Browse Topic: Heavy trucks

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Model-Based Optimization and Evaluation of Hybrid Powertrains for Commercial Heavy-Duty Class 8 Truck Applications02-19-04-00257/27/2026
In an ever-evolving landscape of emission regulations, charging infrastructure, customer demands, fuel/energy costs and decarbonization goals, heavy-duty on-road vehicle manufacturers continue to evaluate alternative powertrain technologies. While most heavy-duty vehicle manufacturers now have battery electric vehicles (BEVs) in their portfolio, significant challenges of charging infrastructure, range anxiety, payload capacity reduction and upfront costs have contributed to their lower adoption rates. Plug-in hybrid electric vehicles (PHEVs) have significant potential of leveraging upcoming BEV infrastructure and component supply chains to reduce operating costs while still maintaining longer range and payload capacity benefits of conventional ICE powertrains. This article applies a model-based approach to evaluate multiple Class 7–8 heavy-duty powertrain configurations. A system-level (1D) model of the conventional diesel ICE-based truck was developed in GT-Suite and validated against on-road test data. Using the diesel ICE model as a baseline, system-level models for different hybrid configurations were adapted, and their powertrain architecture was optimized at the system level. Additionally, an equivalent consumption minimization strategy (ECMS) for energy management was also optimized for each of the hybrid powertrain configurations to maximize fuel efficiency and emission benefits. All the hybrid configurations were then compared against the conventional diesel ICE Class 8 truck in terms of performance (acceleration, top speed, gradeability and startability), fuel economy (real-world cycles and certification cycles), emissions, and range for long-haul applications. Unique to this approach is the simultaneous co-optimization of powertrain component sizing and supervisory control logic by utilizing a Genetic Algorithm–based optimization approach. Results indicate that all parallel hybrid architectures (P2, P2–P3, and P4) achieve performance (acceleration, top speed, gradeability, and startability) parity or improvement compared to baseline diesel architecture. P2-based architectures demonstrated a 12–14% improvement in fuel economy on representative real-world cycles when operating in a blended charge-depleting–charge-sustaining mode of operation, and a 4–6% improvement in fuel economy when operating in charge-sustaining mode alone. By quantifying these results across diverse topologies, this work addresses a significant research gap in the holistic evaluation of Class 8 hybrids, specifically, the trade-off between multi-speed electric drives, system-level mass increases, and real-world fuel economy, that remains underexplored in current literature.
Baburaj, Adithya, Paul, Sumit, Dhanraj, Fnu, Joshi, Satyum, Franke, Michael
Improved Thermal Management for Operating a Battery Electric City Bus under Real Driving Conditions2026-01-07587/1/2026
The goal of reducing global CO2 emissions requires actions especially for the transportation sector. To achieve the goal, electric traction motors are frequently implemented in passenger vehicles, as well as in commercial vehicles like heavy-duty trucks or buses. Particularly electric city buses have the potential to reduce the local emissions in urban areas and provide local exhaust-emission-free mobility. While their number of registrations rises, research focusses on the improvement of the overall system in order to increase energy efficiency. High importance is gained by the thermal management of the whole system. This research investigates a simulative approach to improve the thermal management and therefore the energy efficiency of an electric city bus. The different thermal components of an electric city bus like drive system, battery system and heating, ventilation and air conditioning system (HVAC system) are modelled. Their thermal behavior has been validated in previous research. Based on the validated model, this study proposes an improved thermal management that, state-dependent, combines the thermal circuits of the single components to reduce the overall energy demand. Cooling or heating is provided by the HVAC system. Furthermore, the simulation utilizes real driving cycles of a city bus in the Hamburg area. Measurement data from an entire year are examined by a cluster analysis that results in typical application profiles for urban bus traffic. These profiles are used as basis for further research. An operating strategy for the thermal management of an electric city bus under real driving conditions is developed using the simulation model. Results are presented, which show that the overall energy demand decreases due to an improved, application profile-dependent thermal management system.
Schäfer, Henrik, Hellberg, Tobias, Meywerk, Martin
Field-Based Evaluation of Physiological Fatigue Reduction in Fuel Cell Refuse Collection Vehicle Using Heart Rate Variability2026-01-06906/20/2026
Understanding the physiological impact of vehicle electrification on operators remains an important but underexplored issue in commercial vehicle research. This study quantitatively evaluates the physiological fatigue of drivers and onboard crew members during real-world operation of commercial refuse-collection vehicles by comparing a diesel-powered vehicle with a fuel cell electric vehicle (FCEV). Both vehicles were operated on the same routes under comparable real-world operating conditions, including similar time periods and operational tasks, during municipal waste collection service. Heart Rate Variability (HRV) metrics were obtained from R-R interval (RRI) data recorded using a Polar heart rate sensor. The Root Mean Square of Successive Differences (RMSSD), a time-domain index reflecting short-term parasympathetic activity, and Poincaré (Lorenz) plot area (LP area), a nonlinear HRV index reflecting overall autonomic nervous system modulation, were calculated. In-cabin vibration and noise levels were also measured as supplementary context to support the interpretation of physiological responses. The results indicate that both RMSSD and LP area were higher during FCEV operation than during diesel vehicle operation. For the driver, RMSSD increased by approximately 61.65% and the LP area by approximately 49.91%. For the onboard crew member, RMSSD increased by approximately 18.79% and the LP area by approximately 46.02%. These findings suggest a consistent association between reduced vibration and noise characteristics in the FCEV and increased HRV indices, indicating reduced physiological fatigue during operation. This study provides quantitative evidence that fuel cell electric commercial vehicles are associated with improved occupational conditions, extending beyond conventional environmental benefits.
Utsumi, Atsuko, Yakoh, Takahiro
Development of a Diesel Combustion System for Next-Generation Heavy-Duty Engines Using a Synergistic Analysis-and-Testing Approach2026-37-00046/9/2026
Regulators and policymakers have introduced increasingly stringent limits on tailpipe CO₂ and pollutant emissions to accelerate the decarbonization of heavy-duty vehicle applications. The development of innovative propulsion technologies — such as advanced combustion systems, low-friction reciprocating components, and improved aftertreatment solutions — combined with hybridization and the adoption of alternative fuels (e.g., biogas, HVO, green hydrogen), is a key pathway for meeting future emission and GHG targets. In this study, advanced combustion systems were developed for a 13-liter diesel engine for heavy-duty truck applications, with the objective of meeting forthcoming Euro VII regulations while maximizing thermal efficiency. The combustion system architecture—including open-bowl geometry with high aspect ratio, injector nozzle with wider spray opening angle, and reduced swirl ratio—was optimized using a Machine Learning–algorithm trained on high-fidelity 3D CFD combustion data. The method enabled the identification of two optimized combustion-system “recipes”, one of which was evaluated through engine tests, which refined nozzle specifications and injection strategies, using a structured Design of Experiments (DoE) approach. Results were benchmarked against a MY24 baseline combustion system, assessing efficiency, NOx–soot trade-offs, and combustion behaviors. Based on 3D-CFD results, the advanced combustion concept achieved an improvement in Brake Thermal Efficiency (BTE) of up to +0.8% points and delivered substantial NOx reductions of up to 45%, while maintaining smoke emissions at or below baseline levels. The experimental results indicate that the advanced combustion system developments designed for next-generation heavy-duty engines can further increase BTE by up to ~1% relative to the baseline combustion system, without deteriorating the soot–NOx trade-off.
Belgiorno, Giacomo, Centini, Maria Pia, Pezza, Vincenzo, Cozza, Ivan F., Pesce, Francesco C., Vassallo, Alberto, Colombo, Giovanni, Gallo, Alessandro, Mirzaeian, Mohsen, Borg, Jonathan
Driveline Parking Brake Test Procedure for Medium Duty VehiclesJ2690_202606 (Current)6/3/2026
This SAE Recommended Practice establishes uniform test procedures for friction based parking brake components used in conjunction with hydraulic service braked vehicles with a gross vehicle weight rating greater than 4500 kg (10 000 lb). The components covered in this document are the primary actuation and the foundation park brake. Various peripheral devices such as application dashboard switches or indicators are not included. These test procedures include the following: a Brake Related Tests 1 Brake Functional Performance 2 Brake Dynamic Torque Performance 3 Brake Corrosion Resistance 4 Brake Endurance with Torque 5 Brake Endurance without Torque 6 Vibration Resistance 7 Brake Ultimate Static Load 8 Brake Lining Wear Adjuster Function b Actuation Related Tests 1 Mechanical Actuator Functional Performance 2 Mechanical Actuator Endurance 3 Mechanical Actuator Quick Release 4 Mechanical Actuator Ultimate Load 5 Spring Apply Actuator Functional Performance 6 Spring Apply Actuator Operating Temperature Range 7 Spring Apply Actuator Endurance 8 Spring Apply Actuator Corrosion Resistance 9 Spring Apply Actuator On-Off Switch 10 Spring Apply Actuator Vibration
Truck and Bus Hydraulic Brake Committee
ZF bets big on hybrid transmissions26TOFHP06_066/1/2026
ZF foresees hybrid powertrain technology becoming more popular for commercial transport in the coming years, and it's working earnestly to be a major player in that realm. The supplier unveiled the TraXon 2 Hybrid transmission to the North American commercial vehicle market at last year's ACT Expo and is now evaluating the technology in real-world conditions. The next-gen automated manual transmission (AMT) is optimized to improve fuel efficiency for plug-in and full hybrid heavy-duty trucks and coaches, as well as special applications such as medium- to heavy-duty mobile cranes.
Gehm, Ryan
Side Turn Signal Lamp for Long VehiclesJ2039_202606 (Current)6/1/2026
This SAE Recommended Practice provides test procedures, requirements, and guidelines for side turn signal lamps intended for use on vehicles 12 m or more in overall length, except pole trailers. Side turn signal lamps conforming to the requirements of this document may be used on other large vehicles such as trucks, truck tractors, buses, and other applications where this type of lighting device is desirable.
Heavy Duty Lighting Standards Committee
Design And Analysis of Low-Temperature Liquid Nitrogen Tank Car2026-99-17125/22/2026
The design and analysis of the wave plate of the tank body of the low-temperature liquid nitrogen tank car are carried out. According to the design method of the empirical formula, the 0.43 MPa low-temperature mobile liquid nitrogen tank body wave plate with the working temperature of -196°C to -178°C is optimized. According to the analysis and design standards, the stress distribution law of the mobile liquid nitrogen tank body under the forward impact condition is analyzed by the method of numerical analysis. The results show that the stress value will gradually increase near the junction of the tank body and the support, and the parts such as the head, the pad, the angle steel ring, and the Z3848 glass steel pipe meet the requirements of the analysis and design standards. At the same time, the first six orders of the natural mode vibration frequency of the tank body are analyzed, which provides a reliable and effective data analysis for the optimization design of the low-temperature liquid nitrogen tank body wave plate.
Ding, Xuqiang, Ni, Yiwei, Gu, Chen, Yan, Dongdong, Xu, Zhiquan, Wang, Qi
The Impact of Zero-Carbon Fuels on CO 2 Emissions Reduction from the Long-Haul Heavy-Duty Truck Fleet in Mainland China13-07-01-00035/22/2026
The decarbonization of heavy-duty trucks (HDTs) is a crucial path for China to achieve its “dual-carbon” goals and transition to decarbonized freight transport. Zero-carbon fuels are key alternatives to fossil fuels for these high-emission vehicles. This study develops an integrated scenario analysis framework to quantify the theoretical CO₂e emission trajectories of China’s long-haul HDT fleet from 2020 to 2060. Functioning as a macro-level stress test, the model derives theoretical equivalent stock from anticipated logistics turnover demand, integrating them with well-to-wheel (WTW) emission factors under six distinct policy stringencies (Projects 1 through 6), representing varying paces of fossil fuel vehicle phase-out. The results demonstrate that policy stringency primarily governs the timing and depth of emission reductions, while fuel technology defines the minimum achievable emission level. Three-dimensional visualization analysis reveals a nonlinear “emission cliff” under aggressive policies, marked by accelerated HDT fleet renewal and exponentially growing mitigation benefits. This cliff is more pronounced for the green hydrogen pathway and demonstrates its superior potential for deep decarbonization. In Project 1, CO₂e emissions reach a mid-term peak in 2035. Compared to the diesel baseline, the green hydrogen and green ammonia transition pathways reduce peak CO₂e emissions by 158 and 137 million tons, corresponding to reductions of 10.0% and 8.6%, respectively, under the modeled theoretical boundaries. In contrast, the aggressive Project 6 policy suppresses this peak, triggers the “cliff” effect much earlier, and achieves an extremely low stabilization level by 2040—15 years ahead of Project 1. This study provides a macro-theoretical quantitative decision-support tool for policymakers. It demonstrates that transparent and aggressive phase-out policies are essential to accelerate fleet turnover, trigger the “emission cliff,” and firmly cap total cumulative emissions.
Wu, Yunmei, Huang, Hua, Li, Rui, He, Guijia, Liu, Bo, Liu, Ruowei, Xie, Yongliang
Characterization of Fatal Cyclist Collisions Involving Nine Vehicle Types Traveling at Low and High Speeds in Japan09-14-01-00055/4/2026
To reduce traffic fatalities through vehicle safety measures, particular attention must be given to cyclist-related fatalities. Clarifying the characteristics of hazardous events leading to cyclist fatalities, not only by vehicle speed range but also by vehicle type, is essential and should be based on analyses of real-world accident data. Accordingly, this study aimed to characterize fatal cyclist accidents involving vehicles traveling at low and high speeds in Japan. We used macro accident data from the Japanese Institute for Traffic Accident Research and Data Analysis covering the period from 2013 to 2022. Based on nine vehicle types, we investigated the effects of road type, vehicle behavior, and accident type on cyclist fatalities. Additionally, we identified the five most frequent accident scenarios separately for each low- and high-speed category. At signalized intersections, the proportions of cyclist fatalities involving vehicles traveling at low speeds were higher than those involving vehicles traveling at high speeds across all vehicle types. In contrast, on straight roads, the proportions at low speeds were lower than those at high speeds for all vehicle types. In the low-speed range, cyclist fatalities within the top five scenarios accounted for 65% of all fatalities, with the most frequent scenario occurring at signalized intersections during left-turn maneuvers, where heavy-duty trucks accounted for 86% of the fatalities. In the high-speed range, cyclist fatalities within the top five scenarios accounted for 71% of all fatalities. The most frequent high-speed scenario involved crossing collisions at unsignalized intersections when vehicles traveled straight, with light passenger cars and sedans accounting for 29% and 24% of the fatalities, respectively. These findings provide valuable insights for the development of targeted traffic safety regulations and vehicle technologies aimed at reducing vehicle–cyclist collisions across different speed ranges.
Matsui, Yasuhiro, Oikawa, Shoko
Application of Reliability Growth Methods in Conjunction with Design for Reliability Framework to Validate Heavy Truck Design2026-01-01374/7/2026
Why field campaigns in the automotive industry have been going up over the years despite the strong development of technical knowledge, computational design tools and techniques to secure higher reliability standards since early stages of development phases? Uncertainties created by product complexity have been a factor that affects the ability of the manufacturers to prevent design failures before the product launch. Another factor is the shorter product development time, less test time to validate the product means that the new design will not have enough exposure to the real truck application and so some failures may not be able to be detected during the project. To deal effectively with uncertainties this study shows an application of reliability growth techniques in conjunction with DfR- Design for Reliability framework to validate the truck design in the customer application. The Crow - AMSAA method is applied to measure the reliability growth of the complete vehicle in various stages of product development by using the failure rate intensity. By doing that reliability related failures can be found and fixed during the project to secure the required level of failure rate at SOP.A tool developed in excel has the capability to calculate the confidence level and the demonstrable failure rate at any stage of the project to prove statistically the level of certainty of the results to support the decision-making process during project gates.
Coitinho, Marcos
Quantifying the Impact of Towing on BEV Energy Use: Instrumented On Road Testing and Chassis Dynamometer Reproduction2026-01-04314/7/2026
Electrification is rapidly entering all vehicle classes, including light- and heavy-duty trucks designed for heavy towing capabilities. Still, the quantitative impact of towing on battery-electric vehicle (BEV) energy use and range remains under-characterized. We conducted controlled towing tests with a Ford F-150 Lightning using two trailers of different sizes and varying payloads to isolate aerodynamic and mass effects and to span the full range of towable payloads within the vehicle’s rated capacity. The vehicle was instrumented at the CAN bus level, capturing motor power, torque, speed, and related internal signals from different control modules. On-road testing consisted of repeated back-and-forth passes on level, straight road segments at set speeds focusing on highway operation, where aerodynamic drag is stronger and real-world towing use cases occur. From these data, we extracted road load equations and dynamometer coefficients for each trailer combination, then reproduced equivalent conditions on a four-wheel drive chassis dynamometer across several standard cycles. Results were consistent across runs, showing a significant increase in the vehicle’s overall energy consumption and a corresponding range penalty. Additional impacts on vehicle systems due to towing, including thermal management of the motors and battery, were quantified. Dynamometer tests of varying characteristics (highway, urban, steady state speeds and accelerations) allow isolation of specific behaviors in functions like regenerative braking operation and torque-split strategy. Dynamometer results aligned with on-road measurements, enabling repeatable laboratory evaluation of towing scenarios. These findings provide a validated methodology and dataset to quantify towing impacts on BEVs, inform range prediction and route planning, support labeling and consumer guidance, and characterize sustained, high load real world operation of vehicle components.
Timermans Ladero, Inigo
Model-Based Development of a Heavy-Duty H 2 -ICE and Integrated, Turbogeneration, Electrification, and Supercharging (ITES) System2026-01-04264/7/2026
Changing global economic conditions and efforts to reduce greenhouse gas emissions are driving the need to develop efficient, near-term, alternative propulsion system technologies for heavy-duty vehicles. This study combines a hydrogen internal combustion engine (H2-ICE) with electrically assisted turbocharging, exhaust energy recovery, and mild hybridization to maximize propulsion system efficiency and reduce NOx emissions. To reduce cost and packaging impact of integration of these technologies on an engine, the study presents a model-based development and optimization of an Integrated Turbogeneration, Electrification, and Supercharging (ITES) system that combines the enabling components into a single compact unit. In the first phase of this study, a H2-ICE and aftertreatment concept for a MY2027 7.7L medium heavy-duty on-road engine was developed and evaluated through 1D simulation. The concept was to convert a diesel engine by changing the cylinder head to implement a port fuel injection (PFI) lean H2 SI combustion system with two-stage turbocharging and no external EGR. The concept was optimized for compression ratio, valve lift profiles, turbocharging, aftertreatment size/specification, and calibration using 1D system simulation in GT-SUITE. In the second phase of this study, the H2-ICE concept performance was further improved by integrating the ITES system and evaluated through 1D simulation. The ITES system replaces the conventional low-pressure stage of the boosting system and adds the capability of electrically assisted turbocharging, turbogeneration from exhaust energy, and P1 mild-hybridization. Applying a model-based approach, the H2-ICE & ITES component sizes were optimized for the best performance and emissions benefit. Using 1D simulation of validated models, the efficiency benefit of the ITES system on engine and vehicle level system was predicted. Finally, a vehicle level simulation was conducted comparing the fuel consumption between a conventional advanced boosting system H2-ICE concept and H2-ICE+ITES concept for Class 6-7 medium heavy duty truck application.
Bustamante, Oscar, Correia Garcia, Bruno, Joshi, Satyum, Franke, Michael
Multi-Physics Topology Optimization and Neural Network–Based Design of Experiments for Lightweight Automotive Cast Components2026-01-05104/7/2026
This paper presents a hybrid optimization framework that integrates Multi-Physics Topology Optimization (MPTO) with a Neural Network–surrogated Design of Experiments (NN-DOE) to enable lightweight structural design while satisfying crashworthiness, durability, and noise, vibration, and harshness (NVH) requirements under practical casting and packaging constraints. In the proposed MPTO formulation, crash and durability performances are incorporated through equivalent static compliance measures, while NVH performance is assessed using a frequency-domain dynamic stiffness metric, allowing consistent evaluation of trade-offs among competing design requirements. The framework is first demonstrated using a mass-produced passenger-car lower control arm (LCA) as a benchmark component. In this application, MPTO achieves weight reduction under multi-physics objectives by removing non-load-bearing material. Results show that single-discipline optimization produces unbalanced topologies, while balanced crash–durability–NVH consideration yields robust load paths. The study further demonstrates that crash and durability are dominated by static compliance–based response, whereas NVH performance is governed by frequency-dependent dynamic response over the relevant frequency range. The framework is then applied to a front engine mounting bracket of a newly developed heavy-duty truck. In this second application, a two-step strategy is employed in which MPTO first establishes the global load-carrying topology under manufacturing and packaging constraints, followed by NN-DOE–based local refinement to achieve stress attenuation at non-designable regions through global structural stiffness rebalancing, rather than direct geometric modification. Final verification confirms a steel-to-aluminum material transition achieving approximately 45% weight reduction and a substantial improvement in durability fatigue life, while maintaining required crash performance.
Kim, Hyosig, Senkowski, Andres, Gona, Kiran, Saroha, Lalit, Boraiah, Mahesh
Novel Air System for 300 kW Heavy Duty Fuel Cell2026-01-04344/7/2026
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.
Reich, Evan, Swartzlander, Matthew, Wine, Jonathan, McCarthy, Jr., James, Miller, Eric, Akhtar, Saad, Reddy, Sharan, Lawy, TJ
Physics-Based Simulation for Sustainable Fuels Part 2.2: Inter-Ring Pressure Measurements and 2D/3D Ring Dynamics Analysis across Multiple Engine Platforms – Heavy Duty and Large Bore2026-01-02804/7/2026
The growing demand for sustainable mobility and transportation is accelerating the adoption of alternative fuels, particularly hydrogen, in internal combustion engines. The first part of this publication series highlights the significance of 2D simulation as a crucial and computationally efficient tool for the precise development of hydrogen Power Cylinder Units. This approach demonstrates predictive capability proofed through engine tests, achieving a reduction in lube oil consumption by 5 g/h during high-load operations, alongside a 28% decrease in blow-by and an 11% reduction in hydrogen flow to the crankcase. To provide deeper insights into the complexities identified in Part 1, this study employs inter-ring pressure measurements across various engine types and configurations, including light vehicles, heavy-duty trucks, and large-bore applications, covering a broad range of engine displacements from 2 to almost 100 liters. Part 2.1 focuses on understanding the cyclic variations and mechanisms that lead to oil emissions during low-load operations at a light vehicle, while this investigation in Part 2.2 focuses on upper compression ring instabilities, cyclic variation in a heavy-duty engine and as well as the factors contributing to irregular combustion phenomena at a large bore engine. Complementing predictive 2D simulations and inter-ring pressure measurements, targeted 3D analyses are performed for capturing three-dimensional effects such as bore distortion and ring conformability. These analyses yield valuable insights into oil transport mechanisms that can contribute to irregular combustion. Part 3 of this publication series will concentrate on 3D oil transport simulations and optimization, including predictions of absolute lube oil consumption ranges of the hydrogen engine discussed in Part 1, while building on the valuable insights gained from the in-depth investigation of Part 2.
Köser, Philipp, Moreira, Rui
Experimental Evaluation of After-Treatment Solutions for Heavy-Duty Natural Gas Vehicles to Meet Future CNVII Regulations2026-01-03764/7/2026
The heavy-duty truck market in China has seen a significant increase in the adoption of natural gas-powered engines over the past two years. Simultaneously, the anticipated release of the China VII emissions regulation proposal by the end of 2025 is expected to impose stricter emissions limits on all heavy-duty engines, including new particulate number (PN10) thresholds analogous to those in the Euro 7 regulation. While tailpipe oxides of nitrogen (NOx) and methane (CH4) emissions from natural gas engines can be mitigated through tighter lambda control and adjustments to catalyst volume and precious metal (PGM) loading, addressing NOx and particulate number (PN) emissions necessitate more advanced after-treatment solutions. Although natural gas combustion is virtually soot-free, the entrainment of lubricating oil into the combustion chamber, especially during cold-start conditions, poses a challenge, leading to potential exceedance of the proposed future China VII limits. Additionally, PN emissions from natural gas vehicles are highly dependent on duty-cycles and the state of the actual engine, with applications involving frequent stop/go operation experiencing increased piston ring wear, and thus, higher oil consumption, and elevated PN emissions. This study aimed to evaluate the performance of different after-treatment solutions for natural gas engines in meeting future China VII emissions standards, with a particular focus on the efficacy of particle filters for controlling PN10 emissions. Three different after-treatment configurations, comprising close-coupled and underfloor three-way catalysts, as well as bare and coated filters, were tested on a 15L China VI commercial natural gas engine in a controlled laboratory environment. Emissions and PN10 data were collected over regulatory cold and hot World Harmonized Transient Cycle (WHTC) test cycles, and analyzed for light-off behavior, conversion efficiencies, system pressure drop, and filtration effectiveness for particles as small as 10nm. The relative advantages and challenges of each configuration are discussed. The results indicate that natural gas engines will likely require the integration of particle filter devices to comply with future China VII PN10 limits. The results also show that NOx compliance is challenging and fine-tuning of the lambda calibration is essential for CNVII.
Gao, Jiahui, Besch, Marc, Ding, Ning, He, Suhao, Zhao, Yuxin, Yixiao, Li, Shen, Ye
Camera Monitor System Soiling Correlation for a Class-8 Truck Using Lattice Boltzmann Method2026-01-05964/7/2026
As Camera Monitoring Systems (CMS) become an integrated part of the driving experience for current automotive and heavy vehicles, keeping the CMS clean from water, dirt, sand, snow and ice is a main focus of the design process in order to avoid safety issues due to obscured visibility. On-road soiling prevention becomes an important feature when designing the camera and sensor systems. Computational Fluid Dynamics (CFD) analysis can be used to facilitate the design process, to provide important information of the cause of the problems and design mitigation mechanism to prevent the visibility issues. Most of existing work focusses on automotive applications. This paper is targeted for heavy vehicle application. Road tests were performed in Alaska by the testing department. Results from the road test were compared to CFD simulation. This comparison showed a good agreement between CFD and road testing, based on the qualitative soiling deposition patterns, rivulet formation and dispersed wake-based deposition in the sensor regions.
He, Wei, Dasarathan, Devaraj, Linden, Tom, Park, Jeongbin
Physics-Based Simulation for Sustainable Fuels Part 2.1: Inter-Ring Pressure Measurements and 2D/3D Ring Dynamics Analysis across Multiple Engine Platforms – Light Vehicle2026-01-02814/7/2026
The growing demand for sustainable mobility and transportation is accelerating the adoption of alternative fuels, particularly hydrogen, in internal combustion engines. The first part of this publication series highlights the significance of 2D simulation as a crucial and computationally efficient tool for the precise development of hydrogen Power Cylinder Units. This approach demonstrates predictive capability proofed through engine tests, achieving a reduction in lube oil consumption by 5 g/h during high-load operations, alongside a 28% decrease in blow-by and an 11% reduction in hydrogen flow to the crankcase. To provide deeper insights into the complexities identified in Part 1, this study employs inter-ring pressure measurements across various engine types and configurations, including light vehicles, heavy-duty trucks, and large-bore applications, covering a broad range of engine displacements from 2 to almost 100 liters. This investigation in Part 2.1 focuses on understanding the cyclic variations and mechanisms that lead to oil emissions during low-load operations at a light vehicle, while Part 2.2 focuses on upper compression ring instabilities, cyclic variation in a heavy-duty engine and as well as the factors contributing to irregular combustion phenomena within a large bore engine. Complementing predictive 2D simulations and inter-ring pressure measurements, targeted 3D analyses are performed for capturing three-dimensional effects such as bore distortion and ring conformability. These analyses yield valuable insights into oil transport mechanisms that can contribute to irregular combustion. Part 3 of this publication series will concentrate on 3D oil transport simulations and optimization, including predictions of absolute lube oil consumption ranges of the hydrogen engine discussed in Part 1, while building on the valuable insights gained from the in-depth investigation of Part 2.
Moreira, Rui, Köser, Philipp, Rösch, Hannes, Ehnis, Holger
Analysis and Determination the Time to Rollover of Tractor Semi-Trailer Vehicle Based on Multi-body System Analysis and Newton–Euler Equations02-19-03-00133/27/2026
This article aims to determine the time to rollover (TTR) of a tractor semi-trailer vehicle (TSTV). It uses a full dynamics model for assessment, specifically applying multi-body system analysis and Newton–Euler Equations with a nonlinear tire model. The model is applied to investigate velocities ranging from 40 km/h to 80 km/h and magnitude of steering angles ranging from 12.5° to 300°. The times at which the Load Transfer Ratio (LTR), Roll Safety Factor (RSF), and lateral acceleration reach their maximum values are evaluated. The survey results demonstrate the impact of velocity and steering wheel angle on the time it takes for the LTR, RSF, and lateral acceleration to reach their maximum values. The time interval between the RSF reaching 1 and the LTR reaching 1 range from 0.144 s to 0.655 s. Similarly, the time it takes for the tractor body’s lateral acceleration to peak and the LTR to reach 1 varies between 0.228 s and 1.555 s. Additionally, the time interval from when the semi-trailer body’s lateral acceleration reaches its maximum value to when the LTR reaches 1 range from 0.057 s to 1.155 s. These time intervals can be used to determine the reserve time for early warning or control systems when selecting the thresholds, based on the vehicle’s lateral acceleration during a turn.
Hung, Ta Tuan, Khanh, Duong Ngoc
Anti-Rollover Strategy for Six-Axis Semi-Trailer Based on Lateral Force Balance02-19-04-00242/24/2026
To address the rollover risk of six-axle semi-trailers due to their large mass, high center of gravity, and multi-axle articulation, a lateral force balance anti-rollover strategy based on the Ackermann steering principle is proposed. By establishing the wheel angle constraint equations for the full-wheel steering system of the six-axle semi-trailer, a rigid-body dynamic model considering the articulation characteristics is developed. The key control and observation parameters are included in the wheel angles, center of gravity lateral offset, yaw angular velocity, sideslip angle, and lateral load transfer rate. An SMC-PID joint controller is designed, in which the third axle steering angle of the tractor is optimized by the SMC controller, and the trailer’s three-axle steering angle tracking control is achieved by the PID controller. The nonlinear accumulation of centrifugal force and dynamic load transfer under high-speed emergency lane change conditions is suppressed by a hierarchical control mechanism. The joint simulation results from TruckSim and Simulink indicate that, under the double lane change scenario with 88 km/h, the lateral force balance strategy reduces the rollover angles of the tractor and trailer by 85.5% and 86.9%, respectively, and the center of gravity lateral offset is improved by 77.5% and 92.3%; under the double lane change scenario with 80 km/h, compared with the active steering strategy of the trailer, the lateral load transfer rate fluctuation is reduced to the percentile level, and the rollover angles decrease by 62.9% and 65.3%.
Zhang, Qiyuan, Zhang, Lei, Liao, Shengkun, Sun, Jinxu, He, Jing
Understanding Prevailing Physics in Automotive Aerodynamics Applications—Detached Eddy Simulation vs Reynolds-Averaged Navier–Stokes Approach02-19-04-00232/6/2026
This study presents a structured approach to the aerodynamic evaluation of commercial heavy-duty vehicles by categorizing the underlying flow physics into three primary phenomena: pressure-induced separation, geometry-induced separation, and flow diffusion. Furthermore, the study gives insights into the benefits of Detached Eddy Simulations (DES) over traditional Reynolds-Averaged Navier–Stokes (RANS) approaches by analyzing the flow behavior in cases that correspond to these phenomena. Fundamental insights on pressure and geometry-induced separation were developed through simulations of flow over a sphere and a rectangular cylinder at a Reynolds number of 2.8 × 106. Additionally, flow diffusion was investigated using a coaxial jet interacting with surrounding fluid at a Reynolds number of 2.1 × 104. These cases were analyzed using three turbulence modeling techniques: k-ε, k-ω SST, and DES. To demonstrate the practical relevance of these phenomena, a comprehensive aerodynamic performance study was conducted on a commercial heavy-duty truck. This final analysis integrates all three flow behaviors, showcasing their combined impact on vehicle aerodynamics. The study emphasizes the effectiveness of the DES approach in capturing complex flow structures with enhanced accuracy. Furthermore, this study provides meshing guidelines for near-wall and wake dominant regions, to be implemented in DES-based simulations. The findings aim to support future research by offering a robust framework for applying advanced turbulence models in real-world aerodynamic evaluations.
Sankar, Hari, Holay, Sarang, Ikeda, Masami, Singh, Ramanand
Improving Semi-Truck Torque Overlay Steering Systems to Boost On-Center Performance: Hardware Design Investigation02-19-02-00122/4/2026
In class 8 semi-trucks, the hydraulic steering gear and torque overlay system are critical components affecting the steering feel design and vehicle control. Transitioning from traditional hydraulic gears to hydraulic gears with torque overlay steering (TOS) systems for increased enhancement of driver comfort is beneficial but has also resulted in drawbacks for on-center steer feel, especially at high vehicle speeds (60+ km/h). This article evaluates the impact of three design mechanisms within hydraulic steering gears of a TOS system that have shown improvement in on-center performance for traditional hydraulic gears. The study compares a standard assembly of TOS, i.e., baseline, and a design-optimized ideal prototype, to evaluate the effectiveness of the three design mechanisms: valve curve performance, on-center friction, and torsion bar stiffness. The two samples underwent high-speed vehicle testing to gather driver feedback and assess potential enhancements to the on-center steering feel. The final design changes on the ideal prototype were based on the best valve curve and on-center friction, as limitations in the torsion bar modification process precluded its use in the vehicle. The vehicle qualification team found insufficient evidence linking these design features to improved overall steering performance. Further research will be conducted to analyze the impact of torsion bar change as well as software controller performance within the TOS as a follow-up study.
Bari, Praful Rajendra, Chaudhuri, Nilankan
EDITORIAL: CONEXPO debuts - from micro to massive26TOFHP02_042/1/2026
Visitors to Las Vegas are down. According to a year-to-date summary released by the Las Vegas Convention and Visitors Authority, the number of people who visited the desert city through November 2025 was down 7.4% compared to 2024. Convention attendance was also lower in 2025 compared to the previous year. Many outlets report that a big reason for the drop is fewer international tourists - particularly from Canada - due to U.S. trade policies. The word from some fellow journalists who attended CES in early January is that this trend is continuing into 2026. Jack Roberts of Heavy-Duty Trucking wrote, “I've never seen the city as empty and listless as it was during my time there this year… And the show floor at CES - while still crowded - was noticeably less jam-packed than past years.”
Gehm, Ryan
A proactive approach to hydraulic health in Class 8 trucks26TOFHP02_072/1/2026
For any fleet or logistics manager, the specter of a downed Class 8 truck is a constant concern. The costs aren't just in parts and labor; they're in lost productivity, missed deadlines and potential damage to your reputation. While many factors can sideline a heavy-duty vehicle, one of the most persistent and costly culprits is hydraulic system failure. These failures often trace back to a single, preventable issue: contamination.
Lapierre, Luc
Steering Control Systems - Heavy TrucksJ2425_202601 (Current)1/27/2026
This SAE Recommended Practice describes a laboratory test procedure and requirements for evaluating the characteristics of heavy-truck steering control systems under simulated driver impact conditions, as well as driver entry/egress conditions. The test procedure employs a torso-shaped body block that is impacted against the steering wheel.
Truck Crashworthiness Committee
Waste Heat Recovery Evaluation in FCEV Truck on Different Drive-Cycles2026-26-02591/16/2026
Growing global warming and the associated climate change have expedited the need for adoption of carbon-neutral technologies. The transportation sector accounts for ~ 25 % of total carbon emissions. Hydrogen (H2) is widely explored as an alternative for decarbonizing the transport sector. The application of H2 through PEM Fuel Cells is one of the available technologies for the trucking industry, due to their relatively higher efficiency (~50%) and power density. However, at present the cost of an FCEV truck is considerably higher than its diesel equivalent. Hence, new technologies either enabling cost reduction or efficiency improvement for FCEVs are imperative for their widespread adoption. FCEVs have a system efficiency around 40-60% implying that around half of the input energy is lost to the environment as waste heat. However, recapturing this significant amount of waste heat into useful work is a challenge. This paper discusses the feasibility of waste heat recovery (WHR) technology for a long-haul FCEV heavy duty truck with a rated power of 300 kW. Two WHR system are evaluated – widely used Organic Rankine Cycle (ORC). Working fluids considered for the ORC model are R1233zd(E), R245fa and n-Pentane. The 0-D model of the ORC based WHR systems is developed in Matlab-Simulink platform for analysis. The waste heat generated is quantified at different drive-cycles, namely flat, moderate hilly and hilly terrain, using a complete vehicle simulation tool developed in Simulink platform. The waste heat data from complete vehicle simulation tool is provided as an input for the developed 0-D WHR models. The results show a considerable improvement in the overall fuel consumption of FCEV trucks with WHR systems. The findings imply the importance of WHR in FCEV truck to improve the overall system efficiency.
P V, Navaneeth
Electroluminescent Coating Systems for Heavy-Duty Trucks: Advancing Safety and Sustainability through Smart Surface Technology2026-26-02751/16/2026
As the transportation industry pivots towards safer and more sustainable mobility solutions, the role of advanced surface technologies is becoming increasingly critical. This paper presents a novel application of electroluminescent (EL) coating systems in heavy-duty trucks, exploring their potential to enhance vehicular safety and reduce environmental impact through lightweight, energy-efficient lighting integration. Electroluminescent coatings, capable of emitting light uniformly across painted surfaces when electrically activated, offer a transformative alternative to conventional external lighting and reflective materials. In the context of heavy-duty trucks, these systems can significantly improve visibility under low-light and adverse weather conditions, thereby reducing the risk of road accidents. Furthermore, the uniform illumination achieved without bulky fixtures contributes to aerodynamic efficiency, supporting fuel economy and reducing carbon emissions. use of this coating system, can optimize tooled up plastic part and sub-assemblies specially to those parts we use for indication, marking, highlight & lighting assisting during dark This paper identifies and evaluates specific use cases where EL coatings can deliver substantial benefits: for example, Exterior Lighting systems, Perimeter Lighting for Night Operations, Ingress/degrees illumination with Integrated Safety Features, Emergency and Breakdown Visibility & Trucking illumination accessories. Accentuate brand specific, Technology & design features over a truck
Harel, Samarth Dattatraya, Borse, Manoj, L, Kavya
Design and Development of a Lightweight Aluminium Cascade System for Type IV COPVs for Stationary and Mobile Applications2026-26-04851/16/2026
The global push for clean energy has made hydrogen a central element in decarbonizing transport, industrial processes, and energy systems. Effective hydrogen storage and distribution are critical to supporting this transition, and type IV Composite Overwrapped Pressure Vessels (COPVs) have emerged as the preferred solution due to their lightweight, high pressure capacity, hydrogen embrittlement and corrosion resistance. However, the cascade infrastructure used to house and transport these vessels has lagged behind in innovation. Steel-based cascades, while strong, are heavy prone to corrosion, and unsuitable for mobile deployment. This paper introduces a custom designed aluminium cascade system offering a 65% weight reduction while maintaining structural integrity and safety. Designed for mobile use, the system features modularity, better damping, and enhanced corrosion protection. The paper outlines design methodology, material selection, fabrication process, and comparative performance evaluation against steel cascade, supporting the advancement of hydrogen infrastructure.
Parasumanna, Ajeet Babu, Muthusamy, Hariprasad, Ammu, Vnsu Viswanath, Kola, Immanuel Raju
Mileage Accumulation Target Identification for Autonomous Emergency Braking System Validation for Medium & Heavy Trucks Considering Real-World Accidents in India2026-26-00361/16/2026
Robust validation of Advanced Driver Assistance Systems (ADAS) considering real-world conditions is a vital for ensuring safety. Mileage accumulation is a one of the validation method for ensuring ADAS system robustness. By subjecting systems to diverse real-world driving environments and edge-case scenarios, engineers can evaluate performance, reliability, and safety under realistic conditions. In accordance with ISO 21448 (SOTIF), known hazardous scenarios are explicitly tested during robustness validation in combination of virtual and physical testing at component, sub system and vehicle level, while unknown hazards may emerge through extended mileage by running vehicles on roads, allowing them to be identified and classified. However, defining a mileage target that ensures comprehensive safety remains a significant engineering challenge. This paper proposes a data-driven approach to define mileage accumulation targets for validating Autonomous Emergency Braking Systems (AEBS), using detailed analysis of real-world accident data in India along with ISO 21448 (SOTIF) validation framework. National-level accident data from MoRTH and the RASSI database, along with statistics for medium and heavy commercial vehicles, are utilized to derive the base incident rate for frontal collisions that AEBS is intended to mitigate. The framework integrates critical factors such as hazardous behavior probability, controllability, and severity to calculate a target incident rate, which then informs the required test mileage needed to statistically validate AEBS performance at a specified confidence level. The study outlines the derivation of mileage requirements by considering both accident and fatality reduction as primary safety metrics. This approach provides engineering guidance for defining test mileage requirements with respective to the defined acceptance criteria that ensure AEBS system robust validation considering the real world scenarios in India.
Koralla, Sivaprasad, Ravjani, Amin, Tatikonda, Vijay, Gadekar, Ganesh
Advancing Off-Road Autonomy: Comparative Analysis of Manual and AI-Driven Control in Autonomous Trucks2025-36-015212/18/2025
The deployment of autonomous trucks in off-road environments poses significant engineering challenges due to terrain variability and dynamic operating conditions. While recent advancements in perception, planning, and control architectures have improved vehicle autonomy, experimental validations comparing autonomous and manual control particularly regarding propulsion efficiency remain limited. This study addresses this gap by conducting structured field experiments to evaluate the performance of a heavy-duty truck operating in autonomous and manual modes. Tests were performed on a dedicated proving ground using a multi-sensor autonomous system. Key performance indicators included vehicle speed stability, engine speed regulation, and fuel consumption. The results show that autonomous driving achieved a 4.5% reduction in fuel consumption compared to manual operation. This gain is attributed to the system’s ability to maintain lower speed variance and more consistent engine behavior, especially during curved segments. These findings highlight the operational and energy efficiency advantages of autonomous control strategies in off-road logistics and support their broader adoption in agricultural and industrial applications.
Paula Silva, Cirilo, Yoshioka, Leopoldo Rideki, Kitani, Edson Caoru, André, Fatec Santo, Silva, Nouriandres Liborio
Tailpipe NOx Emissions Modeling of a Heavy-Duty Diesel Truck Using Deep Learning Methods03-18-08-004812/11/2025
This study develops deep learning (DL) long–short-term memory (LSTM) models to predict tailpipe nitrogen oxides (NOx) emissions using real-driving on-road data from a heavy-duty Class 8 truck. The dataset comprises over 4 million data points collected across 11,000 km of driving under diverse road, weather, and load conditions. The effects of dataset size, model complexity, and input feature set on model performance are investigated, with the largest training dataset containing around 3.5 million data points and the most complex model consisting of over 0.5 million parameters. Results show that a large and diverse training dataset is essential for achieving accurate prediction of both instantaneous and cumulative NOx emissions. Increasing model complexity only enhances model performance to a certain extent, depending on the size of the training dataset. The best-performing model developed in this study achieves an R2 higher than 0.9 for instantaneous NOx emissions and less than a 2% error for cumulative NOx emissions on the test data. Furthermore, the model achieves an F1 score above 0.9 in determining whether NOx emissions comply with emission standards. The developed DL tailpipe emission models in this study have diverse applications based on the amount and type of available input data, including engine and aftertreatment system control, diagnostics, and vehicle system-level simulations. These applications collectively contribute to minimizing NOx emissions of vehicles to meet stringent transportation emission standards.
Shahpouri, Saeid, Jiang, Luo, Koch, Charles Robert, Shahbakhti, Mahdi
SAE TOMORROW TODAY - Electrifying Europe?s Heavy-Duty Trucks1354612/5/2025
When it comes to battery electric trucks, is real-world data beating consumer expectations? According to findings from The International Council on Clean Transportation (ICCT), the real-world driving range of heavy duty electric trucks is 10 to 20% better than what is communicated by truck manufacturers. It's an exciting finding -- and one that could propel the decarbonization of freight forward. To learn more, we sat down with Hussein Basma, Senior Researcher at the ICCT, for an eye-opening look at the electrification of Europe's heavy-duty trucking sector. From ambitious regulations to rapid advances in battery technology and charging infrastructure, you'll discover how the EU is driving toward decarbonizing freight -- and what that means for the rest of the world. We'd love to hear from you. Share your comments, questions and ideas for future topics and guests to podcast@sae.org. Don't forget to take a moment to follow SAE Tomorrow Today--a podcast where we discuss emerging technology and trends in mobility with the leaders, innovators and strategists making it all happen--and give us a review on your preferred podcasting platform. Follow SAE on LinkedIn, Instagram, Facebook, X, and YouTube. Follow host Grayson Brulte on LinkedIn, X, and Instagram.
Patterson, Lori
Multi-Objective Design Optimization and Pugh Matrix Analysis to Develop Exhaust Tail Pipe Mounting for EU6 Heavy Trucks2025-28-029311/6/2025
The key performance evaluation criteria for any automotive exhaust system are pass-by noise (PBN), exhaust backpressure, durability and reliability, exhaust brake performance, aesthetics (if visible from outside the chassis), cost, weight and safety. Also, with changes in emission norms, emission from Exhaust Aftertreatment Systems (EATS) is one of the crucial parameters while designing the exhaust system. This paper covers a critical problem faced during the Beta Proto Build and Testing phase of exhaust tail pipe assembly. The exhaust tail pipe assembly had loose fitting issues, which can cause problems during the functioning of the truck. Parameters like material of the pipe, length of strap, tightening torque and tolerance of the pipe diameter were considered to resolve the fitment issue. The resolution is done with the help of Design of Experiments (DoE) and Pugh Matrix Analysis based on QDCFSS (Quality, Design, Cost, Feature, Safety and Sustainability). Design for Assembly (DFA) is a critical event, especially at Beta Proto Build and the pre-launch production phase. It has the dependency with design, parts (piece to piece variations- like dimension, material property), method shop floor facilities / resources (workstation – tools / machines), method/practices (variations – plant to plant / location to location) and workforces (training and physical states - like height). In the subject case, torque loosening / variations and difficulty in assembly have been reported from different plants / proto shops globally for the mounting of the exhaust tail pipe of EU6 heavy Trucks. In this context, Multi-Objective Optimization (MOO) is done with reference to DoE and Pugh Matrix evaluation to resolve the validation phase (testing) blocker problem of EU6 global trucks. Also, Quality Tools are used to do Root Cause Analysis (RCA), find Interim Corrective Action (ICA), and come up with different inputs for DoE. The primary objective of this research is to investigate and optimize the factors involved in tail pipe mounting schemes, which consist of tail pipe (GD&T and material), mounting clamp, torquing, and orientation preference. In material selection, Sustainability which is focused on SOC (substance of concern), CO2 reduction and R-Cycle framework, is equally important in decision making. This work indicates that the DoE technique, along with QDCFSS assessment, is very effective in optimizing multiple factors and resolving the problem identified by the proto build and testing team and ensuring follow the project milestone and business continuity.
P, Balu Mukesh, Rokade, Aditya, Biswas, Sanjoy
Integral–Derivative-Tilted Controller for Semi-Active Magnetorheological Truck Suspension System Using Combined Multi-Objective Ant Colony Optimization Algorithm02-19-02-000910/29/2025
This study proposes a novel control strategy for a semi-active truck suspension system using an integral–derivative-tilted (ID-T) controller, developed as a modification of the TID controller. The ant colony optimization (ACO) algorithm is employed to tune the controller parameters. Performance is evaluated on an eight-degrees-of-freedom semi-active suspension system equipped with MR dampers. The objective is to minimize essential dynamic responses (displacement, velocity, and acceleration) of the sprung mass, cabin, and seat. The controller also considers the nonlinear effects including suspension travel, pitch dynamics, dynamic tire loads, and seat-level vibration dose value (VDV). System performance is assessed under both single bump and random road excitations. The ACO-tuned ID-T controller is compared against passive suspension, MR passive (OFF/ON), and ACO-tuned PID and TID controllers. Simulation results demonstrate that the proposed controller achieves superior performance in both time and frequency domains under diverse road conditions.
Gad, S., Metered, H., Bassiuny, A. M.
Balancing Safety, Stability, and Comfort in Semi-Truck Platooning: A Study on Safe and Optimal Headways under Real-World Traffic Conditions2025-99-001710/17/2025
On highways, platoons of semi-trucks are a common phenomenon. By maintaining a small headway, these platoons can effectively reduce air resistance, thereby improving fuel efficiency and reducing carbon emissions. However, this driving mode is also accompanied by many safety and operational risks, such as increased risk of rear-end collisions, reduced driving comfort, and susceptibility to interference from other vehicles outside the platoon. Therefore, behavioral analysis and evaluation of semi-truck platoons naturally formed in real traffic environments are of great significance for improving their driving safety, comfort and stability. This study focuses on the headway characteristics of semi-truck platoons, analyzes their headway distribution, headway gap and braking response behavior, and then proposes a safe headway threshold for emergency braking to effectively reduce the probability of rear-end collisions. In addition, the study also defines an optimal headway range to reduce the possibility of external vehicle insertion, thereby improving the overall stability and driving experience of the platoon. Based on this, this paper constructs a semi-truck platoon model with safety as the core, and verifies it with actual traffic data, revealing the behavioral characteristics of naturally formed semi-truck platoons in terms of safety headways, optimal headways, and platoon distributions. The research results not only provide theoretical support for improving the safety and stable operation of naturally formed truck platoons, but also provide technical reference for the deployment and operation of future connected and automated truck (CAT) platoons in real road environments, helping the freight industry to develop in a more efficient and sustainable direction.
Hu, Xiaoqiang, Cao, Qiang
Rethinking VEHICLE CONTROLS25TOFHP10_0310/1/2025
Smarter control architectures including CAN- and LIN-based multiplexing can elevate operational efficiency, customization and end-user experience. From long-haul Class 8 trucks navigating cross-country routes to articulated dump trucks operating deep in a mining pit, the need for smarter, more reliable and more efficient control systems has never been more critical. Across both on- and off-highway commercial vehicle segments, OEMs are re-evaluating how operators interact with machines - and how those systems can be made more robust, flexible and digitally connected. Suppliers have responded to this industry-wide shift with new solutions that reduce complexity, improve durability and help customers future-proof their vehicle architectures. For example, Eaton's latest advancement is the E33 Sealed Multiplexed (MUX) Rocker Switch Module (eSM) - a sealed, modular switch solution that replaces traditional electromechanical designs with a multiplexed digital interface. Combined with Eaton's OMNEX Trusted Wireless mobile control systems, these innovations provide OEMs with a unified ecosystem for both cab-based and remote vehicle control.
Ortega, Carlos
Analysis of Front Axle Wheel End Temperature Measurements in Heavy-Duty Trucks2025-01-03649/15/2025
The Front Axle wheel end assembly is a critical component of Vehicle functionality, comprising a wheel hub positioned to rotate smoothly on an Axle spindle. This rotational movement is enabled by bearings positioned between the hub and the spindle, allowing for frictionless rotation. The Front Axle wheel ends’ temperature typically depends on several factors such as type of Vehicle, Load & driving conditions and health of the components involved. In general, the wheel ends can become warm during normal operation owing to friction generated by the rotation of the wheels and the interaction of various mechanical components such as Bearings and Brakes. However, if the temperature of the wheel ends becomes excessively hot, it could indicate potential issues such as Overheating brakes, Wheel bearing problems, improperly inflated tyres, and faulty components. As temperature rise, materials tend to expand. This expansion can affect the dimensions of critical components in the Front Axle wheel end, potentially leading to misalignment or increased friction between moving parts. Hence, it is very important to check the temperatures at various operating conditions and ensure to limit it within acceptance level to detect problems early on and prior to the Customer Vehicle operation. This paper emphasizes on the comparative test results of the Wheel ends’ temperature between Conventional and Unitized Bearings and its physical measurements carried out in a same Vehicle. Conventional bearings, which typically consist of separate Inner and Outer bearing assemblies, might exhibit higher operating temperatures compared to Unitized bearings owing to additional friction points and potential for misalignment. Unitized bearings, which integrate multiple components into a single assembly, tend to operate at lower temperatures compared to conventional bearings due to reduced friction and improved alignment. The Vehicle level temperature measurements at various worst-case conditions carried out and proved that the measured values are in correlation with estimated results. Maintaining appropriate temperatures in the Front Axle wheel ends is crucial for ensuring optimal performance of the Vehicle’s Braking system and drivetrain.
Pandiyan, Mahendran, Jayaraman, Karthik, R, Sabari, B, Ellavarasan, Bhanja, Subrat Kumar
Impacts of Hydrotreated Vegetable Oil as Renewable Diesel Fuel on Engine Performance and Emissions in a Heavy-Duty Diesel Engine03-18-06-00359/8/2025
As the pressure increases to move to renewable carbon-neutral fuel sources, especially in heavy-duty diesel engine applications, hydrotreated vegetable oil (HVO) has shown to be an attractive alternative fuel to fossil diesel. Therefore, this study investigated the impacts of HVO used as a drop-in fuel on performance and emissions of a nonroad heavy-duty diesel engine by running back-to-back D2 ISO 8178 cycles with ultra-low sulfur diesel (ULSD) and HVO. The measurement results showed that brake specific fuel consumption with respect to mass reduced by 1.1%–3.6% switching from ULSD to HVO due to greater heating values of HVO, which is supported by 0.7%–3.5% lower CO2 emissions recorded with HVO. Conversely, brake specific fuel consumption with respect to volume increased by 0.3%–2.9% with HVO because of its smaller density. Combustion analysis revealed that combustion of both fuels is comparable at high loads while HVO ignites earlier at low power. Thus, lesser reductions in NOx emissions (0%–6%) were observed at high loads, which can be attributed to lower combustion temperatures of HVO. On the other hand, higher cetane number of HVO at low loads resulted in notable reductions in NOx (36%–39%). Advanced start of HVO combustion at low power caused an increase in PM, soot, and smoke. At high to mid loads, PM, soot, and smoke decreased by 18%–55% because HVO is fully paraffinic, has higher H/C ratio compared to ULSD, and contains no sulfur or other mineral impurities. With greater reduction at low loads, HC and CO were lower for HVO due to its non-aromatic content, high cetane number, lower distillation curve, lower density, and smaller viscosity. Overall, it is concluded that HVO can play an important role as a sustainable fuel source for transportation and power production in the coming decades.
Duva, Berk Can, Abat, Bryan, Engelhardt, Jens
Reducing Range Prediction Uncertainty in Heavy-Duty Electric Vehicles Using a Route-Informed Transformer-Based Model2025-24-01229/7/2025
Electrification of heavy-duty on-road trucks used for regional freight transportation is a viable option for fleets to reduce operation and maintenance costs and lower their carbon footprint. However, there is considerable uncertainty in projecting their daily range because highly variable payload mass, among other factors, confounds battery state of charge (SOC) prediction algorithms. Previous work by the authors proposed an electric vehicle range prediction model based on two parallel recurrent neural networks (RNNs). The first RNN used mean-variance estimation to output a predicted mean and variance, and the second used bounded interval estimation to provide bounds on the SOC required to complete a trip. The dual RNN approach resulted in estimating the remaining range and error bands of the SOC over the route. The previous work was limited because it did not incorporate driving conditions, like road type and ambient temperature, that affect driver behavior and energy consumption. This work includes embedding additional contextual information about the road network and environmental conditions to narrow the error bands, which leads to more accurate state-of-charge prediction. The road-aware RNN algorithm is trained and tested on time series data collected from electric heavy-duty trucks over 30 months. The proposed model shows that the bands of uncertainty in the prediction of the remaining range can be improved by 67% compared to the previous model, thereby increasing confidence in daily operation by lowering the likelihood of unexpected battery depletion. Further, interpretation of the analysis shows that the algorithm can adapt to route geometry and ambient conditions, giving fleet managers a more robust basis to plan charging schedules under daily route variability. As a result, this refined approach for contextual road-awareness accelerates the adoption of electric heavy-duty trucks by mitigating range anxiety and improving operational planning.
Jayaprakash, Bharat, Eagon, Matthew, Northrop, William F.
Flexible an Low Cost Fuel Consumption Prediction in Heavy-Duty Vehicles Using Machine Learning2025-24-01219/7/2025
This study presents a novel approach for predicting fuel consumption in heavy-duty vehicles using a Machine Learning-based model, which is based on feedforward neural network (FFNN). The model is designed to enhance real-time vehicle monitoring, optimize route planning, and reduce both operational costs and environmental impact, making it particularly suitable for fleet management applications. Unlike traditional physics-based approaches, the FFNN relies solely on a refined selection of input variables, including vehicle speed, acceleration, altitude, road slope, ambient temperature, and engine power. Additionally, vehicle mass is estimated using a methodology presented elsewhere and is included as an input for a better generalization of the consumption model. This parameter significantly impacts fuel consumption and is particularly challenging to obtain for heavy-duty vehicles. Engine power is derived from both engine torque and speed (RPM), ensuring a direct relationship with fuel consumption while keeping computational complexity low. Experimental data were collected from a fleet of heavy-duty trucks under real-world operating conditions. In particular, the study focuses on a turbocharged diesel truck with a maximum power output of 353 kW. The acquisition system is based on an On-Board Unit (OBU) featuring CANbus connectivity, GPS tracking and 4G/LTE-5G communication. The OBU enables continuous logging of vehicle and engine parameters over each mission. Additional road data, such as altitude and slope, were obtained from external mapping services. For the purpose of FFNN development, the training dataset was compiled from approximately 10 different routes, capturing diverse driving conditions, while validation was conducted on 10 independent routes to assess model generalization. Before training, input data were pre-processed using normalization and standardization techniques to ensure stable convergence and mitigate the impact of scale differences among input variables. A correlation analysis was performed to evaluate the relationships among available parameters and fuel consumption, guiding the selection of the most informative inputs. This step reduced redundancy in the dataset and improved network efficiency. Furthermore, hyperparameter optimization was conducted using a Randomized Grid Search algorithm, enabling the identification of an optimal network architecture - specifically in terms of the number of layers and hidden neurons - and training parameters while minimizing overfitting. The final model demonstrated high predictive accuracy across various validation routes, confirming the effectiveness of the FFNN in estimating fuel consumption with a reduced input set. Accuracy was tested on up to 50 routes, whose data where not considered for both training and validation; it was assessed that fuel consumption percentage error per route never exceeded 2%. This approach provides a practical and computationally efficient solution for fleet operators, facilitating advanced route planning and enabling more sustainable transportation strategies through cost-effective fuel management and emissions reduction.
Vicinanza, Matteo, Pandolfi, Alfonso, Arsie, Ivan, Giannetti, Flavio, Polverino, Pierpaolo, Esposito, Alfonso, Paolino, Antonio, Adinolfi, Ennio Andrea, Pianese, Cesare, Frasci, Valentino
Effect of PEM Fuel Cell Technology Advancement on the Energy Efficiency of a Heavy-Duty Vehicle2025-24-01119/7/2025
Fuel cell hybrid electric vehicles (FCHEVs) are a promising solution for decarbonizing heavy-duty transport by combining hydrogen fuel cells with battery storage to deliver long range, fast refuelling, and high payload capacity. However, many existing simulation models rely on outdated fuel cell parameters, limiting their ability to reflect recent technological improvements and accurately predict system-level performance. This study addresses this gap by integrating a state-of-the-art, physics-based model of a polymer electrolyte membrane fuel cell (PEMFC) into an open-source heavy-duty vehicle simulation framework. The updated model incorporates recent advancements in catalyst design and membrane conductivity, enabling improved representation of electrochemical behavior and real-time compressor control. Model performance was evaluated over a realistic 120 km long-haul drive cycle. Compared to the traditional fuel cell model, the updated system demonstrated up to 20% lower hydrogen consumption, significantly reduced compressor power demand, and improved cooling performance due to higher stack efficiency. Peak fuel cell efficiency approached 59%. The findings highlight the critical importance of using up-to-date fuel cell models in FCHEV simulations to enable accurate energy predictions and optimal system design. This work supports more effective deployment of zero-emission heavy-duty vehicles through improved model fidelity and control strategy development.
Dursun, Beyza, Johansson, Max, Tunestal, Per, aronsson, Ulf, Eriksson, Lars, Andersson, Oivind
Energy Prediction for Hotel Loads in Mild-Hybrid Heavy-Duty Vehicle02-18-03-00208/29/2025
Long-haul truck drivers are mandated to take off-duty time of 10 h (a.k.a. hoteling) before driving. During the hotel phase, drivers spend time inside their trucks (sleeper cabs) and idle the internal combustion engine for comfort by utilizing the heating, ventilation, air-conditioning (HVAC), and other onboard appliances. For one 10-h period, the average cost is about $40, which can be a lot when considering a million truck drivers idling overnight. SuperTruck II is a 48 V mild-hybrid heavy-duty truck with auxiliary loads powered by an onboard battery pack. An optimal control algorithm is developed to charge the battery pack during the drive phase up to a certain state-of-charge (SOC) level, sufficient to meet the power demands of the auxiliary load during the hotel phase. This article captures the research done to predict energy consumption in a mild-hybrid heavy-duty sleeper truck during hoteling. Physics-based gray box models are developed to estimate the power consumption of an electronically controlled compressor. For other auxiliary loads, a machine learning algorithm is developed to predict the power as a time series by tracking the user activity. The developed physics and data-driven models are validated with experimental data from heavy-duty trucks to show their efficacy. These validated models generate precise load profiles fed to the developed dynamic programming framework to generate the optimal SOC trajectories. These models help the vehicle battery pack charge only up to the SOC necessary for the hotel phase during the drive time. When the vehicle is out of charge during the hotel phase, these models also help in estimating the amount of idling required to charge the battery enough to support the rest of the hotel period. This saves unnecessary idling. As a result, a cost savings of $40 and CO2 reduction of 175 lb to the environment is achieved for a single heavy-duty truck with a sleeper cab during the hoteling phase.
Khuntia, Satvik, Hanif, Athar, Ahmed, Qadeer, Lahti, John, Jorgensen, Iner
Validation of Wind Noise for Class-8 Truck Using Lattice Boltzmann Method02-18-03-00218/29/2025
The transportation and mobility industry trend toward electrification is rapidly evolving and in this specific scenario, wind noise aeroacoustics becomes one of the major concerns for OEMs, as new propulsion systems are notably quieter than traditional ones. There is, however, very limited references available in the literature regarding validation of computational fluid dynamics (CFD) simulations applied to the prediction of aeroacoustics contribution to the noise generated by large commercial trucks. Thus, in this work, high-fidelity CFD simulations are performed using lattice Boltzmann method (LBM), which uses very large eddy simulation (VLES) turbulence model and compared to on-road physical tests of a heavy-duty truck to validate the approach. Furthermore, the effect of realistic wind conditions is also analyzed. Two different truck configurations are considered: one with side mirror (Case A) and the other without (Case B) side mirrors. The main focus of this work is to assess the accuracy of the commercial CFD software PowerFLOW® to predict greenhouse wind noise analysis for heavy vehicles as a tool to complement or replace physical testing during the vehicle design process. From this study, we found that external microphone measurements at the passenger-side glass demonstrate strong correlation with simulation results, highlighting the importance of including a typical level of on-road free-stream turbulence to achieve accurate sound pressure level (SPL) correlations for the full frequency range available from the physical test (i.e., 100 Hz to 2000 Hz) for both configurations.
Guleria, Abhishek, Novacek, Justin, Ihi, Rafael, Fougere, Nicolas, Dasarathan, Devaraj
SAE TOMORROW TODAY - Powering A Cleaner Commercial Vehicle Industry135328/29/2025
From battery-electric trucks to hydrogen fuel cell vehicles, the company behind Kenworth, Peterbilt, and DAF is leading the charge toward zero-emissions. PACCAR is a global technology leader in the design, manufacture, and customer support of premium light-, medium- and heavy-duty trucks. The company is also actively investing in zero-emission technologies, positioning itself as a leader in the transition to cleaner commercial vehicles. To learn more, we sat down with Dr. Philip Stephenson, General Manager, PACCAR Technical Center and Executive Chair of this year's COMVEC, the annual commercial vehicle engineering conference hosted by SAE International. Listen in for an engaging discussion on PACCAR's approach to battery-electric trucks, hydrogen fuel cell vehicles, and charging infrastructure partnerships. And if you enjoyed this conversation, register now for COMVEC and join us as we bring together industry leaders, engineers, and innovators to discuss the latest advancements in on- and off-highway mobility technologies. We'd love to hear from you. Share your comments, questions and ideas for future topics and guests to podcast@sae.org. Don't forget to take a moment to follow SAE Tomorrow Today--a podcast where we discuss emerging technology and trends in mobility with the leaders, innovators and strategists making it all happen--and give us a review on your preferred podcasting platform. Follow SAE on LinkedIn, Instagram, Facebook, Twitter, and YouTube. Follow host Grayson Brulte on LinkedIn, Twitter, and Instagram.
Patterson, Lori
Methods for Estimating Coasting Resistance of Heavy-Duty Commercial Vehicles under Various Loads02-19-01-00058/19/2025
This research primarily addresses the issue of resistance model setting for chassis dynamometers or EIL (engine-hardware-in-the-loop) systems under various loads. Based on the data available from the heavy-duty commercial vehicle coast-down test reports, this article proposes three methods for estimating coasting resistance. For heavy-duty commercial vehicles that have not undergone the coast-down test, this article proposes the GA-GRNN (AC) model to predict coasting resistance. Compared to the GA-BPNN model proposed by previous studies, the new model, which achieves 93% prediction accuracy, demonstrates higher estimation accuracy. For heavy-duty commercial vehicles that have undergone the coast-down test, the coasting equal power method proposed in this article can estimate the coasting resistance under various loads. The accuracy and stability of the new method are verified by several coast-down tests. Compared to the existing method proposed by existing scholars, the new method has a higher estimation accuracy, thus compensating for the limitations of the coast-down test in measuring the coasting resistance. When neural network is combined with the coasting equal power method, they not only overcome the limitations of neural network predictions for coasting resistance but also compensate for the limitations of the coasting equal power method in estimating coasting resistance. Ultimately, the methods proposed in this article provide a feasible solution for setting resistance models of chassis dynamometers or EIL systems under various loads, without relying on coast-down tests.
Liang, Xingyu, Sun, Shangfeng, Li, Tengteng, Zhao, Jianfu
Refurbishing high-voltage batteries FOR ELECTRIC TRUCKS25TOFHP08_038/1/2025
Mercedes-Benz Trucks employs “like-new” reworked batteries to expand its spare parts portfolio and to inform future battery designs that are more sustainable. Remanufacturing engines for medium- and heavy-duty trucks is nothing new to the industry. Reworking high-voltage batteries for reuse in electric trucks is a newer practice. Used batteries are often recycled or find a second life in stationary energy storage systems. Mercedes-Benz Trucks is all in on the approach, launching the new reworked CB400 battery for first-generation eActros 300/400 and eEconic trucks. The so-called “Genuine Reworked Batteries” offer a resource-efficient and economically attractive alternative to brand-new replacement batteries, the manufacturer says, providing customers with like-new quality, tested safety and full functionality.
Gehm, Ryan
Multibody Analysis for Vehicle Dynamics and Durability: Application to a 6x2 Truck and 1+3 Grain Semi-Trailer Combination2025-36-03188/1/2025
The development of modern road implements demands rigorous and comprehensive analyses of various design aspects, including the dynamic behavior of vehicles and the structural durability of their components. Multi-Body System Simulation (MBS) has become an essential tool in developing efficient products, allowing engineers to virtually assess how a truck + semi-trailer combination responds to different operational and loading conditions. By employing models that account for detailed interactions among various vehicle systems -such as suspension, chassis, axles, and fifth wheel-vehicle dynamics can be investigated in complex scenarios. These scenarios replicate real road usage, abrupt maneuvers, and special testing tracks, providing insights into performance under demanding conditions. This approach also facilitates the cascading of loads between systems to conduct durability calculations and estimate the operational lifespan of the implement. This study introduces a development cycle for complete vehicles using MBS technology combined with the finite element method (FEM). Such an approach enables the inclusion of system flexibility, significantly enhancing the accuracy and reliability of simulation results. The constructed model is designed to be modular, making it reusable for future projects and enabling detailed analyses across multiple scenarios for the same vehicle. This includes extreme cases that are difficult or impractical to evaluate through traditional physical testing methods. In this study, scanned tracks from the CTR durability procedure were used to define the boundary conditions of the simulation models, and the commercial software Altair MotionSolve was employed to perform the multibody calculations. The simulation results are presented and briefly discussed, demonstrating the effectiveness of this integrated approach in advancing vehicle development.
Justo, Gabriel, Crocoli, Micael, Vigânico, Carlos, Pio, Frederico Nodari
Self-Controlled Electrically Powered Semitrailer02-19-01-00027/28/2025
In this article, the hybrid drive is discussed of the combination of conventional tractors with electrified trailers, usually referred to as E-trailer. We demonstrate that this approach offers the possibility of achieving fuel savings exceeding 20%. For regional trips, about half of this reduction is achieved without offline charging, i.e., without applying electric energy from the E-trailer battery. For motorway dominant trips, more use is required of the battery energy. A new control strategy is proposed, validated through simulations, in which only three control parameters are required, which can be tuned effectively to achieve maximum fuel reduction under certain trip and loading conditions. This control strategy adjusts the E-trailer torque request, based on the requested power for the tractor diesel engine, being estimated through a smart kingpin sensor. It ensures that the E-trailer supports the tractor propulsion when significant power is required, and recovers energy when the demand for power is low. The control parameters consist of the maximum torque request for the E-trailer during support, the maximum negative torque request during regeneration, and the transition power between regeneration and support. Semitrailers are generally not linked to a specific tractor. The control strategy is unique in that it does not need access to the tractor data network, thus achieving optimum interchangeability. The sensitivity with respect to driving resistance parameters appears to be low and may be counteracted by tuning the control parameters. More care is needed for the assessment of the trailer mass and trailer center of gravity. Finally, the total fuel reduction is discussed in comparison to the charging costs for the E-trailer battery (cost–benefit analysis), for realistic cost levels for fuel and kWh.
Pauwelussen, Joop, Kural, Karel, Hetjes, Bas
Cab Roof Strength Evaluation - Quasi-Static Loading Heavy TrucksJ2422_202507 (Current)7/22/2025
This SAE Recommended Practice describes the test procedures for conducting quasi-static cab roof strength tests for heavy-truck applications. Its purpose is to establish recommended test procedures that will standardize the procedure for heavy trucks. Descriptions of the test setup, test instrumentation, photographic/video coverage, and test fixtures are included.
Truck Crashworthiness Committee
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