance the combustion phase and the overall efficiency and emissions of such engines. The study was conducted using CFD methods by implementing numerical models of the commercial AIE 225CS rotary engine in CONVERGE, configured with port fuel injection and fully-premixed gasoline combustion. The engine was extensively tested in a previous project while different CFD models were validated against experimental data in previous studies by the same
Vorraro, Giovanni, Im, Hong G., Turner, James
System Dynamics Modeling of Global Electric Vehicle Adoption Using Vensim: Market Transition Time Toward a Single-Dominant Transport Technology2026-24-0017To be published on 09/21/2026
This study presents a system dynamics framework to estimate the transition time required for electric vehicles (EVs) to become the dominant and potentially unique global transportation technology. The model is developed in Vensim and structurally inspired by the classical system dynamics archetypes Growth of a Field, Capacity and Market Growth, and Competitive Dynamics. These reference structures are integrated into a unified dynamic model that captures technological diffusion, production capacity expansion, infrastructure deployment, cost reduction through learning effects, and competition with internal combustion engine (ICE) vehicles. The proposed model represents EV and ICE fleets as interacting stocks, with feedback loops describing market attractiveness, charging infrastructure growth, battery cost decline, policy incentives, and phase-out pressures on conventional vehicles. Nonlinear reinforcing and balancing feedback mechanisms are used to simulate tipping points and saturation
Gutierrez, Marcos, Taco, Diana, Sampietro-Saquicela, Jose, Ulloa de Souza, Raul
EKF-Based Machine Learning Approach for Battery SOH Prediction in Commercial Vehicles Fleet2026-24-0002To be published on 09/21/2026
Estimating battery State of Health (SOH) from field data is essential to ensure successful operation and to increase the uptime of battery electric vehicles (BEVs). Most studies in the literature have proposed several methods for battery SOH estimation, relying on datasets acquired under controlled laboratory conditions. However, SOH estimation becomes significantly more challenging when dealing with real-world driving data due to the increased variability and complexity of operating conditions. In this work, CAN telematics data, sampled at 1 Hz, have been collected across approximately 16 months of operation from 10 electric commercial vehicles. During this period, a battery degradation of up to 2.5 - 3% is observed within the fleet. Firstly, a model-based framework is introduced, in which a battery second-order Equivalent Circuit Model (ECM) has been coupled with an Extended Kalman Filter (EKF) to estimate the battery SOH. The results confirmed that the EKF accurately captures the
D'Agostino, Valerio, Pulvirenti, Luca, Shanker, Anirudh, Cardone, Massimo, Rizzoni, Giorgio, Vitale, Francesco
How micromobility is reshaping urban mobility: a systematic literature review2026-24-0025To be published on 09/21/2026
Micromobility is rapidly reshaping urban mobility by transforming travel behaviour, urban space, and transport systems. Its growing role in reducing car dependency and supporting low-carbon mobility has positioned cycling, e-scooters, and e-bikes as key components of sustainable urban transport. The aim of the study is to investigate how micromobility is reshaping urban mobility, particularly travel behaviour, urban mobility policy, urban infrastructure, and public transport integration. This study employs a systematic literature review (SLR) to provide a structured and transparent framework for synthesising existing research, identifying trends, and mapping knowledge gaps across multiple dimensions of urban mobility[MO1.1]. It combines inductive and deductive reasoning to ensure the review is both theoretically grounded and responsive to emerging patterns in the literature. The findings reveal that the most impactful areas of micromobility development are demand and changes in travel
Olkhova, Mariia, Comi, Antonio
A bicriteria mathematical programming model for strategic road freight fleet renewal under environmental and economic objectives2026-24-0033To be published on 09/21/2026
Road transport is a major contributor to freight-related greenhouse gas emissions, and its relevance for efforts to decarbonize the transport sector as a whole is increasing. It is by now agreed that decarbonization of road freight will ultimately hinge on a transition away from oil-based fuels, mainly diesel and gasoline, which continue to dominate the sector. However, alternatives to oil span a multitude of technologies, ranging from electricity to biofuels, and entail varying levels and forms of investment. To support the development of informed decarbonization strategies in this context, we describe a bicriteria mathematical programming model for optimizing vehicle replacement decisions in a fleet of trucks to be operated over several years. Given a specification of the initial fleet, the model generates a set of renewal strategies that achieve different tradeoffs between aggregate well-to-wheel emissions and total investment and operation costs. The model captures heterogeneity
Mifrani, Anas, MICHEL, Pierre, Mendes Alves, Breno, Chasse, Alexandre
From Crowdshipper Behavior to Urban Mobility Governance: Policy Insights for Sustainable Crowdshipping2026-24-0029To be published on 09/21/2026
Crowdshipping has recently attracted significant attention as a potentially sustainable solution for urban logistics, as it leverages individuals’ underutilized travel capacity to perform last-mile deliveries. While existing research has extensively examined crowdshipper participation through behavioral models, empirical adoption studies, and systematic literature reviews, considerably less attention has been devoted to the governance and policy implications emerging from crowdshipper behavior. This represents a critical gap, particularly in the context of sustainable urban mobility, where logistics innovations are often implicitly assumed to generate positive externalities without adequate regulatory design. This paper aims to address this gap by translating crowdshipper behavioral evidence into policy-relevant insights for sustainable urban mobility planning. The analysis is based on data collected through a structured questionnaire survey administered to potential and active
Comi, Antonio, Idone, Ippolita
Neural-Network-Enhanced Air-Standard Thermodynamic Modeling for Spark-Ignition Engines Fueled with Low Heating Value Alternatives2026-24-0016To be published on 09/21/2026
This study presents a computational framework that integrates an air-standard thermodynamic engine model with artificial neural networks to predict the performance of spark-ignition (SI) engines operating with alternative fuels of reduced lower heating value (LHV). A deterministic thermodynamic simulator was developed in Excel, incorporating engine geometric parameters (compression ratio, bore, stroke, displacement), operating speed, and fuel properties, with particular emphasis on LHV as the dominant energetic descriptor. The model computes in-cylinder states, thermal efficiency, indicated mean effective pressure, and power output under idealized air-standard assumptions. To extend predictive capability beyond fixed-parameter analyses, a feedforward neural network was trained using datasets generated from systematic parametric sweeps of engine geometry, speed, and fuel LHV. The neural network captures nonlinear interactions between compression ratio, combustion energy release, and
Gutierrez, Marcos, Taco, Diana, Sampietro-Saquicela, Jose, Valencia-Ortiz, Nakira
Real-Time Road Intelligence through a Hazard Authentication Model2026-24-0027To be published on 09/21/2026
Advanced Driver Assistance Systems (ADAS) are evolving beyond onboard perception. The ability to dynamically map and share temporary road hazards is important for connected and autonomous driving, but authenticating the data is critical. An in-vehicle hazard recognition layer performs real-time video analysis and geotagging on embedded platforms. Real-time video is analyzed for road hazards—such as potholes, construction zones, waterlogging, fallen trees, roadside accidents, and debris—using onboard cameras and lightweight computer vision models. This metadata is sent to a cloud-based aggregation layer to validate hazard reports. It is of paramount importance to validate hazard reports originating from diverse sources, regardless of their accuracy. This paper presents a mathematical approach to determine an overall Hazard Confidence Score (HCS) based on data received from diverse sources. A unique hazard authentication model is introduced to quantify the credibility of each hazard
Bose, Souvik
Fuel Cell Electric Vehicle-to-Home Strategy for Residential Power Supply Continuity and Load Management2026-24-0026To be published on 09/21/2026
Power supply continuity for household appliances during high-demand peaks or periods of low solar generation remains a critical challenge for modern residential energy systems. Hydrogen-powered Fuel Cell Electric Vehicles (FCEVs) offer a compelling solution by extending their role from sustainable mobility to versatile mobile energy storage units. This study investigates the Vehicle-to-Home (V2H) operation of a high-performance fuel cell vehicle designed to provide backup power and peak-shaving capabilities in a domestic environment during high-demand or grid overload conditions. To evaluate this integration, a comprehensive MATLAB/Simulink simulation model was developed for a residential microgrid. The system comprises a photovoltaic array, a parallel battery energy storage system, and a Fuel Cell Electric Vehicle modeled according to the technical specifications of the Toyota Mirai, equipped with a high-efficiency 128 kW fuel cell stack (330 cells) and a dedicated 5.6 kg hydrogen
Federici, Leonardo, Pistritto, Antonino, Cozzolino, Raffaello
Life Cycle Assessment of Greenhouse Gas Emissions from a Plug-in Hybrid Electric Vehicle with Different Powertrain Configurations in Europe2026-24-0019To be published on 09/21/2026
Plug in hybrid electric vehicles play an important role in transportation decarbonization. Compared with battery electric vehicles, plug in hybrid electric vehicles generally have a lower production carbon footprint due to their smaller batteries, which require far less raw material. Despite their smaller capacity, these batteries are typically sufficient to cover most daily travel distances in pure electric mode. The hybrid powertrain can be configured in multiple ways depending on the number and position of electric machines within the driveline. These configuration differences significantly influence both the total carbon footprint and the use phase greenhouse gas emissions. In this study, we evaluate the life cycle greenhouse gas emissions of a plug-in hybrid electric vehicle with various powertrain configurations in the European context. All configurations share the same premium mid-size sport utility vehicle glider. Battery capacity ranges from 20 kWh to 45 kWh, enabling an
Nguyen, Duc-Khanh, Andersson, Simon, Kristoffersson, Annika
Experimental Comparison Between Real and Simulated Battery Pack Efficiency in Light Quadricycles Using a Custom Inertia Dynamometer2026-24-0008To be published on 09/21/2026
This study compares the energy efficiency of a real battery pack with that of a simulated battery pack using a hardware battery simulator, through experimental testing on a dedicated inertia dynamometer designed for light quadricycles. The real battery pack under investigation consists of lithium-ion cells with a nominal voltage of 48 V, a nominal capacity of 100 Ah, and a total energy content of 4.8 kWh. The pack is equipped with a Battery Management System (BMS) that monitors voltage, current, temperature, and State of Charge (SOC). The battery simulator was configured to replicate the same electrical specifications, including the OCV–SOC curve, internal resistance, and current limits, enabling a direct comparison between theoretical and experimental behavior. Experimental tests were conducted on a custom inertia test bench developed to overcome the limitations of conventional chassis dynamometers when testing light quadricycles, characterized by low mass, limited power output, and
Sementa, Paolo, Vaglieco, Bianca Maria, Altieri, Nunzio
Understanding Tyre Wear Particle Emissions: Volatile Dominance, Variability, Coarse Particles and Measurement System Development for Chassis Dynamometer Use2026-24-0018To be published on 09/21/2026
This paper presents a set of targeted tyre emissions studies carried out within the Department for Transport’s Non Exhaust Emissions programme. The work was directed at improving the measurement of airborne particles generated by tyres, and at examining the factors that influence particle number and particle mass emission, plus explored physical tread wear. To achieve this, a revised sampling duct system was developed with high extraction flow and partial wrap-around of the tyre, and a coarse hard-wearing surface was applied to the chassis dyno roller. The sampling system supplied Total PN4, PN10 (volatile and non volatile), PM2.5, and particle size instrumentation. Multiple tyre types were selected to represent a broad range of sizes, constructions, manufacturers, compounds, and mileages. Tests were performed on a dedicated tyre testing facility using PG42, WLTC, and RDE based cycles, together with additional cycles designed to investigate the influence of temperature, speed, and
Andersson, Jon, Campbell, Michael, de Vries, Simon, Kramer, Louisa, Marshall, Ian, Southgate, Jason, Waite, Gary
Multi-Level CFD and System Simulation Approach for Optimization of Cooling Circuits in High Power Density Powertrains2026-24-0009To be published on 09/21/2026
This paper presents a CFD-based optimization workflow for the simulation and development of automotive cooling circuits, integrating three-dimensional steady-state analyses with one-dimensional transient modeling. The objective of the activity is to establish a robust methodology that links detailed component-level thermal characterization to system-level dynamic simulations, enabling the assessment of cooling performance under both driving and charging operating conditions. The thermal behavior of the cooling circuit components was first investigated using three-dimensional steady-state simulations performed with Ansys Fluent. For each relevant operating point, the fluid flow and heat transfer were resolved in full 3D, and temperatures were monitored at multiple locations within the components and along the circuit. The steady-state analyses provided spatially resolved temperature fields and heat transfer characteristics for a range of boundary conditions representative of real
Chiappini, Daniele, Tribioli, Laura, Rodionov, Artem
Optimal Eco-Driving for Electric and Conventional Refuse Trucks: a Comparative Analysis of Actual Speed, Energy Efficiency, and Travel Time.2026-24-0031To be published on 09/21/2026
Achieving significant reductions in energy consumption and CO₂ emissions in the transportation sector is a key challenge for sustainable mobility, particularly for vocational trucks operating under demanding driving and duty cycles. Beyond technological advancements in powertrain design, energy efficiency can be improved through optimized driving strategies. In this context, eco driving has emerged as an effective approach to reduce energy consumption by optimizing the speed profile under given operational constraints. Eco driving optimization strategies are indeed particularly well suited to predefined and repetitive driving cycles, such as those typically encountered in waste collection. This work presents a comparative analysis between electric and internal combustion engine powertrain configurations applied to refuse trucks and vehicles, highlighting the impact of intrinsic differences on optimal speed profiles, energy consumption, and travel time. Both configurations are required
Giacobbo, Andrea, Villani, Manfredi, Beltrami, Daniele, Tribioli, Laura, Iora, Paolo, Uberti, Stefano
Passive Thermal Management Through Vapor Chamber Integration of a PMSM E-Motor installed on UAV for Urban Mobility Applications2026-24-0010To be published on 09/21/2026
Thermal management represents a critical design aspect for Permanent Magnet Synchronous Motors (PMSMs) employed in Unmanned Aerial Vehicle (UAV) propulsion systems, where high power density and compact integration lead to significant heat generation. Excessive temperatures may compromise efficiency, reliability, and lifetime, making effective yet lightweight cooling strategies essential. The integration of a vapor chamber is investigated as a fully passive thermal management solution for a commercially available PMSM intended for UAV applications. Unlike active cooling systems, the proposed approach does not require moving parts, external power supply, or additional control devices. The vapor chamber operates through phase-change heat transfer mechanisms, enabling an enanched heat dissipation, exploiting the whole external surface of the vapor chamber; consequently the system naturally adapts to local thermal loads and provides self-regulating behavior without auxiliary components. A
Benedetti, Silvia, Lombardi, Simone, Federici, Leonardo, Chiappini, Daniele
Simulation-Based Development and Evaluation of Heat-Quantity-Based Thermal Operating Strategies for Automotive Applications2026-24-0012To be published on 09/21/2026
Efficient and robust thermal management is a key prerequisite for reproducible vehicle testing and energy-efficient powertrain operation. Conventional thermal operating strategies are commonly based on temperature setpoints and often neglect the dynamic relationship between heat input, system inertia and transient operating conditions, leading to increased energy demand and limited reproducibility under highly dynamic driving cycles. This paper presents a simulation-based development and evaluation of a heat-quantity-based thermal operating strategy for automotive applications. Instead of controlling the system solely via temperature targets, the proposed approach utilizes accumulated and instantaneous heat input as central decision variables for thermal control, explicitly accounting for thermal system dynamics. The investigation is conducted using a detailed vehicle simulation model including a physically-based thermal system representation. An innovative decentralized thermal
Stenger, Erik, Fiore, Luis, Weimer, Niko, Beidl, Christian
Experimental and Numerical Investigation of Hydrogen Direct Injection in a CI Engine2026-24-0004To be published on 09/21/2026
Compression ignition (CI) engines are widely used in the transportation sector due to their high torque and efficiency. However, the current climatic framework limits their application, favouring the adoption of low- and zero-carbon technologies. In this context, hydrogen represents a viable energy source for driving CI engines towards clean combustion. The benefits of hydrogen enrichment in diesel engines have been extensively investigated, particularly in port fuel injection (PFI) configurations. In contrast, the addition of a hydrogen direct injection system within a Common Rail engine remains largely unexplored. In this work, a piezo-actuated outward-opening direct injector fuelled by hydrogen was investigated through a combined experimental and numerical approach. The experimental campaign was conducted on an optically accessible single-cylinder research engine (SCRE), with the injector mounted in the cylinder head. Different injection strategies were explored in terms of duration
Episcopo, Domenico, Rossetti, Salvatore, Mancaruso, Ezio, Saponaro, Gianmarco, Lorusso, Leonardo, Camporeale, Sergio, Laera, Davide
Thermal Management of Pre-Chamber Spark Plugs for the Mitigation of Abnormal Ignition in Hydrogen-Fueled Engines – An Experimental and Numerical Study2026-24-0007To be published on 09/21/2026
The internal combustion engine will continue to contribute to global mobility, particularly when operated with CO₂-neutral or low-carbon fuels. Pre-chamber ignition systems are increasingly investigated to meet future requirements regarding efficiency, emissions, and combustion stability. In combination with hydrogen as a carbon-free fuel, pre-chamber spark plugs enable a significant extension of the lean operating limit while ensuring reliable ignition under demanding boundary conditions. A key development challenge is the thermal management of the pre-chamber spark plug. While the thermal behaviour of conventional production spark plugs is well established, limited knowledge exists for pre-chamber systems. The interaction of chamber geometry, material selection, manufacturing and joining processes, and installation position in the cylinder head strongly influences thermal loading and operational behaviour. Excessive local temperatures may promote knock, pre-ignition, or material
Nenzel, Markus, Alkezbari, Ahmad Anas, Rottenkolber, Gregor
Emissions reduction assessment in buses during real driving tests using hydrogen-methane blends as fuel2026-24-0006To be published on 09/21/2026
Increasing concern over climate change on planetary scale and urban pollution on a local spatial dimension are the pressing needs which invite to reduce greenhouse gas emissions in transportation as well as pollutant emissions. Both goals have prompted governments, industry stakeholders, and researchers to pursue innovative pathways toward sustainability in the on-the-road transportation sector trying to interpret this concept on the three requested dimensions, social, economic and environmental. Within this framework, hydrogen–methane mixtures have emerged as a promising alternative fuel solution which in someways match the three expectations. Hydrogen is characterized by carbon-free combustion, while methane is a comparatively clean and widely available fossil fuel. When blended, these two fuels can lower overall emissions relative to the use of pure methane, while still being compatible with existing internal combustion engines. This compatibility makes the adoption of such blends
Di Battista, Davide, Di Bartolomeo, Marco, Di Prospero, Federico, Di Diomede, Domenico, Cipollone, Roberto
Comparative Analysis of BEV Performance from Simulated Environment and Physical Hardware Platform2026-24-0005To be published on 09/21/2026
The proliferation of simulation environments has accelerated technological progress across various scientific domains by offering a cost-effective and time-efficient framework for data acquisition and analysis. In the automotive sector, high-fidelity modeling of vehicle components and driving scenarios bypasses the logistical constraints associated with hardware procurement and the intensive requirements of large-scale testing infrastructures. However, pre-calibrated or native software models often imply simplified hypotheses, missing relevant aspects of the entire powertrain-to-wheel energy chain. This study presents a comparative analysis of battery performance within a battery electric vehicle (BEV) by synchronizing virtual simulations with experimental hardware at the test bench. The methodology involves the concurrent modeling of the driving environment, the vehicle chassis, and the propulsion system, followed by the execution of identical driving cycles on a physical platform
Sequino, Luigi, Sementa, Paolo, Altieri, Nunzio, Vaglieco, Bianca Maria, Sorrentino, Chiara
Conversion of a 15kW diesel engine to operate in dual fuel mode with hydrogen and diesel2026-24-0014To be published on 09/21/2026
A 15kW diesel engine has been modified in the laboratory to operate in dual fuel combustion mode. The engine is a three-cylinder, displacement of 1 liter, fueled with diesel in its original configuration. It fulfills the emission standard by means of EGR system and three-way catalyst at the exhaust. The first system has been deactivated in the dual fuel operation mode of the engine. The engine has been modified to set three PFI injectors, facing the intake valves, in the intake manifold of the engine. The hydrogen injection is phased with the opening of the valve in the engine combustion cycle by delay units. The diesel injection with the standard ECU has been used as the start of combustion within the cylinder. The engine operation in dual fuel mode has been tested at maximum torque and power of the engine. To achieve the torque/power at several engine speeds both the quantity of diesel by the accelerator pedal position and the quantity of hydrogen adjusting the PFI injectors duration
Mancaruso, Ezio, Rossetti, Salvatore, Cameretti, Maria Cristina
Component Dynamics of a Motorcycle Brake Caliper: Analysis and Experimental Validation of Seal-Groove Mechanics and Controlled Rollback Design.2026-01-0823To be published on 09/14/2026
Pad - Rotor separation is critical to effective braking performance, pedal feel and NVH. In floating brake calipers, this separation is primarily governed by the seal and groove mechanics. Current studies primarily focus on the mechanics through empirical methods on single seal-groove systems for car calipers. However, a significant literature gap exists for motorcycle seal grooves and any system that utilizes a two seal-groove system with a primary pressure seal and a secondary dust seal. Since 75% of automobiles registered in India are motorcycles and Anti-lock braking becoming mandatory from 2026, designing a caliper with precise seal-groove mechanics becomes critical. This study proposes a theoretical framework by modeling the seals as a shear-beam and predicting the rollback using stick-slip hysteresis and resistive forces of the piston. Experimental validation was performed on three production motorcycle calipers, with the measured rollback and the piston push following the
Vaitheeswaran, Gyaneshwar, N, Manoj, M, Mahesh, Yogesh, Deepak, Rai, Ashutosh
A Study on Improvement of the Accuracy of Simulation for Squeal Noise Using Real Contact Friction Interface Model2026-01-0819To be published on 09/14/2026
The brake squeal noise arises from the complex phenomenon of the disc and the friction interface. In fact, even within the same shape of friction material, the noise characteristics vary based on the pattern of the friction interface. However, the current squeal noise simulation does not account for the effects of these friction interfaces; instead, it solely utilizes the friction coefficient and braking pressure to replicate the phenomenon. Consequently, the reliability of the complex eigenvalue analysis results is inevitably compromised. In this study, the complex eigenvalue analysis is conducted by incorporating the actual shape modeling technique of the friction interface, and the validity of the enhanced analysis method is validated through empirical testing. The friction surface modeling technique employed in this study is designed to randomly generate the friction interface of the analytical model by measuring the shape (form, waveform, roughness) of the actual friction surface
HWANG, JAEKEUN, KIM, SUNGHO, Kim, Jeongkyu, Kang, Donghoon
Machine Learning Prediction of Wear of NAO Brake Pad Using Scaled-Down FMVSS 135 Testing2026-01-0808To be published on 09/14/2026
Brake pad lifespan significantly influences environmental pollution and public health due to non-exhaust particulate emissions. Global vehicle production reached approximately 7 billion units in 2025, with brake systems generating an estimated 50,000 to 100,000 metric tons of wear debris annually, underscoring the need for improved durability and material optimization. This study investigates the capability of a Fully Connected Neural Network (FCNN) to predict brake pad wear and support formulation optimization. Controlled experiments were performed using a simplified FMVSS 135 protocol on a Universal Mechanical Tester (UMT) to simulate realistic braking conditions. Wear loss was measured under varying normal loads, sliding velocities, and interface temperatures. An FCNN was selected for its ability to capture nonlinear interactions between operating conditions and tribological responses. Despite a limited but high-quality dataset, the application of data standardization
Katakam, Abhishek, Eslamiat, Hossein, Kancharla, Sai Krishna, Filip, Peter
Optimization of Hydraulic Disc Brake Caliper Parameters to Achieve Near Zero Residual Drag in Two-Wheeler Brake Systems2026-01-0820To be published on 09/14/2026
Residual drag in hydraulic disc brake systems is an inherent phenomenon caused by elastic deformation of piston seals, geometric tolerances, and frictional interaction between piston, seal, and brake pads. Even minimal unintended pad-to-disc contact after brake release can generate residual torque, leading to increased rolling resistance, temperature rise, accelerated pad wear, and reduced vehicle efficiency. With growing emphasis on performance optimization and energy efficiency in two-wheeler applications, minimizing brake drag without affecting braking response has become an important design objective. This paper presents the design, analysis, and experimental validation of a zero-drag floating brake caliper concept developed to reduce residual brake torque through optimization of piston seal characteristics and groove geometry. The study focuses on understanding piston rollback behavior as the primary mechanism governing pad clearance after pressure release. Analytical evaluation
Badade, Ashish Laxman
Architecting Safety-Critical Systems for AI-Enabled Software-Defined Vehicles: A Compute, Timing, and Isolation Framework with a Brake System Case Study2026-01-0811To be published on 09/14/2026
Software-defined vehicle (SDV) platforms are reshaping safety-critical system design by consolidating braking and other motion-control functions on centralized heterogeneous edge compute that also executes physical-AI workloads. This consolidation breaks traditional assumptions of fixed ECUs and simple timing envelopes, complicating assurance of determinism, isolation, and fail-operational behavior for ASIL-D brake functions. Building on a decentralized brake-by-wire (BbW) architecture with dual controllers, redundant low-voltage power grids, and smart electromechanical brake corner actuators, this paper proposes a systems-level framework for architecting safety-critical functions in AI-enabled SDVs along three dimensions: compute, timing, and isolation. The framework classifies conventional and AI-based functions and maps them to heterogeneous compute classes; defines architectural patterns that combine safety islands, power-domain redundancy, and hardware partitioning to support
srinivasaraghavan, soumyasudharsan
Influence of Scrub Radius on Steering Dynamics, Bearing Durability and Wheel-End Packaging in Heavy Commercial Vehicles2026-01-0831To be published on 09/14/2026
Front axle geometry is a critical determinant of vehicle performance in heavy commercial vehicles (HCVs), directly influencing steering feel, component life, and maintenance costs. This paper investigates the effects of increasing scrub radius—defined as the lateral distance between the tire contact patch center and the steering axis intersection with the ground—on steering dynamics, durability, and packaging. A larger kingpin offset generating a positive scrub radius improves steering leverage and reduces steering torque, particularly beneficial for power-assisted steering systems. However, its broader implications for wheel-end design require detailed evaluation. High-fidelity multi-body dynamics models, validated through instrumented vehicle testing, were employed to quantify these effects under diverse scenarios, including low-speed maneuvering, high-speed lane changes, and severe braking. Results indicate that a controlled increase in scrub radius (10–20 mm) reduces steering
Pandiyan, Mahendran, Saxena, Saurabh
Assessing brake wear particle emissions and performance characteristic of NAO-ceramic formulation for Euro 7 Compliance2026-01-0828To be published on 09/14/2026
EU7 regulation has focused on non-exhaust emission from brake and tire wear and has set the brake particle emission limits accordingly. The current PM10 limit is set at 7 mg/km for IC vehicles and 3 mg/km for EV (electric/battery vehicles) of M1, N1 category. Hence, the brake particle emissions test should be conducted according to the UN Global Technical Regulation No. 24 (GTR-24) procedure on the brake inertia dynamometer. Due to these new requirements; brake systems need to be homologated with regard to EU7 emissions limits. In this study, NAO-ceramic formulation is developed and tested for performance, wear, noise and brake emission on brake inertia dyno using the global standards such as SAE J2522 (AK-Master Performance), SAE J2707B (Block Wear Test), SAE J2521 (NVH) and, Emission Test (WLTP/GTR-24. The developed NAO-ceramic friction grade not only having better friction, wear and NVH properties, but also reduce the brake emissions substantially and meets the current PM10 limit
Kumar, Mukesh, Tomar, Bharat, Ali, Sharafat, Kalel, Navnath
Thermomechanical Fatigue Life Prediction of Lamellar Graphite Cast Iron Brake Disks Using Advanced Material Models and Elastic-Plastic Fracture Mechanics2026-01-0816To be published on 09/14/2026
A comprehensive thermomechanical fatigue (TMF) life prediction methodology is developed for cast iron brake disks. The approach employs transient temperature fields as thermal loads in a nonlinear structural finite-element analysis (FEA). To obtain reliable stress and strain histories for cast iron, a time- and temperature-dependent plasticity model is required that captures viscous effects, nonlinear kinematic hardening, and tension–compression asymmetry. For this purpose, a unified elasto-viscoplastic Chaboche constitutive model coupled with damage is developed and implemented as a user material subroutine (UMAT) in the general-purpose FEA software Abaqus by Dassault Systèmes. In addition, a mechanism-based short-crack TMF model is extended to three-dimensional stress states under transient non-proportional loading conditions for TMF life prediction. The material parameters of the constitutive and the damage models are identified for lamellar graphite cast iron using isothermal and
Lee, Heewook, Garcia, Arnoldo, Liu, Yi, Hazime, Radwan, Boughanmi, Heni, Kassir, Abdallah
Comparison of the Surfaces and Coefficients of Friction of Truck Brake Pads Tested on a Flywheel Test Bench and a Scaled Tester – A Case Study2026-01-0826To be published on 09/14/2026
Mechanical brakes have been used and studied in many areas of mechanical engineering and automotive technology for decades. However, the processes in the contact zone have not yet been described with sufficient accuracy. One reason for this is the inability to observe the contact zone during contact. Studies in which one contact partner is replaced by an optically transparent material influence the processes in the contact area. Researchers are therefore forced to examine the surfaces of the contact partners after the actual contact has taken place. Various measuring systems, such as microscopes or laser sensors for surface structure measurement, are used to measure the surfaces of the brake pads. Due to shorter measuring times, mainly only smaller samples from measurements using pin-on-disc tribometers are examined for this purpose. However, various studies show that the friction and wear values of pin-on-disc tribometers cannot be transferred to real brake systems. For this reason
Rosenthal, Tobias Richard, Wiest, Daniel Christian, Meyer, Henning Jürgen
Data to Decisions: An AI-Driven Test Intelligence Platform for Integrated Analysis of Raw Data, Test Reports, and Specification Compliance in Brake System Validation2026-01-0807To be published on 09/14/2026
Validation of brake systems is increasing in complexity due to electrification, software-defined architecture, integrated control modules, and higher functional safety requirements. Although physical testing remains the primary source of engineering evidence, interpretation of results including DVP&R/PVP&R compliance verification, anomaly detection, documentation, and milestone decision support continues to rely heavily on manual engineering analysis. This results in extended feedback cycles, inconsistent interpretation across teams, and limited traceability between raw data, reports, and governing specifications. To support engineers with more objective validation processes, there is a growing need for structured, data-driven intelligence that transforms dispersed test artifacts into actionable engineering decisions. This paper presents Data to Decisions, an AI-driven Test Intelligence Platform designed for integrated analysis of raw measurement data, test reports, validation plans
Divakaruni, Saikiran, Willey, Joseph, Srivastava, Namrata, Sankar, Arya, Namala, Divya, Gowtham, Rahul Sangani
Correlation of tribological characteristics with Brake Emission Factors in automotive disc brakes2026-01-0829To be published on 09/14/2026
Following the recent introduction of the Euro 7 regulations, research on non-exhaust emissions, including brake wear particles, has increased. However, full-scale dynamometer tests are affected by complex variables such as vehicle class and brake system specifications, which makes it difficult to analyze the unique characteristics of friction materials independently. Previous studies have predominantly focused on comparing emission levels by friction material composition or on disc surface treatments, and quantitative correlations, resolved by friction material type, between the physical wear mass of friction materials and the Brake Emission Factor (BEF), remain scarce. In this study, the brake emissions from various friction materials were precisely measured using a scale dynamometer reflecting the UN-GTR No. 24 standards. By applying the WLTP cycle, a quantitative correlation was derived between the friction characteristics and the BEF for each braking section. The results show that
Jang, Pan Gyu, Kim, Duck Hyeon, Jeong, Yoon Oh, Kwon, Sung-Wook, Jung, Kwang Ki, Lee, Jungju
Physics-Informed Machine Learning Digital Twin of Electro-Mechanical Brakes for Clamp-Force and Friction Estimation2026-01-0806To be published on 09/14/2026
As the industry is rapidly moving towards dry-by-wire architectures, accurate Electro-Mechanical Brake (EMB) models are increasingly critical for safety-relevant force control, diagnostics, and consistent performance over temperature and lining wear. However, widely used EMB identification methods often rely on linearized models or 'characteristic curve' calibrations that struggle to generalize across operating regions where friction, hysteresis, and compliance are strongly non-linear and temperature sensitive. Prior EMB force-estimation literatures addressed pad contact detection, hysteresis and thermal compensated clamp-force estimation, yet practical accuracy gaps remain during transients and under changing friction signatures. This work proposes a digital twin based on Physics-Informed Neural Networks (PINNs) that preserves the EMB's governing dynamics while learning both (i) physically meaningful parameters- such as effective system inertia, damping, stiffness etc., and (ii) a
Rai, Prakhar, Gadhvi, Tirth
Advanced Brake Force Distribution on trailers with Bendix Electronic Brake Controller2026-01-0797To be published on 09/14/2026
Commercial vehicle fleets frequently operate with tractors that connect to different trailers and dollies, resulting in combinations with varying brake pad wear across wheel‑ends. Traditional brake force distribution strategies whether proportioned, electronic, or load‑adaptive do not account for these pad life differences. This can lead to uneven brake utilization, irregular maintenance intervals, and increased total cost of ownership (TCO), especially in mixed‑fleet and multi‑trailer operations. This work introduces an advanced brake force distribution function, a mechatronic brake control concept that incorporates brake pad health information into supervisory brake force allocation. In the proposed architecture, the tractor is equipped with a Brake Control ECU, which collects brake pad life status from each trailer or dolly through Pad Wear Sensing ECUs over the Tractor‑Trailer CAN (TT‑CAN) network. The Pad Wear Sensing ECUs report pad wear information only and do not host braking
Ganesha, Vinodkumar
Further Investigation of Brake Squeal: Effect of (Inboard/Outboard) Pads Property Differential2026-01-0799To be published on 09/14/2026
It was reported earlier that the wear differential between the inboard pad and the outboard pad leads to brake squeal generation. The (I/O) pads wear differential can occur due to hardware issues such as brake pad drag and/or two different wear rates of the (I/O) pads, which is caused by two different properties of the pads although the pad formula may be the same. The current investigation focuses on the pad property issues. It is found that pad compressibility differential and pad hardness differential are closely related to brake squeal generation. The property differentials are caused by pad porosity variations. The implications of hardness differential on friction/vibration will be discussed.
Liu, Richard, Wu, Shane, Wu, Godot, Li, Aihong, Zou, Tianlang
Time-Series Friction Torque Prediction for Drum Brake Systems via Mixed-Effects Random Forest Framework2026-01-0809To be published on 09/14/2026
The application of drum brake systems is expanding due to increasing cost competitiveness requirements in EV and purpose-built vehicle markets, as well as the introduction of EURO-7 particulate emission regulations. In spite of this trend, drum brake friction behavior is not yet fully understood because it is governed by complex and strongly coupled complicating mechanisms, including temperature history, braking conditions, and interactions between drum brake components. To address this gap, this study presents a method for developing a time-series friction torque prediction model using the Mixed-effects Random Forest (MERF) machine learning framework. Time-series data collected from sensors during drum brake dynamometer tests were analyzed to identify the key variables that govern the friction torque. Significant inputs were selected through Exploratory Data Analysis (EDA), considering test-to-test variability and potential mixed effects, and were then used to train and tune the MERF
Yoon, Jungro, Cho, Sunghyun, Kim, Wonjoon
Influence of Caliper Piston Wall Thickness and Hard Anodizing on Thermal Transfer and Seal Rollback Stability in Hydraulic Disc Brakes2026-01-0822To be published on 09/14/2026
Thermal stability and sealing reliability are critical performance parameters in hydraulic disc brake systems, especially under high-energy braking conditions where elevated temperatures directly influence brake fluid behavior and elastomer seal durability. Lightweight design trends increasingly encourage reduction in caliper piston wall thickness to optimize mass and response characteristics; however, such modifications alter the thermal conduction path and transient heat distribution within the piston–seal interface. This study investigates the combined effect of 50% reduction in aluminum caliper piston wall thickness and increase in hard anodizing thickness from 20 µm to 50 µm on heat transfer characteristics and piston seal rollback consistency. A comparative analytical and experimental approach is adopted to evaluate thermal resistance changes due to variation in anodic oxide layer thickness and piston geometry. One-dimensional thermal modeling is correlated with controlled
Badade, Ashish Laxman
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