Browse Topic: Trucks

Items (5,975)

Design and Application of Simulation-Based Lifting Tool for Fabric Truck Roller Replacement

2026-99-0137

7/31/2026

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

Model-Based Optimization and Evaluation of Hybrid Powertrains for Commercial Heavy-Duty Class 8 Truck Applications

02-19-04-0025

7/27/2026

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

Analysis and Improvement of Rattle Noise in Manual Transmission

2026-99-0527

7/10/2026

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

Kolmogorov-Arnold Networks in Industrial Application of Truck Development

2026-01-0760

7/1/2026

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

Improved Thermal Management for Operating a Battery Electric City Bus under Real Driving Conditions

2026-01-0758

7/1/2026

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 Variability

2026-01-0690

6/20/2026

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

SAE Truck & Off-Highway Engineering: June 2026

26TOFHP066/11/2026

Hitting the road in the all-new VNR Volvo Trucks' revised VNR brings updated safety tech, improved fuel economy and driver comfort features to the regional haul segment. In fuel control How to ensure off-highway combustion systems operate with sufficient control to meet tightening emissions standards and evolving fuel landscapes without sacrificing reliability. Keeping industrial vehicles secure in a digital landscape 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. Editorial Diversification key for sustainable fleets ACT 2026: Uncertainty still exists over EPA 2027 NOx limit ZF bets big on hybrid transmissions Moog simplifies off-highway electrification Bosch shows off its first U.S. electrolyzer Microvision fast-tracks adoption of Luminar tech; eyes defense, industrial sectors Future-ready, customizable connectivity powers precision agriculture Kenworth's new C580 clocks in for work Harbinger extends its range of medium-duty EVs Kubota's SVL110-3 brings new tech and service features to CTL segment Product Briefs SPOTLIGHTS: Diesel Engines & Subsystems; Manufacturing Tools & Materials; Motors, Inverters & Gearboxes Q&A Volvo turns attention to vocational trucks

Development of a Diesel Combustion System for Next-Generation Heavy-Duty Engines Using a Synergistic Analysis-and-Testing Approach

2026-37-0004

6/9/2026

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

Optimal Charging Planning with Energy Consumption Simulation for Battery Electric Long-Haul Trucks

2026-37-0019

6/9/2026

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

Driveline Parking Brake Test Procedure for Medium Duty Vehicles

J2690_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

Hitting the road IN THE ALL-NEW VNR

26TOFHP06_01

6/1/2026

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

Keeping industrial vehicles secure in a digital landscape

26TOFHP06_03

6/1/2026

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 clocks in for work

26TOFHP06_11

6/1/2026

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 bets big on hybrid transmissions

26TOFHP06_06

6/1/2026

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

Q&A

26TOFHP06_15

6/1/2026

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 extends its range of medium-duty EVs

26TOFHP06_12

6/1/2026

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

EDITORIAL: Diversification key for sustainable fleets

26TOFHP06_04

6/1/2026

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

Side Turn Signal Lamp for Long Vehicles

J2039_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

Research on Carbon Emission Calculation Algorithm for Trucks on Expressways in Xinjiang

2026-99-1718

5/22/2026

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

Design And Analysis of Low-Temperature Liquid Nitrogen Tank Car

2026-99-1712

5/22/2026

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 China

13-07-01-0003

5/22/2026

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

Design and Performance Research of an Integrated Thermal Management System for Hybrid Electric Light Trucks

2026-99-0735

5/15/2026

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

Generative AI-Powered Freight Orchestration for Operating the Uncrewed Piasecki KARGO II

F-0082-2026-0254

5/5/2026

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

Adapting Automotive Fuel Cell Technology for Next-Generation VTOL Light Aircraft: Challenges and Opportunities

F-0082-2026-0221

5/5/2026

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

Characterization of Fatal Cyclist Collisions Involving Nine Vehicle Types Traveling at Low and High Speeds in Japan

09-14-01-0005

5/4/2026

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

Effects of Vehicle Speed, Category, and Front-End Design on Full-Body Injury Risks of a Midsized Male Pedestrian

09-14-01-0017

5/4/2026

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.

Thermal Management of Electric Microtruck Motors

2026-01-5026

4/9/2026

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

Energy-Efficient Predictive Cruise Control in Heavy-Duty Electric Trucks with Optimization of the Penalty Factor as a Function of Payload

2026-01-0042

4/7/2026

Heavy-duty Class 8 battery electric trucks not only offer the potential to significantly reduce greenhouse gas (GHG) emissions compared to conventional diesel trucks but can also provide significant savings in fuel costs. To further enhance energy and freight efficiency, Predictive Cruise Control (PCC) algorithms can be developed that generate optimal acceleration profiles for the vehicle by minimizing a cost function which combines both energy consumption and deviation from the desired velocity. A critical component of the cost function is the penalty factor, which governs the tradeoff between energy use and travel time, which are two conflicting objectives in freight logistics. Selecting an appropriate penalty factor is essential, as freight deliveries are time sensitive, but minimizing energy consumption remains a priority. Moreover, variations in payload significantly affect vehicle dynamics and energy usage, making it critical to adapt the penalty factor to different payload conditions and maintain consistent performance. This study presents a method for optimally selecting the penalty factor for various payload scenarios. A validated powertrain simulator which is calibrated using data from an actual electric truck, was used to conduct 100 simulations across a spectrum of payloads, from no load to fully loaded. The resulting discrete search space of energy and time was used to perform a brute-force (exhaustive) search to determine the optimal penalty factor for each scenario. The proposed algorithm incorporates adjustable weightings of the penalty factor for energy and time preferences. This allows flexibility for the driver or fleet operator to prioritize either objective. The results demonstrate that using a fixed penalty factor is suboptimal for heavy-duty electric trucks. In contrast, the optimal selection of the penalty factor significantly improves consistency across different payloads. A reduction of the variation in travel time to within approximately 4% across all loading conditions was observed. This work shows the importance of adaptive penalty tuning in PCC for real-world deployment in freight applications, ensuring both energy efficiency and timely deliveries under varying payload demands.

Safder, Ahmad Hussain, Villani, Manfredi, Wang, Eric, Khuntia, Satvik, Nelson, James, Meijer, Maarten, Ahmed, Qadeer

Application of Reliability Growth Methods in Conjunction with Design for Reliability Framework to Validate Heavy Truck Design

2026-01-0137

4/7/2026

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

Energy Management Strategy for Hybrid Mining Trucks Based on Global SOC Planning and Neural Network Optimal Control

2026-01-0446

4/7/2026

Hybrid mining trucks, as core equipment for mine transportation, face high energy consumption and significant fluctuations in power demand during cyclic operations due to prolonged exposure to demanding operating conditions characterized by heavy loads and variable working conditions. To address the issues of high energy consumption and significant fluctuations in power demand during the cyclic operation of mining trucks, this paper proposes a hybrid mining truck energy management strategy based on global SOC (State of Charge) planning and neural network optimization control. First, a powertrain model was developed for a typical operating cycle of a hybrid mining truck, and its accuracy was validated by comparing it with experimental data. Using dynamic programming algorithms to plan the SOC for single-cycle operations provides a rational reference for energy allocation across different operational phases of mining trucks during a single cycle. Next, using the powerful nonlinear mapping and self-learning capabilities of neural networks, the system learns the optimal power output sequence of the range extender during offline computation. This enables rapid decision-making and adaptive adjustment of power allocation between the range extender and battery in real-time applications, thereby effectively reducing energy consumption under cyclic operating conditions. Design a SOC tracking controller to adjust the output of the neural network optimization controller, thereby achieving tracking of the planned global SOC. Finally, validated through simulations and real vehicle tests, the proposed energy management strategy can improve fuel economy, achieving a 1.27% fuel saving compared to traditional rule-based strategies in real vehicle tests. This study provides a feasible energy management scheme for the green and efficient operation of heavy mining vehicles.

Yang, Jianyu, Zhao, Zhiguo, Chen, Huiyong, Li, Tao, Zhuang, Wenyu, Shen, Peihong, Tang, Peng

Quantifying the Impact of Towing on BEV Energy Use: Instrumented On Road Testing and Chassis Dynamometer Reproduction

2026-01-0431

4/7/2026

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

The Stellantis North America Aero-Acoustic Wind Tunnel Upgrade

2026-01-0609

4/7/2026

The Stellantis North America Aero-Acoustic Wind Tunnel (AAWT) has been upgraded with a cutting-edge 5-belt Moving Ground Plane (MGP) system, featuring an 8.5-meter center belt and four Wheel Spinning Unit (WSU) belts with advanced coatings for durability and visibility. The expanded 9.4-meter turntable enables ±90° yaw and supports vehicles with wheelbases from 1800 mm to 4500 mm and weights up to 5000 kg, accommodating the full Stellantis North America product range. The original 2-stage boundary layer control system was retained, with new tertiary slots added for improved flow quality. A high-stiffness, six-component Horiba balance with integrated calibration weights and tractive force measurement ensures accurate and precise measurements. Facility enhancements include a 550 m2 building addition for equipment and vehicle prep, a dedicated compressor container for clean air supply, and a vehicle underbody wash booth for efficient cleaning. Commissioning confirmed that flow quality, axial static pressure distribution, and acoustic background noise meet or exceed system specifications. Operational since October 2024, the upgraded AAWT now delivers world-class aerodynamic and acoustic testing capabilities, with enhanced automation, safety, and efficiency.

Lounsberry, Todd, Ladouceur, Brent, Fadler, Gregory

Model-Based Development of a Heavy-Duty H ₂ -ICE and Integrated, Turbogeneration, Electrification, and Supercharging (ITES) System

2026-01-0426

4/7/2026

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

Look-Ahead Information based Predictive Cruise Controller for Energy Efficient Powertrain Operation of Heavy-Duty Electric Trucks

2026-01-0039

4/7/2026

Heavy-duty electric trucks represent a growing innovation in the transport and logistics sector, aiming to reduce emissions and reliance on fossil fuels. A major challenge with battery electric trucks is the long recharging time which takes significantly longer than refueling conventional diesel trucks. This limitation highlights the importance of optimizing powertrain operations to reduce energy losses and maximize efficiency. One effective approach is implementing optimal speed control through a predictive cruise controller. By anticipating road conditions, traffic, and elevation changes, the predictive cruise controller can adjust the truck’s speed in real time to minimize energy consumption, enhancing the range and reducing the need for frequent charging. Many problem formulations for electric trucks focus primarily on minimizing the energy required at the wheels, often overlooking the impact of powertrain efficiencies. This simplification neglects critical factors such as the efficiency of the traction electric machine (EM), gear losses, and battery dynamics, which are essential for optimizing overall energy consumption and improving vehicle performance. This research paper shows the impact of powertrain efficiencies on the optimal speed profile generation with a predictive cruise controller (PCC). The PCC optimizes electric truck operation by focusing on three primary factors in its cost function: 1) battery energy consumption, 2) total trip time, and 3) battery state of charge (SOC). To achieve the optimal speed profile, Sequential Quadratic Programming (SQP) is used. A comparison was made with a conventional cruise controller, which simplifies the vehicle model by minimizing the required energy at wheels and ignores powertrain losses in its energy calculations. The results show that the proposed PCC offers a 12.85% improvement in battery SOC and 10.83 % improvement in energy consumption as compared to baseline.

Safder, Ahmad Hussain, Villani, Manfredi, Khuntia, Satvik, Nelson, James, Meijer, Maarten, Ahmed, Qadeer

Techno-Economic Evaluation of Electrified Vehicle Options in Drayage Fleets

2026-01-0454

4/7/2026

The electrification of drayage fleets offers potential economic and operational benefits, but the financial viability of electrified vehicles remains sensitive to battery cost, energy price, and fleet usage patterns. While total cost of ownership (TCO) is a useful benchmark, fleet operators and investors are equally concerned with investment performance metrics such as payback period (PB) and Internal Rate of Return (IRR), which better reflect financial risks and investment return timelines. This study develops a unified techno-economic framework that jointly evaluates TCO, PB, and IRR to determine when electrified trucks become cost-effective alternatives to diesel trucks. Building on a previously developed cost modeling tool and using real-world telematics data from a Class 8 drayage fleet at the Port of Savannah, the analysis incorporates projected battery cost trajectories, electricity and diesel price trends, vehicle efficiency improvements, and multiple battery capacities. Parameter ranges reflect widely cited projections and observed drayage-duty-cycle variability. A surrogate-modeling method approximates economic performance across thousands of battery cost–electricity price combinations, enabling high-resolution identification of conditions that achieve TCO parity, acceptable PB thresholds, and target IRR levels. Additionally, the study estimates the evolving share of the fleet that can feasibly electrify over time under multiple economic metrics. This integrated framework offers a novel, data-driven approach to inform risk-aware decision-making for fleet electrification and supports investment planning under evolving cost and operational conditions.

Sun, Ruixiao, Sujan, Vivek, Goulet, Nathan, Wang, Qixing

Multi-Physics Topology Optimization and Neural Network–Based Design of Experiments for Lightweight Automotive Cast Components

2026-01-0510

4/7/2026

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 Cell

2026-01-0434

4/7/2026

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 Bore

2026-01-0280

4/7/2026

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

Agile Safety Case Assessments for Autonomous Vehicle Fleets

2026-01-0521

4/7/2026

Rapidly upcoming deployment of autonomous vehicles (AVs), including robotaxis and trucks, has intensified the need for rigorous safety assessment of complex AI-driven systems. While considerable effort has been invested in constructing safety cases for AVs, systematic approaches for evaluating these safety cases remain underdeveloped. This paper presents a three-stage methodology for assessing AV safety cases. A process for assessing argumentation is presented that involves traceability to pre-reviewed and peer-reviewed safety cases such as the Open Autonomy Safety Case (OASC). Next, we present a structured process for evaluating the quality of evidence supporting these arguments. We applied this methodology to evaluate safety cases from multiple AV developers, enabling iterative refinement throughout the development lifecycle. Our agile approach supports efficient assessments by establishing clear traceability to industry standards and enabling early identification of potential gaps. This work provides regulators, operators, and developers with a practical framework for systematically evaluating AV safety cases and identifies lessons learned and areas for continued improvement.

Wagner, Michael

Sideslip Angle Estimation for Mining Trucks Based on Real-Time Cornering Stiffness Identification

2026-01-0618

4/7/2026

High-precision estimation of key vehicle–road state parameters is crucial for ensuring the accurate and safe control of mining trucks (MT), as well as for reliable trajectory tracking. Among these parameters, the vehicle sideslip angle is particularly critical for assessing and predicting lateral stability. However, its direct measurement is challenging, and its estimation typically depends on an accurate characterization of tire cornering stiffness. For MT, large variations in loading conditions (from empty to fully loaded) pose significant challenges to sideslip angle estimation due to the resulting nonlinearity and variability of tire cornering stiffness. To address this issue, a novel joint estimation framework integrating the Moving Horizon Estimation (MHE) and Square-Root Cubature Kalman Filter (SCKF) is proposed to simultaneously achieve high-precision estimation of both tire cornering stiffness for each tire and vehicle sideslip angle. In this framework, the cornering stiffness of the front, middle, and rear axles is identified and updated in real time using MHE through a forgetting-factor least squares method based on yaw rate and lateral acceleration data within a fixed-length time window. The updated stiffness is then incorporated into the SCKF for accurate estimation of the sideslip angle. This sequential process effectively establishes a coupling between the estimation of the two parameters, forming an integrated joint estimation mechanism. The proposed framework is validated on the TruckSim–Simulink co-simulation platform, and the results confirm its superior accuracy and robustness, demonstrating its potential to improve the safety and control performance of MT.

Xia, Xue, Shen, Peihong, Jiao, Leqi, Li, Tao, Chen, Huiyong, Zhao, Kun, Jiao, Leqi, Zhao, Zhiguo

Experimental Evaluation of After-Treatment Solutions for Heavy-Duty Natural Gas Vehicles to Meet Future CNVII Regulations

2026-01-0376

4/7/2026

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

Dual Battery Pack System for Multi-Voltage Electric Vehicle Operation

2026-01-0392

4/7/2026

Electric Vehicles (EV) have become a major focus in the automotive industry. This paper introduces a propulsion system design, which supports the Wide Torque Band (WTB) concept to boost the power density of PM (permanent magnet) motors in EV Trucks resulting in performance, efficiency, and cost benefits. A selectable 400V/800V battery system has been developed to support the WTB concept and enhance the power density of permanent-magnet motors in electric vehicles. The RESS comprises two 400V battery packs that can be charged at 400V in parallel or at 800V in series via a DC fast-charging (DCFC) connection. In this study, an 800V driving mode was additionally implemented. A prototype battery management system (BMS) along with existing production voltage, current and temperature measurement block hardware are applied to perform mode switching, safety, and cell balancing. The success of this dual pack hardware enables high voltage dynamometer testing of a new 800V DU (Drive Unit) and inverters for EVs. The flexibility of switching between two voltage levels (400/800V) from the battery packs enables testing of both current 400V and future 800V drive systems in the same test cell. The control concepts developed for managing the dual packs were applied to convert a truck to operate at 800V using the native 24-module battery with modifications. Vehicle tests validated the BMS with this new feature.

Zhu, Yongjie, Lee, Chunhao, Gopalakrishnan, Suresh, Namuduri, Chandra

Camera Monitor System Soiling Correlation for a Class-8 Truck Using Lattice Boltzmann Method

2026-01-0596

4/7/2026

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

Optimization Method for Vehicle Shape to Drastically Reduce Aerodynamic Drag in Heavy-Duty Vehicles

2026-01-0603

4/7/2026

Since air drag is proportional to the square of the speed, it is expected that reducing air drag will significantly improve fuel efficiency for on-highway trucks and buses, which are often driven at high speeds. Therefore, the purpose of this study is to propose an optimization method for vehicle shape to drastically reduce aerodynamic drag in heavy-duty vehicles. Using NSGA-II, one of a genetic algorithm, the overall vehicle shape was optimized with drag coefficient (CD) and lift coefficient (CL) values as objective functions and design variables as parameters in a total of 13 locations. Among the Pareto solutions, an 86% reduction in CD was achieved compared to the base shape when the CD value was the lowest. Since the CL value remains low with this shape, it can be seen that driving stability does not deteriorate. Among the design variables in optimization, it was confirmed that the corner radius of the vehicle side was particularly effective in reducing the CD value. In addition, when optimizing only the cab shape, the optimal value for the front virtual angle was 30 deg., but in relation to the corner radius, the value for this optimized shape was around 40 deg. The CD value of a 1/20 model of the optimized shape was measured in a wind tunnel test and compared with the optimization results from the aforementioned numerical analysis. As a result, the CD value reduction effect of the optimization shape was confirmed in the wind tunnel test as well, demonstrating the validity of the optimization results described above. In addition, an investigation into the yaw angle dependency of the optimized shape revealed that adding a yaw angle provided a sailing effect that reduces CD. A program for calculating fuel consumption rates for heavy-duty vehicles was used to compare fuel efficiency when using the base shape and the optimization shape. The weighted average fuel economy in urban driving (JE05) and interurban driving (highway) modes was improved by approximately 21% using the optimization shape.

Kawano, Daisuke

Investigation of the Blockage Phenomenon in Closed Wall Wind Tunnels during the Testing of Bluff Automotive Bodies with Small Wakes in Yawed Configurations

2026-01-0607

4/7/2026

The difficulties of testing a bluff automotive body of sufficient scale to match the on-road vehicle Reynolds number in a closed wall wind tunnel has led to many approaches being taken to adjust the resulting data for the inherent interference effects. But it has been difficult to experimentally analyze the effects that are occurring on and around the vehicle when these blockage interferences are taking place. The present study is an extension of earlier works by the authors and similarly to those studies uses the computational fluid dynamics analysis of five bodies that generate small wakes to examine the interference phenomena in solid wall wind tunnels. This focuses on the effects on the pressures, and forces experienced by the vehicle model when it is in yawed conditions up to 20 degrees. This is accomplished by executing a series of CFD configurations with varying sized cross sections from approximately 0.4% to 14% blockage enabling an approximation of free air conditions as reference. The configurations include a reference fastback (with detailed and smooth underbodies) and a notchback body (detailed underbody) from the Technical University of Munich, the University of Stuttgart AeroSUV (fastback configuration), and a generic pickup truck model (Ford). Examination is made of the physical phenomena occurring around the vehicle as the proximity to the walls and ceiling is changed holding the test section aspect ratio and length constant. Wall and ceiling static pressure distortions, and the distribution of forces on the vehicle body are examined as well as comparing Body Axis and Wind Axis force representations. It is intended that this dataset be utilized by the SAE Road Vehicle Aerodynamics Forum Committee (RVAC) and the Subsonic Aerodynamic Testing Association combined activity, Commonized Automotive Aerodynamic Test Standards (CAATS), to evaluate and/or develop closed wall wind tunnel blockage techniques for automotive bluff bodies.

Gleason, Mark, Riegel, Eugen

Protection of Megawatt-Scale DC Fast Charging Infrastructure for Heavy-Duty Vehicles: Ultra-Fast DC Breaker Development, Testing, and Future Roadmap

2026-01-0400

4/7/2026

Direct Current (DC) fast charging enables supply of megawatt (MW) scale DC power to the large battery systems of Heavy-Duty Electric Vehicles (HDEVs), such as electric trucks, buses, ferry and construction machinery. This contrasts with Alternating Current (AC) charging, which is limited by the capacity of the On-Board Charger (OBC) that converts AC to DC to charge the battery. In DC fast charging, however, the Electric Vehicle Supply Equipment (EVSE) delivers DC power directly to the HDEVs, bypassing the OBC. The feasibility of fast DC charging has been driven by advancements in semiconductor technology offering higher voltage and current handling capabilities as well as improvements in battery energy density. Ongoing research indicates continued growth in both semiconductor power handling and battery storage capacity, further strengthening the case for fast DC charging. Key benefits include significantly higher charging efficiency, drastically reduced charging times, and lower driver fatigue. However, unlike AC systems, DC based charging infrastructure presents unique protection challenges. These challenges arise from the absence of natural current zero-crossings of DC current and the limited commercial availability of pure DC breakers. This paper presents a concise review of existing protection technologies applicable to DC fast-charging infrastructure, identifying critical gaps in current approaches and evaluating potential solutions for Low Voltage (LV, <1.5 kV) and Medium Voltage (MV, 1.5–35 kV) DC applications. Then a downsized 10 kW prototype of an Ultra-Fast Active Resonance Current Source-Based Hybrid DC Circuit Breaker (UFRDCB) has been developed and experimentally validated as a proof of concept. The prototype successfully interrupts a 1 kA continuous DC current in less than 500 μs, and the corresponding test results are presented and discussed. Finally, the paper outlines a forward-looking roadmap for advancing protection technologies that are critical to the safe and reliable operation of megawatt-scale DC fast-charging infrastructure for HDEVs in the United States and globally.

Rahman, Md Rakib-Ur, Dobrzynski, Daniel

Physics-Based Simulation for Sustainable Fuels Part 2.1: Inter-Ring Pressure Measurements and 2D/3D Ring Dynamics Analysis across Multiple Engine Platforms – Light Vehicle

2026-01-0281

4/7/2026

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

Accelerating Electrification through Modular Propulsion: GM’S Strategy for BEV and BET Platforms

2026-01-0410

4/7/2026

General Motors (GM) continues to advance its electrification strategy through the development of scalable Battery Electric Vehicle (BEV) and Battery Electric Truck (BET) platforms. This paper highlights GM’s latest BEV and BET products that leverage shared Drive Unit (DU), Rechargeable Energy Storage System (RESS), and integrated power electronic (IPE) components across multiple vehicle programs. By adopting a modular and commonized propulsion architecture, GM achieves significant benefits in manufacturing efficiency, cost optimization, speed to market, and product flexibility. The shared DU, RESS, and IPE components are engineered to meet diverse performance requirements while maintaining high standards of energy efficiency, thermal management, and durability. This approach enables rapid deployment of electrified solutions across various segments, from passenger vehicles to full-size trucks, without compromising on capability or customer experience. The paper outlines the technical rationale behind component commonization, including design considerations and integration challenges. Through this shared architecture, GM demonstrates how intelligent component reuse can accelerate innovation, reduce complexity, and support the transition to a zero-emissions future. The findings presented offer valuable insights into the role of scalable propulsion systems in shaping the next generation of electric mobility.

Liu, Jinming, Sevel, Kris, Anwar, Mohammad, Oury, Andrew, Welchko, Brian, Gagas, Brent

Energy Efficiency Analysis of U-Haul Truck and Trailer Systems: Impact of Tongue Weight and Load Variations

2026-01-0466

4/7/2026

The demand for improved energy efficiency in real-world vehicle operations continues to grow with technology enhancement. When transporting large cargo loads with passenger pickup trucks and rental trailers, the interaction between vehicle payload, towing configuration, and fuel consumption becomes a key factor in overall system efficiency. Understanding how towing configurations and trailer loading influence fuel consumption and vehicle performance is critical for both consumer guidance and vehicle system design. This study investigates the energy efficiency of U-Haul truck and trailer systems, with a particular focus on the influence of trailer tongue weight. U-Haul truck and trailer simulation models were developed using AVL Vehicle Simulation Model (VSM) software, with an F-350 engine brake-specific fuel consumption (BSFC) map integrated to represent realistic engine performance. Two configurations with equal payload were evaluated: (1) a U-Haul truck alone, and (2) a U-Haul truck towing a trailer. Within these configurations, multiple scenarios were analyzed, including variations in payload levels and tongue weight distributions. Driving cycles were selected to capture common moving conditions such as urban stop-and-go traffic and extended highway operation. Simulation outputs quantified the interactions among vehicle dynamics, powertrain load, and fuel consumption. Results show clear differences in energy consumption between standalone and towing configurations, with tongue weight distribution exerting a significant influence on both efficiency and stability. The findings provide practical insights into the energy trade-offs between independent vehicle operation and towing scenarios. Moreover, the study highlights the importance of load distribution and driving cycle considerations in optimizing fuel consumption, offering a framework that can be extended to rental, commercial, and consumer towing applications where energy efficiency and vehicle performance are important.

Wang, Gang, Kathadi, Mohammad, Yang, William, Chen, Yan

BorgWarner to supply integrated drive and generator for EREV trucks

26AUTP04_11

4/1/2026

BorgWarner revealed an integrated drive and generator module optimized for range-extended trucks and large SUVs, a technology many see as the predominant electrified strategy for utility vehicles with the headwinds currently facing the BEV market. The company already has a contract with what it calls a major American automaker to build the model beginning in 2029 for a series of range-extended vehicles.

Clonts, Chris

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