Browse Topic: Fuel economy

Items (7,977)
Find
Performance and Scheme Study of the Hybrid Engine Integrated PEMFC with Jet Engine for Commuter Aircraft2026-99-293410/19/2026
To support aviation decarbonization and improve overall propulsion efficiency, this paper proposes a hybrid propulsion architecture integrating a proton exchange membrane fuel cell (PEMFC) with a turbofan engine. The proposed parallel hybrid configuration achieves efficient energy conversion through the thermodynamic coupling of key components, including the heat exchanger, ducted fan, compressor, and combustor. A thermodynamic model is developed for parameter matching and system analysis. Results indicate that, at the design point, the overall system efficiency reaches 0.36, with a thermal efficiency of 0.42 and a propulsive efficiency of 0.82. Compared with the baseline CFM56-3C1 engine, the proposed system shows improved fuel economy and environmental performance, achieving a specific fuel consumption of 5.8 g/(s·kN), NOx emissions of 0.0063 g/kg-fuel, and a noise level of 92 dB. Exergy analysis further indicates that the primary exergy destruction occurs within the fuel cell (20%) and during combustor heat transfer (18%). These findings suggest that multi-energy pathway coupling can reduce fuel consumption and emissions, providing a potential approach for low-carbon aviation propulsion systems.
Huang, Mengxuan, Ji, Zhixing, Huang, Jiao, Xu, Zibo, Yao, Yunan, Cao, Zhipeng, Wang, Zhanxue
Aerospace & Defense Technology: Oct 202626AERP1010/8/2026
Terabit Optical Communications in Space: Engineering High-Speed Networks for Data Centers in Orbit Mild Hybrids: A Current-Gen Bridge to Electrifying Military Ground Vehicles The Integrated and Flexible Approach to Large-Scale Metrology: How Integrating Laser Trackers and Modular Arms Creates a 'Unified Nervous System' The Defense Industry Continues to Meet CMMC Phase II Requirements Despite 60-Day Pause In Space, No One Can Hear You Stream AMD to Bring UCIe Connectivity to Select Versal Adaptive SoCs How Special Interface Gages Provide Microscopic Precision for Designing Ballistic Missiles The pristine precision needed to certify the nation's underwater nuclear deterrent is anchored on the talents of civilian scientists at a Navy laboratory in Southern California. Rapidly Testing Deployable Systems Sandia National Laboratories is evaluating portable security architectures that combine radar, drones, ground sensors, cameras and wireless communications networks into a single rapidly deployable system for remote and austere environments. Testing focuses on sensor integration, resilient communications and edge-based data processing to improve situational awareness while operating within real-world bandwidth constraints. Tailored Surface Vibrations to Improve Aerodynamic Performance in Passenger Jets University of Colorado Boulder researchers have demonstrated two new phononic flow-control concepts, super-resonance and scatterless interference, that use engineered subsurface vibrations to interact with boundary-layer airflow across a broader range of turbulence frequencies than previously possible. By delaying flow instabilities without altering a wing's external shape, the technology could reduce aerodynamic drag and improve fuel efficiency in passenger aircraft. New Type of Attack Can Slip Past the Defenses in Your Computer's Processor MIT researchers found a way to exploit a split-second gap in chip security - and used it to acquire a Linux system's password file. Army Tests Safer Electrical Connectors for Ground Vehicle Readiness U.S. Army DEVCOM Ground Vehicle Systems Center engineers are evaluating cadmium- and hexavalent chromium-free electrical connectors designed to reduce hazardous material exposure while maintaining corrosion protection, electrical performance, and long-term vehicle sustainment.
Importance of Duty Cycle Variability in Estimating Total Cost of Ownership for Vocational Battery Electric and Fuel Cell Vehicles13-07-02-000710/7/2026
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
Initial Thermal Evaluation of 422 Martensitic Stainless Steel Piston in a High-Output Diesel Engine2026-01-75649/22/2026
A piston manufactured with a crown comprised of grade 422 martensitic stainless steel and skirt manufactured from 4140 steel was instrumented with fifteen thermocouples and a wireless telemetry system. Piston temperature data were collected at five engine operating conditions and compared to two additional instrumented pistons with crown and skirt both made of 4140 martensitic steel, which is traditionally used for heavy-duty diesel applications. Thermal finite element modeling was used to predict the increase in operating temperature of the 422 piston relative to the 4140 piston and help understand instrumentation uncertainty. Previous research of candidate high-temperature alloys indicated that 12Cr martensitic steel alloys, such as alloy 422, offer several potential benefits when used in a diesel piston application, including increased high-temperature oxidation resistance and strength. The potential benefits of alloy 422 may however be partially negated by the expected increased piston operating temperature due to the alloy’s lower thermal conductivity. In this work 422 alloy resulted in no statistically significant change in piston temperatures relative to the baseline 4140 steel during engine testing. The 422 alloy is poised to offer a dual durability advantage because the initial results show it can achieve superior oxidation resistance without operating at the higher temperatures that would accelerate such degradation. Maximum piston temperature capability is expected to be a critical design limit in next generation diesel engines with greater power density, lower heat rejection, and improved fuel economy. Citation: E. Gingrich, et. al., “Initial Thermal Evaluation of 422 Martensitic Stainless Steel Piston in a High-output Diesel Engine,” In Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium (GVSETS), NDIA, Novi, MI, Aug. 11-13, 2026.
Gingrich, Eric, Tess, Michael, Grunin, Arkady, Korivi, Vamshi, Sebeck, Katherine, Pierce, Dean, Wang, Yiyu, Muralidharan, Govindarajan, Pillai, Rishi, Haynes, James A., Will, Kurt
Adaptive Neural Network Fuel Mass Correction for Structural Model Error Compensation in Diesel Engines with Variable Biodiesel Properties2026-24-00239/21/2026
Compression-ignition engines operating with biodiesel blends often exhibit variability in fuel properties, such as density, viscosity, and cetane number, which can lead to systematic deviations in injected fuel mass when using conventional physics-based models. These deviations can reduce combustion efficiency and increase brake-specific fuel consumption (BSFC). This study proposes a lightweight neural network–based approach to compensate for structural errors in baseline injection models, using a single-layer perceptron trained on the relative error (delta) between actual and modeled injected mass. By normalizing engine and fuel parameters and introducing a small amount of measurement noise, the network learns to predict a corrective factor that adapts the injected mass to match the desired target under varying fuel conditions. Simulation results demonstrate that the neural correction significantly reduces systematic bias: in test cases with intentionally introduced structural error, the average injection deviation of −1.7% in the baseline model is reduced to approximately 0.002% after correction. Root-mean-square (RMS) error over training and validation datasets remains below 0.16%, indicating robust generalization. The proposed method offers a computationally efficient solution suitable for embedded engine control units, requiring minimal additional complexity while ensuring precise fuel delivery. By eliminating bias caused by fuel property variability, the approach has the potential to improve fuel economy, reduce emissions, and maintain consistent engine performance under a wide range of operating conditions. This framework provides a practical path for integrating adaptive, data-driven correction mechanisms in diesel engines operating with heterogeneous or variable biofuels.
Gutierrez, Marcos, Taco, Diana
Navigating an increasingly complex engine oil landscape26AUTP09_029/1/2026
As the impending ILSAC GF-8, dexos 1 Gen 4, and a hybrid specification continue to obscure the North American landscape, passenger car engine oils need additive solutions that can help simplify blending operations and optimize product portfolios. Modern passenger car engine oils have evolved far beyond basic lubrication, becoming highly engineered fluids that support advanced engine technologies. Driven largely by the need to meet increasingly demanding efficiency and emissions requirements, today's engine oils must deliver a broad range of performance benefits in addition to wear protection. These requirements are defined through industry performance specifications, such as those established by the International Lubricant Standardization and Approval Committee (ILSAC). In North America, current passenger car engine oils are formulated to meet ILSAC GF-7 standards, helping ensure that lubricants are aligned with the operational needs of modern vehicles. Change is on the horizon. ILSAC is in the early part of its development process for ILSAC GF-8, which will further push the envelope in terms of how an engine oil must contribute to greater fuel economy.
Hanthorn, Jason
Research on Energy Consumption Optimization Control Strategy for Hybrid Electric Passenger Vehicles2026-01-50508/6/2026
The energy management strategy of hybrid electric vehicles (HEVs) is critical to achieving overall vehicle efficiency. Current global optimization methods involve significant computational complexity. Conventional or adaptive equivalent consumption minimization strategy (ECMS) also presents challenges in robustness and calibration efficiency, as it typically depends on real-time driving condition recognition and online parameter adjustment. To address these issues, this study proposes an engineering optimization framework based on a system efficiency lookup table approach. This method uses offline iterative simulation to determine a globally representative equivalent factor. It pre-computes optimal system efficiency, drive modes, and energy allocation across the entire operating range. These results are stored in a lookup table that the vehicle control unit (VCU) can access in real time. This approach eliminates the uncertainties associated with online optimization. It also provides calibration engineers with a quantitative tool to directly balance competing objectives, such as fuel economy and NVH. The optimized strategy increases the proportion of electric and parallel mode operation. This concentrates engine operating points within the high-efficiency zone and significantly reduces losses from multi-stage energy conversion. Simulations, dynamometer tests, and real-world road tests confirm the strategy’s effectiveness and repeatability. The approach achieves a fuel consumption reduction of approximately 0.2 L/100 km, with all test coefficients of variation (CV) remaining below 5%. The framework demonstrates good extensibility and can be adapted to different architectures, such as plug-in hybrid electric vehicles (PHEVs) and fuel cell vehicles (FCVs). It offers a universal and efficient engineering solution for optimizing energy consumption in hybrid powertrain systems.
Lin, Haoqiang, Wang, Jinhang, Chen, Lihua, Li, Huan
Model-Based Optimization and Evaluation of Hybrid Powertrains for Commercial Heavy-Duty Class 8 Truck Applications02-19-04-00257/27/2026
In an ever-evolving landscape of emission regulations, charging infrastructure, customer demands, fuel/energy costs and decarbonization goals, heavy-duty on-road vehicle manufacturers continue to evaluate alternative powertrain technologies. While most heavy-duty vehicle manufacturers now have battery electric vehicles (BEVs) in their portfolio, significant challenges of charging infrastructure, range anxiety, payload capacity reduction and upfront costs have contributed to their lower adoption rates. Plug-in hybrid electric vehicles (PHEVs) have significant potential of leveraging upcoming BEV infrastructure and component supply chains to reduce operating costs while still maintaining longer range and payload capacity benefits of conventional ICE powertrains. This article applies a model-based approach to evaluate multiple Class 7–8 heavy-duty powertrain configurations. A system-level (1D) model of the conventional diesel ICE-based truck was developed in GT-Suite and validated against on-road test data. Using the diesel ICE model as a baseline, system-level models for different hybrid configurations were adapted, and their powertrain architecture was optimized at the system level. Additionally, an equivalent consumption minimization strategy (ECMS) for energy management was also optimized for each of the hybrid powertrain configurations to maximize fuel efficiency and emission benefits. All the hybrid configurations were then compared against the conventional diesel ICE Class 8 truck in terms of performance (acceleration, top speed, gradeability and startability), fuel economy (real-world cycles and certification cycles), emissions, and range for long-haul applications. Unique to this approach is the simultaneous co-optimization of powertrain component sizing and supervisory control logic by utilizing a Genetic Algorithm–based optimization approach. Results indicate that all parallel hybrid architectures (P2, P2–P3, and P4) achieve performance (acceleration, top speed, gradeability, and startability) parity or improvement compared to baseline diesel architecture. P2-based architectures demonstrated a 12–14% improvement in fuel economy on representative real-world cycles when operating in a blended charge-depleting–charge-sustaining mode of operation, and a 4–6% improvement in fuel economy when operating in charge-sustaining mode alone. By quantifying these results across diverse topologies, this work addresses a significant research gap in the holistic evaluation of Class 8 hybrids, specifically, the trade-off between multi-speed electric drives, system-level mass increases, and real-world fuel economy, that remains underexplored in current literature.
Baburaj, Adithya, Paul, Sumit, Dhanraj, Fnu, Joshi, Satyum, Franke, Michael
Fuel Savings from Predictive Charge Control Based on Short-Trip Duration in Series Hybrid Electric Vehicles14-15-03-00157/10/2026
Series hybrid electric vehicles (HEVs) employ an electric motor for propulsion, while the internal combustion engine operates solely as a generator under energy-efficient speed and load conditions. Owing to this architecture, series HEVs can achieve high fuel efficiency with a relatively simple control structure. However, conventional energy management systems (EMSs) often prioritize battery state-of-charge (SOC) stabilization, which can lead to frequent engine start–stop operations and unnecessary fuel consumption, particularly in short-trip driving. This study aims to enhance energy management performance in series HEVs by optimizing engine power generation timing based on predicted short-trip duration. A computationally efficient, rule-based prediction model is developed using real-world driving data, in which short-trip duration is estimated from vehicle speed and acceleration. Due to its low computational load, the proposed model is suitable for implementation in an onboard electronic control unit (ECU). The proposed control strategy initiates engine power generation when the battery SOC is low and the predicted trip duration is long, and suppresses generation when the SOC is sufficiently high or the predicted trip is short. A detailed vehicle model incorporating an engine, generator, electric motor, inverter, and battery is developed in Modelica to evaluate the proposed strategy. Simulation results demonstrate that the proposed EMS significantly reduces the frequency of engine start–stop events, leading to fuel economy improvements of 3.6% under the WLTC (excluding the extra-high phase) and 13.4% in a real-world urban–rural driving cycle, compared with a commercialized baseline vehicle. These results confirm the effectiveness and practical applicability of the proposed EMS for passenger vehicle applications.
Mizushima, Norifumi, Sato, Akira, Kuboyama, Tatsuya, Moriyoshi, Yasuo
Multi-Scale Modelling of Localized Battery Degradation in Heavy-Duty Series Hybrids: From Electrochemical Impedance Spectroscopy to Powertrain and Battery Pack Performance2026-01-07477/1/2026
Hybrid electric vehicles rely heavily on battery pack power capability, which is often compromised by non-uniform aging and thermal gradients. Conventional battery models typically use bulk state-of-health metrics, failing to capture localized degradation that leads to current imbalances and reduced pack utility. This paper presents a multi-scale modelling framework that integrates Electrochemical Impedance Spectroscopy data into a fractional-order equivalent circuit model to simulate localized degradation in Lithium Iron Phosphate cells. Results show that the terminal voltage of LFP cells can be accurately modelled using the proposed fractional-order equivalent circuit with a discrete transfer-function implementation, maintaining root-mean-square errors below 20 mV across most state-of-health and state-of-charge conditions. The validated cell model is then extended to a degradation-aware battery pack representation. The battery pack in this work utilizes a 200-kWh, 800 V architecture consisting of five modules connected in parallel, each module composed of 13 parallel strings of 250 series cells, evaluated under multiple degradation scenarios. By integrating this pack model into a Class-8 series hybrid powertrain simulation, this study quantifies how cell-to-cell heterogeneity impacts vehicle performance under the VECTO regional delivery drive cycle. At the vehicle level, these battery constraints influence engine duty cycles and battery pack stress metrics. When localized degradation reaches up to 40% in one module while the remaining modules degrade up to 20% to 30%, such inhomogeneous degradation reduces the minimum pack terminal voltage by approximately 27% and increases peak discharge current by more than 30%, resulting in more rapid degradation. These battery-level limitations translate into higher fuel consumption by up to 6% in a charge-sustaining scenario.
Safavi, Seyed Reza, Homayouni, Hooman, Shoa, Tina, Wang, Jason, McTaggart-Cowan, Gordon
SAE Truck & Off-Highway Engineering: June 202626TOFHP066/11/2026
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
Potential of ORC-Based Waste Heat Recovery in Conventional and Hybrid Heavy-Duty Powertrains2026-37-00186/9/2026
Heavy-duty vehicles significantly contribute to greenhouse gas emissions and urban air pollution, especially during cold-starts and transients when engine and aftertreatment efficiencies drop. Waste heat recovery (WHR) via Organic Rankine Cycle (ORC) systems offers a practical solution to improve fuel efficiency and cut CO₂ in real-world heavy-duty operations. This study examines ORC-based WHR integration into conventional and hybrid powertrains of an Isuzu FTR850 truck, analyzing four configurations: Shell-and-Tube or Plate heat exchangers with simple or regenerative ORC layouts. For hybrids, it compares two engine sizes and energy management strategies: an optimized fuzzy logic approach versus constant-power operation to enhance exhaust heat recovery. A validated quasi-static simulation framework is used to predict fuel consumption and exhaust properties over representative duty cycles. 2D performance maps using exhaust temperature and mass flow as inputs are used to model the WHR under off-design conditions. Results show that the recovery of waste heat WHR depends on the hybridization level and strategy. Conventional powertrains benefit most from Shell-and-Tube exchangers, recovering ~2 kWh of electrical energy per 8-hour cycle and reducing fuel consumption by 0.5%. Hybrid setups recover up to 3.9 kWh from exhaust gases with a simple layout coupled with a Shell-and-Tube heat exchanger under constant-power control. Electricity is used to support onboard auxiliaries and battery charging, further lowering fuel demand (-44%) and emissions. Finally, a multi-objective optimization was performed to exploit the synergy between hybridization and WHR while maintaining acceptable payload and battery operating conditions.
Donateo, Teresa, Morrone, Pietropaolo
Experimental Investigation on Cold Start and Warm-Up Phases for an Ethanol Fueled SI Engine2026-37-00316/9/2026
The reduction of Greenhouse Gas (GHG) emissions represents a key challenge for the transportation sector, requiring the adoption of renewable fuels capable of ensuring both environmental benefits and compatibility with existing internal combustion engine technologies. In this context, bioethanol emerges as a viable solution for Spark Ignition (SI) engines, offering a low life-cycle CO₂ footprint and favorable combustion characteristics. Nevertheless, despite its well-known advantages under steady-state operation, the widespread use of high-ethanol-content fuels is still limited by critical issues during engine cold start. The aim of this work is to experimentally investigate the influence of ethanol content on cold-start behavior and idle warm-up transient operation of a Naturally Aspirated (NA), Port Fuel Injected (PFI) SI engine. The experimental campaign was carried out under idle conditions using four fuels with increasing ethanol content, namely commercial gasoline (E5), E30, E60, and neat ethanol (E100). Cold-start and full warm-up tests were performed starting from ambient temperature, while additional dedicated experiments were conducted on E100 to evaluate startability under different initial engine wall temperatures. The results show that increasing ethanol content has a limited impact on the overall warm-up duration, while slightly reducing engine wall and exhaust gas temperatures. Conversely, E100 exhibits pronounced startability issues at low initial wall temperatures, requiring multiple cranking attempts to achieve stable idle operation. A minimum wall temperature threshold in the range of 25-30 °C was identified as necessary to ensure reliable cold start with E100. The outcomes of this study provide experimental evidence of the key role played by engine thermal conditions in enabling stable operation of ethanol fueled SI engines during cold start.
Falbo, Luigi, Falbo, Biagio, Perrone, Diego, Castiglione, Teresa
Hybridized Diesel Powertrains - An Important Enabler for Commercial Applications on the Long Journey towards Full Electrification2026-37-00226/9/2026
The ongoing efforts for reduction of the traffic-related greenhouse gas emissions and, at the same time, the mitigation of harmful pollutant emissions from vehicle exhaust emissions are important development tasks for the entire automotive industry worldwide according to demand to provide clean and efficient products. Further tightened fleet average FE standards and ultra-low limits for exhaust emissions require the continuous development of new propulsion system types. Due to the given reluctance of the end customer and corresponding low acceptance of fully electrified vehicles, especially in the commercial vehicle segment, new and innovative topologies are needed to meet regulatory requirements and maintain the high versatility of today’s dominating solutions. For further optimization of operating conditions with enhanced fuel efficiency, the technical strategy is also determined by uplifting the attractiveness of electric driving incl. the avoidance of areas with poor ICE efficiency and as well as the coverage of emission-critical operations by electric propulsion. In this context, the support provided by an electric drive on board the vehicle in a combined drive system is becoming increasingly important. This article discusses accordingly various platform strategies for hybridized Diesel powertrains in different sectors of commercial vehicle applications and delivers a comprehensive comparative analysis of different hybrid drive concepts. Specifically, several hybrid powertrain configurations that extend an electric drive platform (hybridized BEVs), such as series and parallel-series topologies, are compared with traditional parallel hybrid powertrain topologies based on internal combustion engines (ICE). The study focuses mainly on two different cornerstone applications: a large light commercial vehicle, ranging from 3,5 to 6,5 to. and a heavy-duty long-haul truck with 40…44 to. gross vehicle weight. It evaluates the advantages in terms of CO2 emissions and Diesel fuel savings and investigates the effects on emission controls aspects. In addition to technical comparisons, the paper addresses also regulatory demands and end customer merits, assessing the integrational effort and commonalities in components with pure ICE and battery electric topologies. Furthermore, it explores the additional impact of advanced operational strategies for Hybrid Diesel powertrains, incorporating insights from innovative observations from executed hybrid technology demonstrator vehicles.
Koerfer, Thomas
Hitting the road IN THE ALL-NEW VNR26TOFHP06_016/1/2026
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
ZF bets big on hybrid transmissions26TOFHP06_066/1/2026
ZF foresees hybrid powertrain technology becoming more popular for commercial transport in the coming years, and it's working earnestly to be a major player in that realm. The supplier unveiled the TraXon 2 Hybrid transmission to the North American commercial vehicle market at last year's ACT Expo and is now evaluating the technology in real-world conditions. The next-gen automated manual transmission (AMT) is optimized to improve fuel efficiency for plug-in and full hybrid heavy-duty trucks and coaches, as well as special applications such as medium- to heavy-duty mobile cranes.
Gehm, Ryan
Q&A26TOFHP06_156/1/2026
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
Effect of Burning Biomass Fuel Cyclohexanol on Diesel Engine Performance2026-99-17085/22/2026
Against the backdrop of growing global demands for energy sustainability and stricter emission regulations for diesel engines, this study investigates the performance implications of incorporating cyclohexanol—a renewable oxygenated fuel—into diesel fuel blends. Using a marine medium-speed diesel engine as the experimental platform, the research systematically evaluates engine performance and emission characteristics across a range of cyclohexanol-diesel blend ratios under low, medium, and high load conditions. Experimental findings reveal multifaceted effects of cyclohexanol blending on engine operation. Combustion of the blended fuels enhances the engine’s dynamic performance, particularly under medium and high loads, where the maximum in-cylinder burst pressure exhibits a noticeable increase. This improvement is attributed to cyclohexanol’s oxygen-carrying capacity, which promotes more vigorous and sustained combustion reactions. In terms of emissions, increasing the proportion of cyclohexanol in the fuel blend leads to significant reductions in soot and carbon monoxide (CO) emissions, reflecting the cleaner-burning properties of the oxygenated component. However, this is accompanied by an uptick in nitrogen oxide (NOx) emissions, likely due to the elevated combustion temperatures generated by the more efficient fuel oxidation process. From an economic perspective, cyclohexanol blending at consistent load levels induces a postponement in the crank angle at which peak heat release occurs during combustion. This temporal shift prolongs the effective combustion duration, enabling more complete fuel utilization within the cylinder. Consequently, fuel consumption rates decrease, and overall engine efficiency improves, highlighting the potential of cyclohexanol blends to enhance operational economy in marine propulsion systems. In summary, this study underscores the complex trade-offs associated with cyclohexanol-diesel blends: while they offer tangible benefits in power output, fuel efficiency, and reduced particulate emissions, managing the increase in NOx emissions remains a critical challenge. The results provide a foundational framework for advancing biofuel applications in marine engines, emphasizing the need for integrated emission control strategies to optimize the balance between performance and environmental sustainability.
Chen, Ke, Yang, Chenxi, Wang, Yibin, Fan, Jinyu, Liu, Yuchen, Ye, Zixiao, Huang, Jialiang
Effect of EGR Rate on Cyclohexanol-Diesel Dual-fuel Engines2026-99-17095/22/2026
To reduce high NOx emissions from diesel-cyclohexanol blends, this study employed a marine medium-speed diesel engine as the experimental platform. An in-cylinder combustion model was developed and meshed using AVL - FIRE software, with model validity validated against experimental data. Tests were conducted at four load conditions (25%, 50%, 75%, and 100% load) with a 30% cyclohexanol blend (C30) and four EGR rates (0%, 7.5%, 10%, and 12.5%) to analyze combustion characteristics, emissions, and fuel economy. The results showed that the introduction of EGR had a striking inhibitory effect on NOx emissions. At 100% load with 12.5% EGR rate, NOx emissions were substantially reduced compared to baseline operation without EGR. However, EGR implementation led to delayed ignition timing, reduced in-cylinder pressure, and worsened fuel economy. Therefore, an appropriately calibrated EGR strategy can effectively reduce NOx emissions, though it requires optimization to mitigate adverse effects on combustion performance and efficiency.
Liu, Yuchen, Yang, Chenxi, Fan, Jinyu, Chen, Ke, Ye, Zixiao, Huang, Jialiang
Establishing a Standard S-Factor: Improving Accuracy and Flexibility in SOC Corrections for HEV Testing2026-01-04224/7/2026
Hybrid-electric vehicle (HEV) fuel economy test procedures require that the net energy change (NEC) of the battery not interfere with measuring accurate fuel consumption results. SAE J1711-2010 required the NEC to stay within 1% of fuel energy consumption, assuming that residual changes in state of charge (SOC) would have negligible impact. In practice, however, the asymmetry between fuel and electricity conversion efficiencies means that an imbalance of one unit of battery energy can translate into a likely fuel consumption error of roughly three units. A standard S-Factor, a dimensionless ratio of marginal fuel change to marginal NEC change, was introduced in J1711-2023 to improve SOC correction procedures. The method improves upon the previous J1711 (2010) accuracy by correcting all results for NEC changes and expands the NEC-to-fuel ratio (NECFR) window, enabling HEVs to use electric propulsion more aggressively and potentially achieve higher fuel economy in testing and real-world usage. Using a standardized value (instead of requiring additional testing to determine the vehicle-specific value) provides a simple, low-burden approach across HEV designs. Empirical data, supported by simulations of HEV powertrains, indicate that there exists a practical range of S-Factors common to efficient HEV designs. The standard value represents a defensible best estimate within this range, close enough to provide corrected results with minimal error. The method also allows the NECFR window to be doubled (e.g., from ±1% to ±2%) while improving the fidelity of final fuel consumption results compared with the legacy procedure. This paper reviews the data and simulation work used to identify practical S-Factor values, evaluates the resulting correction accuracy across vehicle types and test cycles, and demonstrates that a single standardized S-Factor provides consistent results within an expanded NECFR window.
Duoba, Michael
Simulation Verification and Design Guide for P1+P2 Hybrid Built-in Damper System2026-01-00064/7/2026
The damper system in a hybrid TMED system reduces engine-induced vibration and damps the rapid torsional torque applied by the motor through spring stiffness. Furthermore, the built-in damper system of the P1+P2 TMED-II hybrid system offers improved fuel efficiency compared to the external damper system of the existing P0+P2 TMED-I. Although the internal layout of the transmission is limited, the built-in damper system was redesigned to accommodate installation between the P1 and P1 motor. However, CAE analysis techniques for damper systems are currently not clearly defined, and research data on their strength under rotational torque loads are lacking. To reduce development costs and provide direction, CAE analysis technology development and validation are necessary. In this study, a finite element model of the damper system was developed and compared with experimental results to ensure CAE reliability. Furthermore, based on the validated model, structural and fatigue durability analyses were performed, attempting to replace test-driven R&D methods with CAE. Additionally, we used Design of Experiments (DOE) to determine the impact of structural analysis stresses on the design parameters of the embedded damper system. Through this process, we selected an optimal model that minimized stresses, and verified the improvement effects through analysis of this model.
Sun, Hyang Sun, Ganesan, Karthikeyan
Multi-Objective Reinforcement Learning Framework for Transmission Shift Schedule Optimization2026-01-01624/7/2026
Building upon previous work that successfully employed a Reinforcement Learning (RL) agent for the autonomous optimization of transmission shift programs to enhance fuel efficiency, this paper addresses a critical limitation of that approach: the neglect of human-centric factors. While the prior methodology achieved substantial fuel consumption reductions by training an RL agent in a Software-in-the-Loop (SiL) environment, it did not explicitly account for aspects such as driver comfort and preferences, which are paramount for real-world user acceptance and drivability. This work presents a multi-objective optimization framework extending the artificial calibrator to simultaneously maximize fuel efficiency and enhance driver comfort. The method introduces a modified RL reward function that penalizes undesirable shift behavior to ensure a smooth driving experience (drivability). This new methodology also incorporates a mechanism to capture and integrate driver preferences, moving beyond a purely quantitative fuel-economy-driven objective to a holistic, user-focused calibration. Experimental evaluation demonstrates that the extended framework successfully generates a shift strategy that achieves a favorable trade-off between fuel efficiency and drivability, resulting in a more balanced and practical calibration. The ability to integrate these qualitative factors into an automated, data-driven process represents a significant step forward, promising to accelerate the development of powertrain control systems that are both highly efficient and aligned with the expectations of human drivers. This work lays the foundation for future RL-based calibration tools that are capable of addressing the full spectrum of development objectives, from fuel economy to the subtleties of vehicle drivability.
Kengne Dzegou, Thierry Junior, Schober, Florian, Rebesberger, Ron, Henze, Roman, Sturm, Axel
A Study on Fatigue Life Prediction Method for Point-Based Joints Considering Multiple Fracture Modes – FDS, Blind Rivet, and Blind Nut Focus2026-01-01804/7/2026
The application of multiple materials in vehicle bodies is accelerating as the adoption of lightweight aluminum alloys and composite materials advances rapidly. These materials play a crucial role in reducing overall vehicle weight, enhancing fuel efficiency, and complying with increasingly strict environmental regulations. As the automotive industry continues to evolve toward electrification and sustainability, the integration of lightweight and high-performance materials has become a key design strategy. However, the use of multiple materials creates new challenges in manufacturing, particularly for joining technologies. Since different materials have varying mechanical properties, thermal behavior, and surface characteristics, the selection of appropriate joining methods is essential for ensuring structural integrity and durability. Depending on material types, thicknesses, production processes, and cost constraints, various joining techniques—such as mechanical fastening, welding, and adhesive bonding—are selectively applied. This study focuses on fatigue life prediction for point-based joints commonly used in automotive structures, including flow drilling screws (FDS), blind rivets, and blind nuts. Fatigue fractures in these joints typically propagate in multiple directions: through the sheet thickness and along the in-plane direction. Accurate fatigue life prediction requires numerical simulations that account for both crack propagation paths and the interaction of these paths with joint geometry and loading conditions. Traditional fatigue models often assume a single fracture mode, limiting the ability of these models to evaluate multiple failure mechanisms simultaneously. To address this issue, this study proposes a simplified modeling approach that enables the simultaneous consideration of multiple fracture modes. This paper introduces a numerical analysis-based method capable of predicting the fatigue strength of point joints, and describes the fatigue tests that were conducted to validate the proposed approach. This research contributes to the development of more reliable and efficient design strategies for multi-material automotive structures.
Takuno, Sougo, Isono, Toshiyuki, Urakawa, Kazushi, Goto, Suguru, Kawamura, Hiroaki, Niisato, Eita, Ishigami, Yuta
Application of Topology Optimization to Production-Ready Passenger Seat Components Design2026-01-04984/7/2026
Lightweighting of components has become a key challenge in the development of modern transportation systems. In the automotive and aerospace industries, the overall mass of a vehicle has a significant impact on its fuel efficiency and manufacturing cost. Therefore, the lightweight design of vehicle components is crucial in the industrial field. Topology optimization (TO) is a computational design approach aimed at achieving lightweight designs. However, most existing studies focus on simplified academic models, with limited demonstration in real-world applications. This paper presents a revised TO workflow to obtain production-ready design and a practical implementation of TO in the design of three structural components in the aerospace industry: seatback frame, seat fuselage mount, and seat spreader. The revised TO workflow incorporates the practical demands of industry, including enhanced manufacturability and cost efficiency through TO design. The resulting designs are evaluated to ensure all regulatory requirements are satisfied. Comparative results show that the designs produced by the presented TO-based design method achieve a significant weight reduction of 50% for the seatback frame. For the seat fuselage mount and seat spreader, the proposed method produced designs with a weight comparable to the baseline while satisfying stricter crashworthiness requirements. These components also ensure manufacturability, efficient fabrication cost, and compatibility with family parts. These findings demonstrate that TO can deliver production-ready solutions without compromising structural performance. The study highlights the potential of integrating TO into a revised design workflow to support performance-driven development of complex, production-ready industrial components.
Lee, Hanbok Jake, Shi, Yifan, Gray, Savannah, Orr, Mathew, Park, Taeil, Wotten, Erik, LeFrancois, Richard, Huang, Yuhao, Patel, Anuj, Kim, Hansu, Jalayer, Shayan, Burns, Nicholas, Hansen, Eric, Grant, Robert, Kok, Leo, Kim, Il Yong
Evaluating the Impact of Drag Coefficient Changes on Driving Energy Using a Probability Distribution Model of Yaw Angle Based on Empirical Data from North American Highway2026-01-06154/7/2026
This study estimates the impact on driving energy of differences in aerodynamic characteristics for yaw angle from natural wind during North American Highway mode driving. A previous study [1] clarified the potential to estimate the fuel consumption impact of natural wind by integrating the drag coefficient yaw characteristics and yaw angle occurrence probability. The natural wind was measured on a vehicle while driving a representative North American Highway test course [2]. Driving energy is predicted from the obtained yaw probability and the drag coefficient yaw sweep data in a wind tunnel. Measurements were conducted every weekday for 8 hours in 2023, covering 70% of the traffic volume. The validity of the measurement period was evaluated by the deviation from the annual average of wind direction and speed. Since yaw probability varies depending on the road environment, it is necessary to weigh the road environment type probability when calculating the driving energy. The probability was calculated using machine learning from more than 490,000 images of North American Highways. Based on the obtained natural wind data, a yaw probability model was created for each vehicle speed in the US Highway driving mode. An evaluation method for the driving energy was constructed from data before and after the improvement of the drag coefficient yaw characteristics. This evaluation method is based on verification results from actual driving data. By using the yaw probability distribution that considers the road environment and traffic volume of the North American highway, the impact of the yaw angle due to natural wind on driving energy can be numerically estimated. According to this method, for a specific the drag coefficient yaw sweep characteristic with a 13 ct improvement in the drag coefficient at a 6-degree yaw angle, this would result in an improvement in drive energy of approximately 1% on real US highways. This is an important indicator for optimizing aerodynamic characteristics, and suggests a development direction that can improve fuel efficiency in the real world by optimizing the vehicle shape while taking into account the yaw angle caused by natural wind.
Onishi, Yasuyuki, Nucera, Fortunato, Nichols, Larry, Metka, Matt
Aerodynamic Development of Maruti Suzuki Victoris2026-01-06024/7/2026
MSIL (Maruti Suzuki India Limited), India’s leading automotive manufacturer, offers a diverse range of SUVs (Sports Utility Vehicles) in its portfolio. Traditionally, SUVs are associated with an assertive stance and a commanding road presence; however, this bold design language often compromises aerodynamic drag performance. Over the past decade, demand for this segment has surged, while CAFE (Corporate Average Fuel Economy) regulations have become increasingly stringent. To address this growing market need, MSIL conceptualized a new SUV - Victoris - targeted to deliver best-in-class aerodynamic efficiency in MSIL SUV portfolio. This paper details the aerodynamic development process using CFD (Computational Fluid Dynamics) and full-scale WTT (Wind Tunnel Testing). Initially, the aggressive styling of Victoris negatively impacted drag performance. Strategic exterior surface refinements and integration of aero components enabled recovery of aerodynamic efficiency. Key interventions included redesigned front and rear bumpers, roof-end treatment, quarter spoiler profiling, bumper corner vents, and aero-cut alloy wheels. Victoris successfully retained its bold styling while meeting ambitious aerodynamic targets. The optimized aerodynamic silhouette comprising hood-to-windshield transition, roof contouring, backdoor spoiler, and side body profiling - along with underbody elements such as covers, strakes, and air curtains improved drag performance by 14% compared to the initial design. Achieving this improvement required significant shape modifications and aero part additions without compromising SUV identity. This paper explains how these measures were implemented and the resulting airflow characteristics.
Dey, Sukanta, Singh, Shekhar, Kumar, Chandan, Alphonse, Felix Regin
Optimization Method for Vehicle Shape to Drastically Reduce Aerodynamic Drag in Heavy-Duty Vehicles2026-01-06034/7/2026
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
Study of Deposit Control Additive Efficacy in Gasoline Direct Injection Engines2026-01-03494/7/2026
There is an increasing adoption of Direct-Injection Spark-Ignition (DISI) engines in the market, which per 2024 US Environmental Protection Agency (EPA) Automotive Trends Report represents 73% of new vehicles sold in the US. And while it is well accepted that DISI offers advantages over Port Fuel Injection (PFI) technology in meeting stringent CO2 emissions and fuel economy requirements set by the EPA, DISI engines are also associated with increased formation of injector deposits. These deposits may foul injectors and accumulate on the injector tip causing distorted spray patterns and diffusive combustion. Ultimately, this leads to engine performance deterioration and increased harmful emissions. To control deposit formation, detergent-type chemistries are added to the fuel in small amounts. Deposit Control Additives (DCAs) function by preventing the formation of deleterious injector deposits as well as removing existing ones. This study used standardized protocols describing the assessment of DCA in controlling injector deposits that have been developed by industry in both the US and Europe. When used at standard concentrations, DCA showed some engine performance and emission benefits over untreated base fuel. This investigation also demonstrated that engine performance can be recovered, in an engine with fouled injectors, with the use of higher DCA concentrations, accompanied by improved fuel economy and reduced particulate and total hydrocarbon emissions. This further confirms previous findings that, although DCA increases gum levels in the fuel, higher concentrations of DCAs improve injector cleanliness enough to outweigh any negative impacts from the increased gum content.
Soriano, Nestor, Williams, Rod, Cracknell, Roger, Lang, Wendy, Chahal, Jasprit
Energy Management Strategy for Hybrid Mining Trucks Based on Global SOC Planning and Neural Network Optimal Control2026-01-04464/7/2026
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
Automotive Aerodynamics Surrogate Modeling using NVIDIA PhysicsNeMo on Mid-Sized SUV GM Dataset2026-01-06004/7/2026
Aerodynamic simulations are crucial in vehicle design and performance evaluation. Traditionally, these simulations utilize Computational Fluid Dynamics (CFD) techniques to compute flow quantities such as velocity, pressure, and wall-shear stresses. Accurate prediction of these quantities is vital for estimating drag and lift forces, which directly impact fuel efficiency, stability, and acoustics. This study focuses on developing an AI surrogate for aerodynamic design of production mideo-size SUVs using NVIDIA’s PhysicsNeMo framework. Firstly, high-fidelity 3D CFD data are generated using first-principles solvers on 102 different geometry variants at a uniform inlet velocity of 38.89 m/s and a fixed set of boundary conditions. The DoMINO (Decomposable Multiscale Iterative Neural Operator) AI model, part of the PhysicsNeMo framework, is then used to train on this dataset, accurately predicting surface pressure and flow fields around vehicles for rapid estimation of critical aerodynamic metrics such as drag and lift. DoMINO is a neural operator that learns local geometry representations from point cloud data and predicts PDE solutions on discrete points using dynamically constructed computational stencils in local regions. By leveraging both short- and long-range geometric features, the DoMINO model predicts solution fields on the vehicle’s surface and in the surrounding flow domain—capabilities essential for informed design and engineering decisions in industrial applications. In this study, the DoMINO model is evaluated on a realistic production mid-size SUV vehicle designed by General Motors. Comprehensive hyperparameter tuning is conducted to optimize model performance, along with an analysis of input grid sensitivity. The findings highlight DoMINO's effectiveness as a robust and accurate tool for aerodynamic analysis in the automotive sector, enabling accelerated design cycles and enhanced vehicle performance.
Keum, Seunghwan, Raul, Vishal, Grover, Ronald, Parrish, Scott, Ranade, Rishikesh, Ghasemi, Abouzar, Kamenev, Alexey, Tadepalli, Srinivas
The Impact of Various Renewable Hydrocarbons on Performance and Emissions in a Super Lean Burn Engine2026-01-03064/7/2026
Compared to regular fuels, biofuels can play a key role as low-carbon transitional energy sources for ICE vehicles as the fleet moves towards increasing electrification. Blending of ethanol plays a key role in enhancing the anti-knock properties of the fuel and also allows renewable hydrocarbons (such as bio-naphtha) to be incorporated into the blend whilst maintaining an acceptable overall fuel quality. Super lean burn ICE technology with λ between 2 and 3 can lead to enhanced fuel economy and reduced NOx emissions. The Toyota prototype engine used to generate data for this project injects most of the fuel in PFI mode to generate a homogeneous super-lean charge in the cylinder, but just before spark ignition the DI injector sprays a small amount of fuel towards the spark plug to create a richer charge near the spark plug to promote flame kernel development. Various fuel formulations with high biofuel content were tested in both conventional and super lean burn engines. Certain fuel compositions were formulated with faster burning components such as ethyl benzene. The super lean burn engine showed a clear link between faster combustion and minimization of unburned fuel losses, thereby resulting in a further efficiency benefit. The effect of fuel composition on particulate emissions was more complex: although the conventional engine emitted higher particulate numbers (PN) when operating on fuels with a higher content of heavier aromatics (as might be predicted from standard particulate index approaches), the super lean burn engine suggests that additional factors are at play which are discussed in the paper.
Aradi, Allen, Krueger-Venus, Jens, Jain, Sandeep Kumar, Cracknell, Roger, Kolbeck, Andreas, Shibuya, Masahiko, Yamada, Ryota, Matsubara, Naoyoshi, Kitano, Koji
Optimization of Engine Cooling System for Improved Fuel Efficiency and Vehicle Marketability2026-01-02974/7/2026
Effective thermal management in internal combustion engines is essential for meeting increasingly stringent emissions regulations and achieving fuel efficiency improvements. This study introduces a novel and comprehensive approach to optimize engine thermal management by addressing key system components, including coolant circuit design, Integrated Thermal Management Module (ITM) control strategies, port-specific flow management, zero-flow operation techniques, and HVAC (Heating, Ventilation, and Air Conditioning) settings standardization. Unlike previously published works, this study focuses on reducing coolant circuit thermal mass to accelerate engine and component warm-up, refining ITM control logic through linear mapping and advanced signal filtering for precision, and enhancing zero-flow operation for minimizing lubricant oil dilution during start-up and reducing heat loss under low ambient conditions. Additional optimizations include port-specific adjustments and radiator flow distribution strategies to improve system responsiveness and fuel economy. Standardized HVAC configurations were implemented to ensure reproducibility across WLTP vehicle and bench testing scenarios. The methodology validated key improvements through rigorous testing on a newly developed engine platform and demonstrated scalability by successfully integrating these measures into vehicles designed to comply with EU7 regulations. Results indicate substantial gains in warm-up performance, coolant temperature control stability, energy efficiency, and regulatory compliance. Furthermore, these advancements underscore their practical application for automakers seeking novel solutions to meet evolving environmental standards and enhance market competitiveness. Overall, this study presents a set of scalable and widely applicable strategies for modern spark-ignition engines, supporting both new engine development and optimization of existing engines, while addressing global fuel-efficiency and emissions challenges effectively.
Lee, Changjoo, Lee, Kyumin, Kim, Seonyeong, Nam, Choonho, Yoo, Jihun
Standardization of On-Vehicle Measurement of BEV Thermal System Energy Consumption and Range Impacts2026-01-01324/7/2026
This paper presents research and digital twin modeling results to support work on a methodology to properly account for the energy consumed by the thermal system of a BEV, for use within both existing Petroleum-Equivalent Fuel Economy (PEFE) calculations, and the proposed addition of hot and cold weather range values to the consumer-facing Monroney label [1]. Properly accounting for thermal system impacts would incentivize minimizing energy consumption of these systems, since 1) BEV PEFE is a direct input to an OEMs overall CAFE performance, and 2) the values on the Monroney label has some impact on consumer vehicle choice. The impetus for this work was Final Rules issued by the EPA and NHTSA in early 2024 eliminating A/C Efficiency Credits for BEVs from the 2027 MY, thus eliminating regulatory incentives to minimize energy consumption of these systems. Higher energy consumption will produce a number of negative secondary effects, including higher real-world greenhouse gas emissions, reduced vehicle range, greater strain on the nation’s electrical grid, and higher vehicle mass leading to reduced vehicle safety - should OEMs opt to merely install larger batteries to address cold and hot weather range impacts instead of implementing lower energy-consuming technology. The results from the analysis, which ideally would be confirmed with follow-up vehicle tests, show that for a baseline, PTC-heat based system, thermal system energy consumption represents 19.2% of the total energy consumed by a BEV on an annual basis, using an ambient-VMT weighted approach. It seems to be the technical equivalent of “straining at a gnat while swallowing a camel” to focus so much time and energy on identifying incremental improvements in energy consumption from the propulsion-portion of a BEV, while by comparison ignoring the system that according to this analysis can account for nearly 20% of the total on an annual basis.
Taylor, Dwayne
On-Road Vehicle Testing and Characterization2026-01-01954/7/2026
Vehicle testing for fuel economy and emissions is typically performed indoors over standard dynamometer drive schedules to minimize variability and maximize repeatability of the results. In contrast, during on-road operation, operational parameters such as vehicle speed and acceleration and environmental factors such as temperature and wind will change unpredictably. These factors influence vehicle fuel economy and emissions, making on-road operation much more variable than dynamometer results. However, even though on-road conditions may be unpredictable, the on-road operational data can still be used to characterize vehicle performance. This paper describes the development of an on-road vehicle test methodology, with a focus on accounting for on-road factors with a high degree of accuracy while requiring only an achievable and reasonable amount of data. To develop this methodology, a 2016 Honda Civic was instrumented and driven multiple times over a route covering urban, rural, and freeway segments. Vehicle operational data, environmental conditions, fuel consumption, and emissions were recorded. The route was divided into segments and drive cycle parameters were calculated for each segment. Simple empirical equations were developed for this vehicle correlating fuel consumption with drive cycle parameters and the environmental conditions. The empirical models were compared to fuel consumption data from dynamometer tests with good results. Criteria pollutants (CO, NOx, and THC) were also measured and compared to dynamometer data. Finally, the amount of testing and data required to adequately characterize vehicle performance is discussed.
Moskalik, Andrew, Barba, Daniel
Embedded Real-Time Control of a Distributed Trailer Propulsion System with Regenerative Braking for Net Neutral Load Towing2026-01-00654/7/2026
Towing imposes substantial efficiency penalties on both battery-electric vehicles (BEVs) and internal combustion engine (ICE) vehicles, reducing range by 30-50%. This paper presents a proof-of-concept embedded control architecture for distributed trailer propulsion that actively regulates drawbar force to reduce towing loads. Unlike proprietary e-trailer systems requiring specialized hardware, the proposed implementation demonstrates feasibility using commercial off-the-shelf (COTS) components and open-source software. The distributed architecture employs dual Raspberry Pi 4B single-board computers communicating via ROS 2 at 20 Hz. The trailer-mounted controller executes a Simulink-generated control node coordinating load cell acquisition (HX711 ADC), motor CAN bus telemetry, and throttle commands to a 5 kW BLDC traction motor powered by a 5 kWh LiFePO4 battery pack. A vehicle-mounted controller logs OBD-II/CAN validation data. The control pipeline implements cascaded EWMA/Hampel digital filtering with intentional phase lag for hitch-force regulation. The system was validated through on-road testing with an ICE towing vehicle pulling a 1,000-lb trailer over standardized 2.1 km segments following SAE J1321 Type II procedures. Preliminary trials demonstrated stable control performance with drawbar force regulation with no oscillatory behavior. Fuel consumption measurements showed promising improvements (9.4% lower fuel consumption in assisted vs. baseline conditions), though limited sample size precludes definitive causal claims. The primary contribution is establishing technical feasibility of cost-effective COTS implementation (USD 5,000 hardware cost) for trailer propulsion control, providing a foundation for expanded validation studies and commercial deployment pathways.
Joshi, Gaurav, Adelman, Ian, Liu, Jun, Donnaway, Ruthie
Dynamic Programming–Based Fuel-Saving Predictive Cruise Control12-09-03-00224/2/2026
This article investigates the optimization problem of fuel economy for heavy-duty commercial vehicles. A Dynamic Programming–Based Fuel-Saving Predictive Cruise Control (DP-FSPCC) method is proposed, which is based on the Bellman optimality principle and uses the cost function to evaluate the optimal feedback control gain, thereby improving the fuel economy of heavy-duty commercial vehicles on complex roads with varying slopes. To address the issues of low accuracy in road feature representation and poor adaptability to different driving conditions in existing slope reconstruction algorithms, the road ahead is dynamically segmented for high-precision processing by integrating ADASIS (Advanced Driver Assistance Systems Interface Specifications) map information with significant turning point detection and dynamic sensitivity analysis. An engine fuel consumption mapping model based on local gradient information is established to provide an accurate cost function for dynamic programming. Furthermore, a feedforward optimization mechanism based on slope classification is proposed. This mechanism adopts a differentiated cost function weight design strategy for different road conditions, making the control strategy more in line with actual driving experience, effectively reducing the computational complexity of dynamic programming and improving the real-time performance and optimization efficiency of the algorithm. Finally, through numerical simulations and real-vehicle tests on highways, the effectiveness and superiority of the proposed method are verified.
Jin, Dapeng, Shuai, Yue, Wu, Xin, Jia, Tong, Qiao, Zhiyuan, Chang, Shiwei, Mu, Tong
How higher-quality gasoline keeps modern engines CLEAN AND EFFICIENT26AUTP03_033/1/2026
Gasoline direct injection (GDI) engines are the most common technology on American roadways in 2025, and soon, an industrywide gasoline quality standard will better reflect their unique operational needs. Here's why that's important. It's no secret that fuel economy has been one of the greatest driving forces of automotive evolution over the past several decades. As corporate average fuel economy (CAFE) standards have grown increasingly lofty, OEMs eke out new efficiencies from every area of the vehicle. One of those areas, of course, is the engine, and many OEMs have deployed gasoline direct injection (GDI) technology, which is becoming the most common engine technology on American roadways. But while GDI engines proliferate, varying fuel additization throughout North America has not necessarily kept pace with their unique needs and can, in fact, hinder those engines from meeting and sustaining their full fuel economy potential.
Blackburn, Brett
EDITORIAL: Politics hits engineering, but harder26AUTP03_053/1/2026
The U.S. auto industry might be getting “more than what they asked for” when it comes to slashing federal fuel economy regulations. That's a quote from Cox Automotive's director of industry insights, Stephanie Valdez Streaty, and reported by multiple outlets. This is a topic you'll find addressed in this month's Supplier Eye (page 6), but it's worth mentioning here just as one more marker in the sand of where things look like they are headed. On February 12th, the U.S. EPA rescinded the scientific finding that greenhouse gas emissions pose a threat to public health. As vehicles are a main source of GHGs, this finding allowed regulators to, well, regulate. The current White House discounts scientific findings it finds inconvenient, and has now weakened the EPA's power to regulate fuel economy standards. News reports say the administration is likely to reduce the current, agreed-to rules requiring 50.4 mpg (4.67 L/100km) new-vehicle fleet average by model year 2031 to just 34.5 mpg (6.82 L/100km).
Blanco, Sebastian
Optimization of Combustion Stability and Fuel Economy for Dedicated Hybrid Engines with High Exhaust Gas Recirculation Rate03-19-02-00082/26/2026
In recent years, the rapid growth of hybrid vehicles has driven the development of dedicated hybrid engines (DHEs) as a key powertrain technology for achieving high thermal efficiency and low emissions. Driven by stringent emissions regulations and demand for improved fuel economy, enhancing thermal efficiency in gasoline engines remains a critical industry challenge. Exhaust gas recirculation (EGR) technology dilutes oxygen in the intake charge, suppresses knock, and optimizes combustion phasing. However, excessive EGR rates compromise combustion stability by inducing elevated cyclic variability and potential misfire, posing challenges in maintaining stable combustion and improving fuel efficiency at high EGR levels. Thus, combustion stability and fuel efficiency optimization in Geely’s DHEs under high EGR conditions was investigated in this article. In this study, a high tumble combustion system was designed to enhance charge motion and promote stable flame propagation. Furthermore, exhaust gases were drawn from the upstream side of the three-way catalyst to realize high EGR rate. Additionally, high-energy ignition system was applied to ensure stable combustion under high EGR dilution conditions. Compared with the 1.5T engine with a similar technical route, the optimized DHE achieved a 5.4% increase in EGR rate and a 7.2 g/kWh reduction in brake specific fuel consumption (BSFC). These results demonstrate the feasibility of high EGR operation in gasoline engines through synergistic combustion system design and ignition enhancement, offering a scalable solution for meeting future fuel efficiency and emissions targets.
Li, Qiang, Deng, Xiaorong, Ren, Siming, Zhang, Peiyi, Zhu, Yunfeng, Li, Hongzhou, Yan, Pingtao, Gu, Xiangsheng
Intelligent Steering System to Improve Fuel Efficiency in Heavy Duty Vehicles2026-28-01032/12/2026
In commercial vehicles, conventional engine-driven hydraulic steering systems result in continuous energy consumption, contributing to parasitic losses and reduced overall powertrain efficiency. This study introduces an Electric Powered Hydraulic Steering (EPHS) system that decouples steering actuation from the engine and operates only on demand, thereby optimizing energy usage. Field trials conducted under loaded conditions demonstrated a 3–6% improvement in fuel economy, confirming the system’s effectiveness in real-world applications. A MATLAB-based simulation model was developed to replicate dynamic steering loads and vehicle operating conditions, with results closely aligning with field data, thereby validating the model’s predictive accuracy. The reduction in fuel consumption directly translates to lower CO₂ emissions, supporting regulatory compliance and sustainability goals, particularly in the context of tightening emission norms for commercial fleets. These findings position EPHS as a cost-effective and scalable solution for improving vehicle efficiency and environmental performance. Furthermore, the study highlights the future potential of transitioning to fully electric power steering systems (Full EPS), which not only promise additional efficiency gains but also enable seamless integration with Advanced Driver Assistance Systems (ADAS), laying the foundation for enhanced safety, automation, and intelligent vehicle control in next-generation commercial vehicles.
T, Aravind Muthu Suthan, Mani, Kishore, Ayyappan, Rakshna, D, Senthil Kumar, S, Mathankumar
Development of Plug-In Hybrid Motorbike and Analysis towards Sustainable Urban Mobility2026-28-01112/12/2026
The transportation system is one major catalyst to urban ecological imbalance. In developing countries, two-wheelers are considered a major mode of urban personal transportation because of their compactness, easy maneuver in heavy traffic and good fuel efficiency. In India, middle and lower middle-class people prefer to choose two wheelers, and these vehicles are dominantly fuelled by gasoline. Although, the energy consumption by a two-wheeler is comparatively less than that of a four-wheeler, they use about 60% of the nation’s petroleum for on-road vehicles and the impact on urban air quality and climatic change is significantly high. This high proportion of gasoline utilization and emission contribution by two wheelers in cities demand greater attention to improve urban air quality and near-term energy sustainability. Electrification of two-wheelers through the application of a plug-in hybrid idea is a promising solution. A plug-in hybrid motorbike was developed by putting forth a novel drive technique, which demonstrated the advantages of reducing greenhouse gas emissions and using less fuel. The experimental investigation reveals noticeable petroleum fuel savings and greenhouse emission reduction. Through the installation of a hub motor in the rear wheel, the dynamic behaviour of the prototype was examined and observed marginal changes in ride parameters. A cost-benefit analysis was also performed to estimate the payback period for the additional cost incurred.
Kannan, Prashanth, Shaik, Amjad, Talluri, Srinivasa Rao
Plasma Surface Activation for Stronger, More Durable CFRP Bonds in Aerospace26AERP02_012/1/2026
Carbon fiber-reinforced polymers (CFRPs) have become essential in modern aerospace structures, from fuselage skins and wing components to nacelles, interior structures, and a growing range of primary load-bearing parts. Their high strength-to-weight ratio delivers major benefits in fuel efficiency, payload capacity, and fatigue performance. Yet achieving reliable adhesive bonds on CFRP surfaces remains a persistent engineering challenge. The low intrinsic surface energy of composites - particularly under thermal cycling, vibration, and moisture exposure - limits bond durability unless surfaces are properly prepared. Plasma surface treatment has emerged as a pivotal solution, offering a fast, controllable, and non-destructive way to increase surface energy, improve wettability, and enhance adhesion across complex geometries. This is especially important as the aerospace industry transitions from thermoset to thermoplastic composites (TPCs), which enable faster processing, lower production costs, and better recyclability.
Direct Deposition of Nickel Abrasion Guards on to Carbon Filled Composite Rotor Blade StructuresSM-2026-VLADA-51991/27/2026
Composite materials have become widely adopted in commercial aviation, as aerospace manufacturers look to use them to drive weight reduction and improved fuel efficiency in new aircraft designs. In the case of aircraft rotary blades, the poor wear properties of these materials have necessitated the development of metal leading edge guards that can provide critical protection against erosion and impact damage during flight. Electroforming has been a leading process for the manufacture of these protective guards, with nickel parts providing excellent wear resistance that significantly extends the service life of the rotary blade assembly. Currently there has not been a focus on utilizing direct electrodeposition of metal on to carbon filled epoxy composite structures, as traditional plating-on-plastics approaches require considerable effort in surface preparation and normally do not provide adequate adhesion to the underlying structure. Alpha Metalcraft Group has been working in cooperation with aerospace suppliers in the design of an electroplating ready composite structure that would allow for direct nickel deposition, provide excellent adhesion, and significantly reduce both the time and cost for the manufacture of ready-to-assembly rotary blade structures. Test panels were constructed of commercially available prepreg materials or by resin infusion of dry fabrics that incorporated different metal containing conductive layers to allow for the direct deposition through a nickel sulfamate electrodeposition process. Different surface modification strategies were investigated to expose the metal conducting layer and thereby provide the metal-to-metal bonding surfaces required for successful electrodeposition.
Cazzaniga, Luigi
Electroluminescent Coating Systems for Heavy-Duty Trucks: Advancing Safety and Sustainability through Smart Surface Technology2026-26-02751/16/2026
As the transportation industry pivots towards safer and more sustainable mobility solutions, the role of advanced surface technologies is becoming increasingly critical. This paper presents a novel application of electroluminescent (EL) coating systems in heavy-duty trucks, exploring their potential to enhance vehicular safety and reduce environmental impact through lightweight, energy-efficient lighting integration. Electroluminescent coatings, capable of emitting light uniformly across painted surfaces when electrically activated, offer a transformative alternative to conventional external lighting and reflective materials. In the context of heavy-duty trucks, these systems can significantly improve visibility under low-light and adverse weather conditions, thereby reducing the risk of road accidents. Furthermore, the uniform illumination achieved without bulky fixtures contributes to aerodynamic efficiency, supporting fuel economy and reducing carbon emissions. use of this coating system, can optimize tooled up plastic part and sub-assemblies specially to those parts we use for indication, marking, highlight & lighting assisting during dark This paper identifies and evaluates specific use cases where EL coatings can deliver substantial benefits: for example, Exterior Lighting systems, Perimeter Lighting for Night Operations, Ingress/degrees illumination with Integrated Safety Features, Emergency and Breakdown Visibility & Trucking illumination accessories. Accentuate brand specific, Technology & design features over a truck
Harel, Samarth Dattatraya, Borse, Manoj, L, Kavya
Mathematical Modeling and Genetic Algorithm-Based Energy Management in Hydrogen PEM Fuel Cell Electric Vehicles2026-26-02571/16/2026
Hydrogen Fuel Cell Electric Vehicles (FCEVs) represent a significant trajectory in vehicular decarbonization, harnessing the inherently high energy density of diatomic hydrogen within electrochemical conversion systems. When sourced via renewable pathways, such hydrogen facilitates propulsion architectures characterized by zero tailpipe emissions, enhanced energy efficiency, and extended operational range profiles. Realizing peak systemic efficacy necessitates the synergistic orchestration of high-fidelity fuel cell stack design, resilient compressed gas storage modalities, and nuanced energy governance protocols. To reduce transient stressors and guarantee long-term electrochemical stability, employing multi-scale modeling and predictive simulation, combined with constraint-aware architectural synthesis, is crucial in handling stochastic driving conditions spectra. This study develops a high-fidelity mathematical plant model of a hydrogen Proton Exchange Membrane (PEM) fuel cell vehicle and implements advanced Energy Management Strategies (EMS). The FCEV plant model is developed with the forward approach method, taking into account the power limitations of the power plant. A PEM fuel cell system is accurately and in detail modeled, representing voltage loss mechanisms. The performance of the mathematical model was calibrated with the experimental results with an error margin of 8-10%. Whereas, a permanent magnet synchronous motor is modeled mathematically along with a Field-Oriented Controller (FoC) for ensuring precise torque regulation. Energy Management Strategies (EMS) optimize fuel cell and battery coordination to boost vehicle performance and efficiency. Online EMS adapts control using real-time data, while offline EMS applies machine learning to past driving patterns for predictive energy allocation. In this study, a Genetic Algorithm (GA)-based EMS, which is one of the types of offline EMS, is implemented to enhance fuel economy, dynamic performance, and component-level energy usage. Compared to non-optimized operation, the GA approach offers improved power split efficiency, 9-12% improvement in hydrogen consumption, resulting in lower energy consumption and enhanced overall vehicle performance. This work improves PEM FCEV technology through better design, simulation, and optimization methods, laying a solid foundation for future advancements in sustainable and efficient transportation.
Mulik, Rakesh Vilasrao, E, Porpatham, Senthilkumar, Arumugam
Wheel Corner Module Energy Losses and Potential Improvements2026-26-00961/16/2026
With the inevitable shift of automotive industry towards E-mobility and mandatory fuel efficiency targets, there is a need to evaluate the energy losses in the vehicle & identify potential areas of improvement. Energy losses are calculated for different components in the corner module system of a passenger car. Contribution of losses (resistances) from respective component are depicted using simple analytical models. Potential energy saving improvements were identified and analyzed basis emerging technologies in respective areas.
Raghatate, Kumar Shreyas, Vedartham, Raghavendra, Khanger, Rakesh, Bisht, Arun
Data-Driven Prediction of Global Automotive Trends: Forecasting Fuel Economy and CO₂ Emissions Using Machine Learning2026-26-06431/16/2026
In the pursuit of environmental sustainability and cleaner transportation, the global automotive industry is expediting transformation. This paper utilized multi-decade data spanning from 1975 to 2024, for the development of predictive models for fuel economy and CO₂ emissions across a wide range of vehicle technologies from 2026 - 2050. This is done with the help of advanced machine learning algorithms like Linear and Random Forest Regression in Python and integrating insights through Power BI visualizations, the project identifies key correlations between vehicle attributes such as weight, powertrain, and footprint and their environmental performance. Results highlight the increasing impact of electric vehicle adoption, hybridization, and light weighting on overall emissions reduction. These insights help forecast the direction of fuel economy standards, emission patterns, and technology shifts across manufacturers and vehicle types. Beyond technical predictions, the study offers a decision-support framework for global policymakers, automotive designers, and sustainability advocates. The findings provide the importance of data-driven approaches that can increase regulatory compliance, influence the innovation process, and support sustainable mobility solutions on a global scale.
Hazra, Sandip, Tangadpalliwar, Sonali, Hazra, Sanjana
Representative Drive Cycle Velocity Profiles Prediction Using ML Algorithms for Energy Efficiency2026-26-06381/16/2026
Maximizing vehicle energy efficiency and its performance is a high priority for automotive industries as customers’ expectations rise. Engineers constantly face the challenge of balancing the conflicting goals of achieving superior performance and maximizing energy efficiency, all while meeting increasingly tight development timelines. Leveraging digital methods can potentially enable considerable reduction in development timelines. Driving cycles function as standardized measurement procedures for certifying vehicle fuel efficiency and driving range. Representative velocity profiles condense numerous real-life driving cycles to enable quicker energy analysis and driver feedback evaluations. This paper introduces a novel methodology for generating synthetic drive cycles, such as average velocity cycles and ideal consumption velocity cycles, based on real-life driving scenarios. In this study, the importance of creating representative drive cycles to enhance vehicle performance and energy consumption is highlighted. A detailed analysis of city cycle drives is provided, focusing on the prediction of average and ideal consumption velocity profiles using advanced machine learning, deep learning, and reinforcement learning techniques available in the field of data science. By leveraging data from numerous drives conducted at various ambient temperatures throughout the year, these velocity profiles were forecasted. The validation of these models is discussed in the paper, along with how effective and usable this method can be to save time in the overall vehicle development process. The merits and demerits of each ML model used to create synthetic drive cycles are discussed in the paper. This research offers valuable insights for automotive testing and development, significantly improving driver feedback analysis and providing essential insights to enhance driving habits and overall vehicle efficiency.
Kanakannavar, Rohit, Kelkar, Kshitij, Sadalge, Anand
Exploring the Influence of Wheel Rim Width on Tyre Performance through Rig-Testing and Vehicle-Level Evaluation: A Comprehensive Study2026-26-06031/16/2026
With increasing demand for improving the vehicle Ride and Handling (R&H) performance, the synergy between vehicle subsystems such as suspension, chassis, brakes & tyres play a major role towards it. In this regard, the interaction between wheel rim width and tyre performance characteristics is a key focus area in vehicle development process. Detailed research is being conducted worldwide to understand their dynamics of interaction and based on the tested data, vehicle manufacturers make the design selection. In this context, the proposed study aims to provide a in-depth analysis of how variations in wheel rim width affect key tyre performance parameters such as lateral force characteristics, damping property, tyre footprint, and pinch cut resistance. Also, the subsequent influence on vehicle-level performance parameters such as R&H, braking, steering, and durability is captured. Based on these analysis, appropriate wheel rim size selection is done which is most optimal for the project requirements. The study involves multiple rig-level testing and full-vehicle evaluation data through which several observations have been tabulated which reinforce the previous studies and provide new insights. Firstly, it was observed that narrower wheel rims tend to have reduced rolling resistance in turn offering higher fuel efficiency. However, this comes at the cost of reduced lateral grip and stability during vehicle direction-changing maneuvers. In contrast, wider wheel rims enhance traction and cornering power by providing a broader contact patch between the tyre and the road surface. Furthermore, the study shows that the tyre sidewall pinch-cut performance is deteriorated with wider wheel width. This is due to the tyre mounted on a narrower rim showing uniform energy dissipation along the cavity thus preventing any sidewall cuts during curb impacts. In conclusion, this study shows a detailed perspective on the intricate relationship between wheel rim width and tyre performance characteristics which can help vehicle OEMs to make quicker and informed decisions regarding wheel rim width selection to optimize both performance and efficiency while ensuring safe driving conditions.
Singh, Ram Krishnan, Paua, Ketan, Sundaramoorthy, Ragasruoban, Lenka, Visweswara, ahire, Manoj, Adiga, Ganesh N
First in the Industry 8.5 Ton GVW on Four Tyre Truck with 245/90R16 Tyre – A Global First2026-26-06021/16/2026
This project introduced a brand-new tire size 245/90R16 for the first time globally in the 16-inch tube-type category, designed specifically for commercial vehicles with Vehicles 8.5T -12T gross vehicle weight (GVW). The main goal was to create a compact vehicle that can carry more payload, reduce overall weight, and improve fuel efficiency with use of rear single tyre instead of twin tyre in 8.5T. This helps customers lower their operating costs and improve vehicle performance, especially on narrow roads. The new tire supports high load capacities: up to 2300 kg for single tire use and 2180 kg for dual tire fitment. It enables a new type of vehicle to be developed an 8.5-ton GVW vehicle with rear single tires offering better payload capacity without increasing the size of the vehicle. By using this new tire, the kerb weight of the vehicle is reduced, which increases the payload and helps improve fuel economy. This helps lower the cost of the vehicle by optimizing surrounding components design. This new tire has been tested and approved as per Indian Standards (IS) also, successfully added to the IS tire regulations. This concept is evaluated through new vehicle program development through vehicle development cycle. It consist of complete vehicle-level design,, design reviews (DR), and Design validation planning (DVP). This invention supports to create a new segment of vehicle which is cost effective, compact vehicles, offering value to customers. This will create a new industry benchmark.
Pawar, Dhondiram Dnyandeo, Shaikh, Matin, Ambekar, Prasad
Items per page:
1 – 50 of 7977