Browse Topic: Trucks

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Currently, methods to improve the stability of liquid tank trucks mainly focus on mitigating the sloshing of liquid inside the tank. This is usually achieved by adding various additional devices such as baffles, bulkheads, and flexible materials. However, existing methods are relatively singular and passive in addressing the liquid sloshing response under complex driving conditions of tank trucks, and they do not fully consider the coupling effects of the entire vehicle’s dynamics model on tank sloshing. This article proposes an intelligent control strategy that uses threshold values as a control criterion to move the baffle in the direction opposite to the liquid sloshing. For comparison, a corresponding condition with stationary baffles was set as a control, and the effects of movable baffles and their porosity on the roll stability of tank trucks were studied. To further investigate the coupling interaction between liquid sloshing and the vehicle during actual driving, this article realized a bidirectional coupling response between the liquid sloshing numerical model and the vehicle’s eight-degree-of-freedom dynamic numerical model. Through model validation, the accuracy of both the liquid sloshing model and the vehicle’s eight-degree-of-freedom model was confirmed. The study found that movable baffles can more effectively suppress liquid sloshing compared to stationary baffles. By controlling the movement of the baffles, the impact of liquid sloshing on vehicle behavior can be reduced, thus improving vehicle stability. This article provides a new, customizable intelligent control approach for complex driving conditions.
Zhang, Zhe, Liu, Lingzhi, Zhang, Shijie, Li, Jinji, Zhang, Yingchao, Liu, Tao
This article presents an experimental investigation of off-tracking in a tractor–semitrailer during intersection-type turning maneuvers, which typically involve quarter-circle turning paths at urban junctions. Two coupling configurations are examined: a conventional fifth-wheel coupling (CFWC) and a split fifth-wheel coupling (SFWC). A scaled articulated vehicle prototype is developed to conduct controlled low-speed turning tests across multiple radii representative of intersection maneuvering conditions. The measured trajectories of the tractor and semitrailer are compared with predictions from a previously developed zero-speed kinematic model adapted for the present configuration. Maximum off-tracking is quantified for both coupling systems, and agreement between measured and simulated trajectories is evaluated using a normalized root-mean-square error metric. Results show that the SFWC consistently reduces off-tracking relative to the CFWC across all tested radii, while the kinematic model predicts the measured off-tracking profiles with mean-normalized errors below 0.1. The study is positioned as an experimental assessment of a previously proposed SFWC concept and kinematic formulation, rather than as a new coupling concept or a new modeling method. The findings provide controlled experimental evidence on the influence of coupling configuration on low-speed off-tracking behavior, while the practical implementation of the SFWC is identified as requiring further full-scale mechanical design, articulation limit, and durability studies.
Jogi, Ajith, Chandramohan, Sujatha, Krishnapillai, Shankar
Total Cost of Ownership (TCO) is a key metric in commercial vehicle purchase decisions and evaluation of advanced technologies such as battery electric and fuel cell vehicles (BEVs and FCEVs). Inputs derived from aggregate operating data, such as annual miles of travel and average fuel efficiency, as used in most TCO tools, may be inadequate for assessing technologies in specific applications. To provide more accurate estimates, the Transportation Technology Total Cost of Ownership (T3CO) model integrates vehicle simulation using the Future Automotive Systems Technology Simulator (FASTSim™). T3CO incorporates opportunity costs that may arise when technologies do not provide equivalent performance to conventional powertrains, such as reduced payload capacity and added downtime for more frequent and longer duration refueling. While past analyses used single duty cycles representative of average daily distance and energy per mile, fueling dwell time is nonlinear with respect to daily energy requirements and may not be captured with representative cycles. In this study, T3CO is applied to real-world operational data collected over 32 months from conventional Class 5 work trucks in three fleets, covering a variety of use cases and variability in daily demands. Diesel, BEV, and FCEV powertrains were simulated over the full data set, for a total of 1,986 vehicle days and 145,919 miles each. Analysis of duty cycle variability results in up to a 61% difference in fleet-level weighted average TCO compared to analysis over a single representative day. While diesel and FCEV TCO results are sensitive to fuel cost, BEV TCO is sensitive to the downtime from occasional daytime charging present in the total life cycle and not reflected in a subset “representative day.” For the studied fleets, these findings alter conclusions about the relative cost-effectiveness of new technology options at both the vehicle and fleet levels.
Birky, Alicia, Panneer Selvam, Harish, Sigler, Cory, Carow, Kyle, Miller, Eric, Ortmann, Walt, Tascillo, Mark
This SAE Recommended Practice contains dimensions and their tolerances concerning disc wheel to hub or drum interface areas for truck and bus applications. Disc wheels designed only for single wheel applications (not dual wheels) for light trucks and special or less common applications are not covered in this document.
Truck and Bus Wheel Committee
Four-axle electric-drive special vehicles are often deployed to execute complex tasks under extreme operating conditions. Their harsh working environments, stringent dynamic-response requirements, and high energy demand for mobility impose higher requirements on both the energy-regeneration efficiency and braking safety of the braking system. To address these issues, this article proposes an electro-hydraulic composite braking control strategy for four-axle electric-drive special vehicles. First, a braking axle-load transfer model for the four-axle electric-drive special vehicle is established, enabling axle-to-axle braking force distribution based on axle loads. Second, considering the motor torque characteristics and battery charging characteristics and by establishing an anti-lock braking prediction model, an electro-hydraulic composite braking torque allocation strategy with safety-range constraints on motor braking torque is designed. Then, to enhance vehicle safety during emergency braking, an adaptive super-twisting sliding-mode variable-structure anti-lock braking system (ABS) controller is proposed, and based on this ABS controller, an emergency braking control strategy is developed in which the motor braking torque is pre-reduced to within a safe range, with motor-dominant and hydraulic auxiliary modulation. Finally, simulation and real-vehicle tests demonstrate that the proposed electro-hydraulic composite braking control strategy improves the motor braking energy recovery rate under service braking conditions, reduces the braking distance, and enhances braking safety under emergency braking conditions.
Jin, Liqiang, Peng, Jinxin, Ke, Yuan, Peng, Silun, Li, Jianhua, Xiao, Feng
Rollovers are among the most severe road crashes, often leading to high fatalities and significant property damage, as reported by government and insurance agencies. This study investigates the impact of curve geometry and loading conditions on the rollover stability of a two-axle truck using validated vehicle dynamics simulations. The research highlights the importance of providing adequate curve radii and shows that larger radii are required to ensure design consistency. The study reveals that a 1 cm increase in center-of-gravity height results in a 0.82% decrease in the margin of safety against rollover, and that loading the truck to 93.75% of its full capacity over an equivalent platform length is the most critical loading condition in terms of rollover stability. To enhance safety, predictive models for lateral acceleration are developed along with geometric design consistency evaluation criteria based on vehicle rollover stability. Design guidelines for consistent curve design are also proposed. These models and criteria guide strategic improvements in road geometry, including optimized placement of rollover caution signage and targeted infrastructure refinements. The study underscores the need for enhanced curve design standards to improve truck stability and driver comfort while providing essential tools for advancing highway safety and mitigating rollover risks for heavy vehicles.
Remya, Y. K., Jacob, Anitha, Subaida, E. A.
J1979 DBCJ1979DBC_2026099/16/2026
The SAE J1979 DBC file contains decoding rules for converting raw J1979 data to 'physical values' (MPH, %, etc.). This file lets you easily decode data from passenger vehicles and heavy-duty vehicles that employ the J1979_2 protocol. This DBC file download includes: The SAE J1979 DBC file includes 250+ single-frame PIDs and 2250+ Signals defined in the J1979 DA released in October 2025. One legal license (1 user, 1 PC) matching the DA license, based on an annual subscription. DECODE J1979: Convert J1979 data in wide range of software/API tools REVIEW FIRST: Use our CAN ID converter to check if your PIDs are covered CROWD INPUT: Benefit from free corrections based on large user base SAVE HOURS: Avoid manually constructing the DBC file from scratch for improved Accuracy & Reliability. The file will be kept up-to-date as new J1979DA additions are approved. A standardized DBC file ensures accurate signal decoding, eliminating errors and ensuring reliable data interpretation. Partnership with DG Technologies Developed by DG Technologies, this dbc is seamlessly compatible with many different software stacks, enabling frictionless adoption and significantly expanding market reach. What is a DBC file? A DBC file is a standardized method for storing the "rules" on how to interpret raw CAN bus data. It contains the details needed to fully decode the signals, including names, descriptions, positions, lengths, offset and scaling are included in the DBC.
This study presents a shared vehicle scheduling model designed to tackle scheduling conflicts arising from changes in orders for bulky waste collection and transportation. The model accounts for five types of interference events: alterations in the original order location, modifications to the time window, changes in waste size, the inclusion of new orders, and order cancellations. The goal of the model is to reduce variations in the frequency of collection and transportation, minimize costs, and meet the three requirements of three-dimensional loading for shared trucks, as well as satisfy user time windows. To solve this complex combinatorial optimization problem, the sparrow search algorithm is employed. Numerical studies indicate that the proposed method outperforms the genetic simulated annealing algorithm in objective function value and computational efficiency under the five interference scenarios. These results also confirm the model’s efficacy.
Xu, Chen, Ma, Huimin
To analyze the handling stability of an 8×4 heavy-duty truck, a multi- body dynamics model of the heavy truck was established in ADAMS. Simulation tests for minimum turning radius, double lane change, steering wheel step input, and steady-state returnability were conducted on this model. Analysis of the simulation and experimental results revealed that, except for the significant discrepancy between the rigid-flex coupling model simulation results and the actual values in the returnability experiment, other experimental results were relatively close to the simulation data, indicating that the established vehicle model has high accuracy. It can provide a basis for the subsequent optimization design of this vehicle type.
He, Wenjian, Dong, Fulong
To solve the multiple conflicts between user requirements and structural constraints in the new frame structure design of electric heavy-duty trucks, this research proposes a conceptual design methodology that integrates modular design theory, quality function deployment, and TRIZ theory. Firstly, the quality function deployment approach is employed to construct the requirement- technology priority matrix, translating the system of user requirements for electric heavy-duty trucks into specific engineering characteristics. Supported by modular design theory, foundation reusable modules and specialized modules requiring optimization in traditional heavy truck chassis are identified. Then, a three- dimensional requirements-space-technology heat map accurately reveals key design collisions. Furthermore, TRIZ theory is applied to extract relevant engineering parameters and leverage the contradiction matrix for rapid acquisition of innovative solutions, thereby standardizing the conceptual design process, optimizing its implementation, and improving design efficiency during product development.
Sun, Lei, Huang, Wei, Zhu, Baoli, Jin, Zhenye, Guo, Shouwu, Feng, Yu, Chen, Xianlong
As one of the important freight modes, heavy trucks need a high- strength and high-reliability drive system to carry huge goods. Therefore, the drive axle housing, a key component, significantly influences the performance and service life of vehicles, and its design and optimization have high practical significance. Firstly, this study begins by creating a geometric model of the axle housing using SW and analyzes its stress distribution under four typical operational conditions. Through static analysis, it is concluded that the most critical operational conditions are the maximum deformation of 2.151 mm and the peak stress of 272.3 MPa; in the fatigue analysis of ANSYS Workbench, the minimum life is 820,000 times. Results from both static and fatigue assessments indicate that the initial axle housing design satisfies stiffness, strength, and fatigue requirements. There is a large margin in the structure, which has certain optimization space. Considering the most dangerous working condition, the response surface optimization module of ANSYS Workbench is used with the objective of mass reduction. Finally, the axle housing is reduced by 4.09 kg; the corresponding maximum deformation is 2.262 mm, meeting stiffness criteria, while the peak equivalent stress reaches 280.3 MPa, remaining below the material's yield strength. The minimum life is about 620,000 times, and the maximum fatigue life is 1 million times, which still meets the requirements of the vertical bending fatigue test. This lightweight redesign reduces material and manufacturing costs while maintaining the requirements for deformation, stress, and fatigue strength.
Zhao, Shenglian, Zhong, Weijie, Zhang, Jian
Research on automatic emergency braking (AEB) control algorithms for heavy vehicles is relatively limited. Compared with passenger cars, heavy vehicle AEB algorithms must accommodate both unloaded and fully loaded conditions, with the latter posing higher demands. This study compares two distinct AEB control strategies: the time-to-collision (TTC) algorithm and the professional driver fitted (PDF) algorithm. Using simulation analyses under three regulatory-recommended scenarios—stationary lead vehicle, slow-moving lead vehicle, and decelerating lead vehicle—the results indicate that the PDF-based control system better adapts to both unloaded and fully loaded conditions. It demonstrates significant improvements in braking performance and robustness compared to the TTC-based system. For an unloaded vehicle equipped with the PDF–AEB control system (5500 kg), the final gap to the lead vehicle is the longest (11.5 m) under the scenario of a stationary lead vehicle with an initial ego vehicle speed of 80 km/h and the shortest (3.1 m) under the scenario of a lead vehicle with an initial speed of 50 km/h braking at 0.4 g. For a fully loaded vehicle (12,500 kg), the corresponding final gaps to the lead vehicle are 11.2 m and 2.5 m, respectively.
Lai, Fei, Huang, Chaoqun
SAE TOMORROW TODAY - Is Megawatt Charging the Missing Link to EV Scalability?135828/27/2026
As electrification expands beyond passenger vehicles to commercial trucks, mining equipment, marine vessels, and even aircraft, the challenge is no longer whether megawatt charging is possible, it's how to scale it safely and efficiently. Fortunately, industry standards are making that future possible. Listen in as we sit down with Ted Bohn, Principal Electrical Engineer at Argonne National Laboratory and Chair of the SAE J3271 Committee, to discuss the Megawatt Charging System (MCS) and how collaboration across industries is laying the foundation for high-power charging that works across multiple transportation sectors. This conversation offers a behind-the-scenes look at how standards are developed, tested, and validated, and why scalable charging depends on much more than the connector itself. Whether you're designing commercial EVs, deploying charging infrastructure, or following the future of heavy-duty Class 8 electrification, this episode provides valuable insight into the technologies and standards that will shape the next generation of mobility. Have your own thoughts on this topic? 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
Semi-trailers are widely used in highway freight transportation because of their large payload capacity and high transport efficiency. However, structural characteristics such as a high center of gravity (CG), heavy loads, and the dynamic coupling between the tractor and trailer make them prone to yaw instability and rollover under complex conditions. To solve these problems, this article proposes a hierarchical stability control architecture for semi-trailers based on the joint estimation of equivalent parameters. First, a six-degree-of-freedom (6-DOF) theoretical dynamic model is established. This model includes the lateral, yaw, and roll motions of both the tractor and trailer to provide desired reference states. Second, a parameter estimation method combining a genetic algorithm (GA) with a forgetting-factor recursive least squares (RLS) algorithm is designed. It dynamically identifies eight unknown equivalent parameters, specifically the tire cornering stiffness and suspension damping. Next, a hierarchical controller is developed. The upper layer uses model predictive control (MPC) to calculate the required additional yaw moments, while the lower layer allocates these moments through quadratic programming (QP) based on vehicle steering characteristics. Co-simulation results, evaluated using error metrics that compare control outputs directly against TruckSim reference outputs, show that the fusion GA-RLS method offers better accuracy and adaptability than a standalone GA. Furthermore, the stability controller prevents rollover in high-speed maneuvers and reduces peak state indicators by over 41.2% in low-speed scenarios. Robustness tests also confirm its effectiveness under low-adhesion road conditions and heavy payloads. Compared with a conventional fixed-parameter MPC, the proposed adaptive architecture improves key stability indicators by 19% to 25%, effectively enhancing the dynamic safety of semi-trailers.
Song, Dafeng, Ni, Lixin, Duan, Chaosheng, Zeng, Xiaohua
I wanted to return to the topic from last month's column, my visit to the annual Summit of the International Transport Forum, the world's largest gathering of transport ministers and a global transport policy event, in Leipzig, Germany. Since there wasn't a lot of news directly related to automotive engineering news, I wanted to share a bit from this high-level event through editorial privilege. It was interesting to hear from some of the people in charge around the world as they shared their views on our current transportation situation and what they are doing to affect the future. At a panel on EV expansion, for example, the people in the room seemed to agree that the commercial EV industry has moved beyond proving the viability of battery-electric trucks and is shifting focus to overcoming infrastructure, regulatory, and systems integration challenges that continue to limit large-scale deployment. Even better, for those of us who've been listening to the arguments for and against electric vehicles for multiple decades now, representatives from across the industry - including logistics providers, vehicle manufacturers, charging companies, and policy groups - said that zero-emission freight transport has become a business strategy today, more so than any sort of sustainability effort as it might have been in years past. In the same vein, what might have been a battery-electric transport pilot program in 2016 can today be integrated into an organization's core freight operations.
Blanco, Sebastian
KPIT experts address challenges of maintaining legacy architectures while introducing centralized compute, OTA, new energy platforms and AI layers - driving integration complexity and validation effort. KPIT Technologies is providing the executive leadership for this year's SAE COMVEC, a forum for global leaders in trucking, construction equipment, agricultural machinery and defense vehicles to address the technologies, regulations and innovations impacting transportation today and in the coming years. The theme for COMVEC 2026 (www.sae.org/events/comvec), which takes place in Schaumburg, Illinois, from September 29 to October 1, is “Resolving Current Challenges While Reimagining the Future.” “For commercial and off-highway, this theme captures a structural contradiction the industry lives with every day: transform the entire product architecture while continuing to deliver near-zero downtime, tight margins and proven reliability,” Satish Kumar, senior VP at KPIT, said in a pre-event interview with Truck & Off-Highway Engineering.
Gehm, Ryan
At the ACT Expo in Las Vegas, Rivian CEO RJ Scaringe said that the coming R2 pickup would help pay for the company's massive R&D budget. He said that budget was the result of a conscious decision to design and build the majority of items for its trucks and SUVs in-house. Scaringe joined Erik Neandross, president of TRC's Clean Transportation Solutions Group, for a fireside chat reflecting on Rivian's journey and its future.
Clonts, Chris
The trucking industry is dealing with a lot of uncertainty, and higher fuel and equipment costs are making it harder for companies to plan and buy new trucks. What can OEMs and fleet operators do to mitigate these challenges? Hybrid systems may be the answer. With internal combustion and electric power, hybrid systems reduce fuel consumption, improve transient performance, enable low-speed electric operation and create more flexible power management. Vehicles and equipment that could benefit from new or retrofit hybrid systems include refuse trucks, dump trucks, long-haul trucks, port equipment, excavators, terminal tractors and commercial delivery vehicles.
Glass, Jason
In the conversation surrounding electrification, the vehicle itself typically dominates the headlines. But those operating on remote jobsites in the mining, construction and agriculture sectors know the machine is only half the equation. These industries prioritize reliability and uptime and require machines that can handle grueling shifts in demanding environments without compromise. Power providers in these heavy-duty, off-highway markets must move beyond the battery itself to explore a holistic approach to infrastructure when it comes to powering remote jobsites. The first step to success is understanding the fundamental differences between off-highway duty cycles and on-highway applications. While on-highway applications like long-hauling trucks benefit from steady-state operation and passive airflow for cooling, off-highway machines often operate at high torque for extended periods, with little to no forward movement. In these scenarios, there is no passive cooling to rely on or regular refueling stations at the next exit. Success, therefore, is defined by the engineering required to ensure that electric machines deliver the same productivity as diesel, even when operated at their limits in the most rugged, remote conditions.
Moore, Preston
In the process of replacing the rollers of the fabric cart of the tobacco storage cabinet, in order to solve the problems of low replacement efficiency and high safety risk.This article proposes a specialized lifting tool for fabric cart rollers with a self-locking and adopts the screw lifting structure, which facilitates roller maintenance operations, and conducts SolidWorks Simulation calculations and dynamic simulation methods. Jinan Cigarette Factory fine cigarettes special line leaf silk temporary storage cabinet fabric car roller replacement, for example, the results show that: the average operating personnel reduced by 50%, the replacement time from 6.7h to 1.2h, efficiency increased by 458%, This innovation significantly reduces the labor intensity of maintenance personnel and ensures a safe and reliable replacement process.
Zhang, Lei, Xue, Yifei, Zhang, Ge, Sun, Yanzhao, Wang, Hongbin, Cheng, Linfeng
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
In response to the problem of manual transmission rattle noise in the acceleration process of a truck, the mechanism of the problem is analysed, and the scheme is developed and verified from two aspects: reducing the torsional vibration of the system and reducing the response of the transmission gear. The results show that, on the one hand, reducing the clutch stiffness and optimizing the torsional vibration of the system can reduce the rattle noise of the transmission; On the other hand, it can also reduce the rattle noise of transmission gears by improving the engagement precision of transmission gears and reducing the gear clearance. Considering the improvement effect, cost, and influence on other performance of the two schemes, the appropriate engineering scheme is selected to effectively solve the problem and improve the riding comfort of the product.
Yang, Zhijie, Xu, Binghua
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
Kolmogorov-Arnold Networks (KANs) are a novel mathematical method to generate data-driven AI surrogate models. Compared to neural networks based on the MLP standard (Multi-Layer Perceptron), these offer further mathematical interpretability and thus allow improved validation of AI for industrial applications. In this paper, we use KANs to generate an AI vehicle model of a truck as a mathematically precise AI surrogate model. To do this, we combine the KAN approach with the approach of Neural Ordinary Differential Equations (Neural ODEs) to generate predictions for the time-series of the truck’s velocity. Furthermore, we compare the results of the AI based on KANs with the traditional approach using MLP in terms of model size, accuracy, and computational time in order to evaluate advantages and disadvantages of the KAN approach. The best AI-KAN vehicle model identified in this way is then embedded in a co-simulation via the Functional Mockup Interface standard, thus opening up a wide range of applications in AI-driven truck development.
Vaudrevange, Patrick K.S., Halverson, James, Ruehle, Fabian, Fabcic, Tomaz, Dingler, Christian, Piskala Dilipkumar, Santhoshkumar, Ibrahim, Muhammed, Herrnberger, Michael, Kasper, Johanna, Türk, Lars, Keckeisen, Michael
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
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
Vehicle fleet decarbonization is a key objective for the coming years, with electrification representing the primary pathway to achieving the targets set by the European Union. The share of battery electric trucks in new registrations has been gradually increasing especially in light and medium size trucks. The replacement rate of diesel long-haul trucks with zero emission trucks is still low due to challenges posed by added complexity and limitations of battery charging. Depot overnight charging is not sufficient to cover the energy needs of a truck covering large distances and careful planning of the route using public charging infrastructure is crucial for an optimized route minimizing extra costs and range anxiety. The current work aims to develop a methodology to propose the optimal charging locations for a given route of a battery electric truck based on nearby stations along the route. Our study uses an open-source optimization algorithm for the fixed route vehicle charging problem coupled with a powertrain simulation model that is used to calculate the energy consumption and the electric range of the vehicles. A variety of constraints, such as initial State of Charge, lowest allowed State of Charge threshold, maximum trip duration, distance deviation, have been implemented in different scenarios from real world locations with a goal to investigate the impact of planning constraints and charging infrastructure in the optimal planning of electric truck routing. The results of our analysis indicate that the integration of an accurate energy consumption calculation model to a route and charging optimisation algorithm can be proven beneficial for minimizing the time penalty due to charging.
Perdikopoulos, Michail, Doulgeris, Stylianos, Livitsanos, Georgios, Kazakis, Thomas, Mellios, Giorgos, Ntziachristos, Leonidas
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
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
Volvo Trucks' revised VNR brings updated safety tech, improved fuel economy and driver comfort features to the regional haul segment. Volvo Trucks has continued its rollout of new models for every sector of the commercial truck market. The redesigned VNR is the latest model to see the spotlight. The new VNR naturally carries all of Volvo's latest safety tech, but also prioritizes maneuverability, fuel efficiency and configurability for a wide variety of fleet uses. “The VNR is an incredibly versatile truck,” said Maddie Sullivan, product marketing manager. “There are so many different configurations to meet our customer's needs. We offer four different cab sizes, three different axle configurations and two different chassis configurations.”
Wolfe, Matt
OEMs, integrators and suppliers must continuously process, assess and identify platform vulnerabilities to prioritize and implement updates that protect systems from cyberattacks and data breaches. Security researchers have demonstrated that the control systems in vehicles and machines are open to attack. In 2010, researchers from the University of Washington and the University of California, San Diego demonstrated that by gaining physical access to a vehicle, they could manipulate critical systems like brakes and engines. Just a few years later, security researchers Charlie Miller and Chris Valasek remotely compromised a vehicle over the internet, controlling steering, braking and acceleration, leading to a 1.4 million vehicle recall. In 2024, researchers at Colorado State University successfully demonstrated a wireless drive-by hack by exploiting vulnerabilities in common electronic logging devices (ELDs). In their proof-of-concept test, they achieved remote control over a truck by reflashing the ELD with malicious firmware, which allowed them to slow down a moving truck and show a design for a truck-to-truck worm virus that could theoretically spread through a fleet.
McGuirk, Finn
Kenworth's new C580 vocational truck made its debut at CONEXPO 2026. The C580 is the replacement for the long-serving C500 and aims to build on that truck's legacy thanks to new tech, more muscle and improved interior amenities. According to Kenworth, the C580 rides on the C500 platform, but has been endowed with Kenworth's latest cab, which brings modern comfort and technology features. Truck & Off-Highway Engineering was in attendance for Kenworth's introductory press conference for the C580 in Las Vegas.
Wolfe, Matt
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
Sustainability needs to be practical. That was a point Peter Voorhoeve, president of Volvo Trucks North America, made clear at CONEXPO 2026 in Las Vegas. “We're running a business, so we are focusing a lot on efficiency and uptime,” he said, referencing the up-to-10% improvement in fuel efficiency with the new VNL. “That helps our customers to run their operations at a better pace and a lower cost, but at the same time we have a very positive impact on the climate.” Voorhoeve also teased the launch of a new vocational truck. “We are strong in long haul. We are a leading sleeper manufacturer, very strong in regional haul, and we now have renewed focus on vocational,” he said. “In August we will launch a new truck specifically for the vocational segment that's built on the same platform as the VNL and VNR.” (See page 22 for our feature story on the new VNR.)
Gehm, Ryan
Harbinger revealed its HC Series Cab during Work Truck Week 2026 in Indianapolis, Indiana. The HC Series is a new line of medium-duty, low cab forward vehicles available as both an electric and plug-in hybrid model. Harbinger states that the HC Series' hybrid powertrain uses a range-extended hybrid platform with a gasoline engine to recharge the truck's batteries, extending range up to 500 miles (805 km), depending on upfit configuration and drive cycle.
Wolfe, Matt
We hear it often at industry events, in keynote speeches and during expert panel discussions: There is no silver bullet. Peter Voorhoeve, president of Volvo Trucks North America, says as much in this issue's Q&A (page 44). “Electric is one solution, but biodiesel is another solution, and hydrogen is, too. So we have these different fuel solutions to get to better sustainability.”
Gehm, Ryan
These days, no one blinks an eye at two-day, one-day, or even same-day package deliveries. Despite the plethora of localized fulfillment and distribution centers cropping up to meet demand, delivery trucks still need to make considerably long drives, often on highways. To reduce fuel and maintenance costs as well as carbon emissions, companies are investing in electric trucks for their delivery fleets. While turning to electric trucks is a promising solution, the battery packs incorporated into these automotive designs often fall short in the lifetime needed to make consistent long-distance highway travel feasible.
In the field of measuring carbon emissions from road traffic, the carbon emission factor method has remarkable advantages in terms of standardization, operational simplicity, and adaptability. Backed by the IPCC international standard framework, this method offers convenient access to a dynamic factor database and incorporates an adaptive adjustment mechanism for real-world scenarios, such as technological advancements and regional disparities. Against this backdrop, this study employs the carbon emission factor method to establish refined measurement models based on load capacity and fuel consumption, respectively. These models are then applied to quantify carbon emissions from trucks on specific sections of the G30 highway in Xinjiang. The load-based model calculates emissions by integrating truck axle weight and driving distance, while the fuel-based model analyzes fuel consumption data in conjunction with driving mileage. A comparison of the two models in terms of measurement differences is also carried out in the research. Furthermore, it provides a granular breakdown of energy consumption data for fully loaded trucks exceeding 31 tons, as specified by national standards. This introduces a novel approach to precise carbon emission measurement in heavy-duty transportation in northwestern China. It also provides a method for establishing an emission mitigation policy that is region-specific on a scientific basis.
Li, Maowen, Han, Dongchen, Gao, Yansen, Bai, Haotian, Dai, Xiaomin
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 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
Addressing issues in traditional hybrid light trucks—such as low overall energy utilization efficiency and performance degradation of key components under extreme operating conditions—this study presents a novel, high-efficiency, integrated vehicle thermal management system. By coupling various subsystems, the system achieves efficient and rational utilization of the vehicle’s overall energy consumption. Comparative simulation analyses were conducted under different ambient temperatures and initial state-of-charge (SOC) levels to verify the reliability of the designed integrated thermal management system. Results show the system can meet the temperature requirements of all components under both high and low-temperature conditions. Meanwhile, findings indicate that ambient temperature and power modes have a substantial impact on the temperature of each component, and there is potential for utilizing motor waste heat. These outcomes provide a reference for the subsequent optimization of control strategies for thermal management systems in hybrid light trucks.
Meng, Shun, Zhang, Chunyu, Zhang, Yu, Zhang, Dong, Yao, Mingyao, Qiu, Liang, Wu, Yadong, Qian, Yejian
Fuel cell systems have achieved a significant level of technological maturity in ground-based mobility over the past two decades. In particular, commercially available fuel cell propulsion systems are now in serial production for passenger cars and city buses, and are already in regular commercial operation. In the segment of heavy-duty vehicles - such as trucks and other long-haul applications - small-series production and technology demonstrators are currently available and are on the verge of entering the mainstream market. These developments have resulted in well-proven system architectures, sophisticated balance-of-plant components, and established supply chains. In contrast, the utilization of fuel cell propulsion in aviation is still at a very early stage. At present, only a handful of individual prototypes and technology demonstrators - mostly for small aircraft - exist, while serial production remains far in the future. Particularly in the field of lightweight, small, electrical vertical take-off and landing (eVTOL) aircraft there is a unique opportunity to leverage the proven fuel cell systems developed for ground vehicles, adapt them, and further develop them to meet aviation-specific requirements. Such an approach can shorten development timelines and reduce technical risks. Transferring existing fuel cell technologies into aviation, however, is far from a straightforward process. One decisive difference lies in the required specific power density. Aircraft - especially eVTOL - demand significantly higher power densities than those delivered by current commercial fuel cell systems from the automotive sector. This requires a direct adjustment of the stack design and system architecture. Likewise, thermal management poses particular challenges. Whereas piston engines and gas turbines discharge a large portion of their waste heat via exhaust gases, fuel cells must remove all waste heat directly through their cooling systems. This requires efficient radiators capable of transferring heat from the coolant to ambient air. Larger radiator surfaces, however, increase both total aircraft mass and aerodynamic drag, making compact radiator designs essential for aviation applications.
Schmitz, Maximilian, Walters, Marius, Taron, Moritz, Eschmann, Christian
Cargo-focused autonomous Vertical Takeoff and Landing (VTOL) operations are advancing toward commercialization significantly faster than passenger missions due to a confluence of regulatory pragmatism, technical readiness, and market economics. This paper examines the commercial potential of integrating Artificial Intelligence (AI) and Beyond Visual Line of Sight (BVLOS) control into an Uncrewed VTOL Air Cargo (AI-UVAC) vehicle for dual use military and commercial logistics applications. The Piasecki KARGO II was designed specifically for these missions and is used as the basis for evaluating this capability. This AI-UVAC concept has useful commercial application in the "mid-weight Less than Truck Load (LTL)" freight market for middle-mile delivery of time-sensitive cargo in infrastructure-constrained markets. To validate the advantages of commercial freight orchestration, a multiphase pilot program is conducted to measure the effectiveness of the LogistiWerx Generative AI-Powered Freight Logistics Orchestration platform as integrated in the KARGO II uncrewed BVLOS VTOL developed by Piasecki Aircraft Corporation (PiAC).
Stanzione, Kaydon, Cavazzoni, Marco, Piasecki, John
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
This study investigated how vehicle front-end geometry, impact speed, and vehicle category influence injury risk to a midsize male pedestrian. Eighty-one generic vehicle (GV) models representing sedans, sport utility vehicles (SUVs), pickup trucks, and minivans sold in the United States were developed by morphing three base models using an automated pipeline. Front-end parameters that were varied included ground clearance (GC), bumper height (BH), hood leading-edge (HLE) height, hood length (HL), bumper lead angle (BLA), hood angle (HA), and windshield angle (WSA). Each vehicle impacted the Global Human Body Models Consortium 50th percentile male simplified pedestrian (GHBMC M50-PS) model at 30, 40, and 50 kph, totaling 243 simulations. Boundary conditions followed the European New Car Assessment Program (Euro NCAP) pedestrian test protocol. Thirty-five injury metrics were extracted across the head, neck, thorax, abdomen, pelvis, and lower extremities. Linear mixed-effects regression models assessed relationships between vehicle front-end geometry, impact speed, and injury outcomes, with predictor selection guided by principal component analysis (PCA) and collinearity diagnostics. Impact speed was the strongest predictor of injury severity across all body regions. GC and HLE height were also dominant predictors. Wrap-type trajectories were common at lower speeds and in SUVs, trucks, and minivans, while sedans and minivans showed roof vaulting at higher speeds. Head injury severity increased with speed and was influenced by HA and BLA. Minivans showed elevated brain injury criterion (BrIC) and cumulative strain damage measure (CSDM25) values, indicating increased diffuse brain injury risk. Trucks produced the highest thoracoabdominal injury metrics, which correlated with HL, HA, and HLE height. Sedans showed higher right-side (trailing leg) femur forces, slightly lower left-side femur forces than SUVs and minivans, and lowest tibia moments. Trucks had greater tibia bending moments, while SUVs and minivans had higher left femur moments compared to sedans. GC and impact speed exacerbated lower extremity injuries, varying by vehicle category. These effects are driven by geometry: Higher GC increases the unsupported span below the knee, promoting tibial bending, while lower HLE heights shift impact forces above the knee, elevating femur injury risk.
Poveda, Luis, Miller, Logan E., Edwards, Colin C., Pollock, Madeline, Armstrong, William M., Hsu, Fang-Chi, Gayzik, Scott F., Weaver, Ashley A., Stitzel, Joel D., Devane, Karan S.
This study investigates the gradeability performance of an L7e-class electric micro truck from both vehicle dynamics and thermal perspectives. A 1D simulation model (Amesim) was developed and validated with multiple test results. Using inputs such as motor characteristics, drivetrain configuration, and vehicle mass, the model analyzed vehicle performance on a 20% gradient, calculating the required torque, achievable motor speed, and corresponding vehicle speed. Furthermore, gradeability limits were evaluated, and the effects of gear ratio and airflow rate around the air-cooled motor on both gradeability and thermal behavior were examined. The findings provide practical insights for improving the powertrain and cooling system design of lightweight electric vehicles. The results showed that selecting an appropriate gear ratio can enable the motor to operate more efficiently under demanding driving conditions. A 20% increase in the gear ratio was found to delay motor heating by up to 10%. However, its effect was observed to be negative under driving conditions such as WLTP, which require variable RPM demand.
Turan, Azim, Kantaroğlu, Hasan Hüseyin, Akbaba, Mahir, Kasım, Recep Faruk, Yarar, Göktuğ
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