Search Results (1,120)

This study addresses an off-site construction (OSC) task: installing heavy prefabricated equipment modules at elevated positions inside existing structures. The task simultaneously demands multi-ton payload capacity, a lift height approaching 10 m, and holonomic maneuvering in narrow aisles; to the authors’ knowledge, no single reported platform satisfies all three. We present a heavy-duty, high-lift mobile robot that lifts 6 t to 8 m. Two active swerve-drive modules and three passive casters form a five-point asymmetric layout combining holonomic mobility with load distribution, and the lift unit functionally decouples the vertical stroke (four helical band actuators) from the lateral stiffness (four scissor-stabilizing mechanisms). Planar motion is partitioned into three driving modes with closed-form forward and inverse kinematics, and zero-velocity transitions remove the kinematic model mismatch and the instantaneous-center-of-rotation discontinuity of a single unified model. Prototype measurements confirmed the motor-sizing torque assumptions, and chassis finite element analysis showed a factor of safety above 2.0 under maximum payload and quantified the in-plane stress induced by kinematic mismatch. In two field deployments, the robot reduced personnel by 25.0–27.3%, equipment by 42.9–60.0%, and installation duration by 50.0–85.7% relative to the incumbent methods, thereby extending mobile robots from horizontal transport to vertical OSC module installation. Full article

Greenhouse gas emissions from heavy-duty vehicles (HDVs) must be drastically reduced. Battery electric trucks (BETs) are the main option for low-carbon road freight transport, but they require recharging infrastructure. However, a thorough cost analysis of public charging is lacking, especially for the Megawatt Charging System (MCS). This study estimates the infrastructure-related levelised cost of megawatt charging for battery electric trucks in Europe based on simulated truck operations and techno-economic modelling. The analysis combines empirical driving data with cost assumptions for MCS infrastructure. The reported values are infrastructure-only costs and include annualised capital expenditure, installation costs, grid connection costs and operating expenditure. They exclude electricity prices, taxes, levies, land costs and operator margins. Low- and high-cost scenarios differ in assumed charger hardware and installation costs, while grid connection costs and utilisation assumptions are held constant across scenarios. The results show that utilisation is the key driver of cost reductions over time. The infrastructure-related levelised cost of MCS declines to 0.03–0.07 EUR/kWh by 2050 under the analysed cost assumptions. The total annual infrastructure costs for Europe are estimated at 6.6–10.8 billion EUR, or 2.9–4.7 EUR cents/km. The results support policy decisions on infrastructure deployment and highlight the importance of coordinated rollout and demand growth. Full article

Hydrotreated vegetable oil (HVO) is considered a promising drop-in alternative to conventional diesel fuel for reducing greenhouse gas emissions in road freight transport. However, empirical evidence on its performance under real-world operating conditions remains limited. This is particularly true for complex logistics systems such as agricultural transport. This study assesses the effect of neat HVO (HVO100) on fuel consumption using high-resolution vehicle operational data collected from three heavy-duty trucks during a full-scale sugar beet logistics campaign in Germany. Vehicle operation was recorded via a manufacturer-independent fleet management system interface and combined with satellite-based positioning data for route reconstruction. After data preprocessing and quality filtering, a total of 3353 valid transport tours were analyzed. Fuel consumption values during HVO100 operation were corrected for density-related measurement bias. The effect of fuel type was evaluated using a linear mixed-effects model. The model accounted for load status, route topography, driving speed, and their interactions. In addition, stratified pairwise comparisons were conducted across operational conditions. The results show that, in the full three-vehicle model, HVO100 was associated with a statistically significant increase in fuel consumption of 0.51 L/100 km under baseline conditions with an empty vehicle, low topographic variability, and medium driving speed, corresponding to approximately 2.3%. In a sensitivity analysis excluding the diesel-only truck, the estimated difference decreased to 0.34 L/100 km and was no longer statistically significant. Load status and topography were identified as the dominant drivers of fuel consumption with substantially larger effects than fuel choice. Overall, the findings indicate that the effect of HVO100 on fuel consumption is small relative to operational variability. Under many real-world operating conditions, operational factors outweighed the differences attributable to fuel type. These findings indicate that switching to HVO100 did not result in a substantial volumetric fuel-consumption penalty in the investigated agricultural logistics system. Full article

Marine deck coatings suffer from premature failures such as wear thinning, flaking, and brittle cracking under repeated rolling, abrupt stopping/steering, and high shear loads of heavy equipment due to the imbalance of hardness, strength, toughness, and wear resistance. To address this issue, a rolling load-resistant coating system with an epoxy–amine/epoxy–thiol dual-crosslinked network was constructed using liquid polysulfide rubber (Lp-3) as the key crosslinking modifier, and the effect of Lp-3 content (0–2 wt%) on the comprehensive performance of the coating was systematically investigated. The results showed that the coating achieved the optimal synergy of properties at 1 wt% Lp-3 loading: Shore hardness reached 88.7 HD with the pencil hardness maintained at 8H, adhesion strength increased to 7.2 MPa, Taber abrasion loss significantly decreased to 14.8 mg, tensile strength rose from 5.5 MPa to 12.4 MPa, elongation at break nearly doubled, shear strength reached 10.2 MPa, and the failure mode transformed from brittle cleavage to ductile shear. Mechanistic analysis revealed that the terminal thiol groups of Lp-3 underwent a click reaction with epoxy groups, covalently embedding flexible polysulfide segments into the rigid epoxy network and forming Fe–S interfacial chemical bonds to enhance adhesion. The microphase separation, chain relaxation, and energy dissipation mechanisms effectively blunted crack propagation and alleviated stress concentration, while maintaining sufficient surface hardness and the continuity of the load-bearing skeleton. This work realizes the synergistic optimization of high strength, high toughness, strong adhesion, and excellent wear resistance for marine deck coatings and provides a new strategy and critical technical parameters for the design of functional coatings under heavy-duty dynamic service environments. Full article

The startup process of gas turbines driven by the static frequency converter (SFC) exhibits complicated electromechanical coupling characteristics. Conventional simulation methods fail to integrate physical modeling with sequence of event (SOE) data and cannot support co-simulation of multiple startup schemes at the power station level. In this paper, a hierarchical digital twin architecture oriented to gas turbine SFC startup is established to realize intelligent deduction of sequential control and break through the technical limitations of traditional simulations. Relevant waveforms and data of the F-class heavy-duty gas turbine during startup are obtained via the digital twin. The maximum effective value of voltage is 12.07 kV, the maximum effective value of current is 1.6 kA, and the peak output power of the SFC reaches 15.67 MW. The system achieves the rated speed (3000 rpm) within an acceptable start-up duration, demonstrating satisfactory dynamic response. All the above data conform to the preset startup parameters and operation control logic of heavy-duty gas turbines. Full article

Ammonia is increasingly regarded as a carbon-free energy carrier for hard-to-electrify power sectors, including marine propulsion, heavy-duty transport, and distributed generation. Its direct use in internal combustion engines, however, is constrained by high ignition energy, low laminar flame speed, narrow flammability limits, slow low-temperature chemistry, and strong trade-offs among efficiency, nitrogen-containing emissions, and unburned ammonia slip. Hydrogen enrichment is one of the most effective routes for improving ammonia combustion reactivity, but it also introduces a multivariable control problem: hydrogen fraction, ammonia injection timing, injection mode, air-path dilution, ignition strategy, and aftertreatment operation are tightly coupled and strongly condition-dependent. This review synthesizes recent progress in ammonia–hydrogen and ammonia-based dual-fuel engine control from a control-oriented perspective. The discussion first summarizes application scenarios, nonlinear combustion-mode transitions, emission-formation pathways, and control-relevant metrics. It then compares actuator-level strategies, including ammonia injection timing and staging, port and direct injection, hydrogen energy-fraction scheduling, excess-air-ratio and EGR control, high-energy ignition, and turbulent jet ignition. Advanced optimization methods are further reviewed, with emphasis on model predictive control, control-oriented combustion and emission models, artificial-intelligence-based virtual sensors, and reinforcement-learning control. The analysis shows that the central challenge is no longer whether ammonia can burn in an engine, but how a controller can keep the system inside a narrow moving window bounded by misfire, knock, NO_x, N₂O, and NH₃ slip. Finally, future research priorities are proposed, including engine–aftertreatment co-optimization, physics-informed virtual sensing, digital-twin-assisted calibration, lightweight deployment on electronic control units, and robust control under fuel and aging uncertainty. Full article

Electrohydrodynamic (EHD) actuators offer a promising approach for active particulate matter (PM) control in heavy-duty and marine exhaust systems. However, continuous DC corona discharge often leads to excessive energy consumption and is susceptible to aerodynamic re-entrainment in high-velocity flows. This study introduces an idealized transient advection mechanism combining a macroscopic corrugated duct geometry with high-frequency pulsed EHD actuation. A fully coupled, time-dependent multiphysics model—integrating RANS turbulent flow, Poisson-Nernst-Planck space charge transport, and Lagrangian discrete particle tracing—was developed to analyze the physical kinetics of 0.2 µm soot particles. The results demonstrate that the corrugation troughs act as effective aerodynamic dead zones with partial electrostatic shielding, creating aerodynamic and electrostatic dead zones. During active microsecond voltage pulses (25 kV peak), intense Coulombic forces rapidly overcome turbulent drag, driving kinetic injection of particles into the corrugation troughs. During the resting phase, particles remain securely trapped by aerodynamic shielding, significantly mitigating the risk of aerodynamic re-entrainment under the simulated conditions. A comprehensive parametric analysis revealed that an optimized 500 Hz pulse with a 5% duty cycle maintains a robust 82.7% trapping efficiency. Compared to standard continuous DC precipitators, this pulsed actuation strategy requires an idealized active corona power of 15.3 mW. This study provides fundamental physical insights into transient EHD flows and establishes optimized design criteria for fundamental EHD transport models. Full article

Aiming at the problems of fault samples being difficult to obtain in fault diagnosis research on heavy-duty bearings of thin-seam shearers and the insufficient diagnostic performance of existing methods under small-sample conditions, this study focuses on dataset construction, sample augmentation and fault diagnosis. First, based on the virtual prototype model of the cutting-unit transmission system of a thin-seam shearer, three-dimensional models of healthy bearings and four typical fault types (inner ring fault, outer ring fault, rolling-element fault and cage fault) of heavy-duty bearings were built using SolidWorks 2024. Vibration signals were collected through ADAMS dynamic simulation and converted into time-frequency images via Continuous Wavelet Transform (CWT), thereby constructing an original fault dataset with five states. Furthermore, a conditional generative adversarial network incorporating VGG perceptual loss (VGG-CGAN) was proposed to achieve targeted sample augmentation for the five bearing states, effectively alleviating the class-imbalance problem. On this basis, an improved ResNet50 fault-diagnosis model was constructed, and Bayesian optimization was used to automatically tune key hyperparameters. Experimental results show that the improved ResNet50 model achieved an accuracy of 87.14% on the self-built thin-seam shearer heavy-duty bearing dataset and 98.28% on the public CWRU dataset. The proposed method exhibits strong diagnostic performance and generalization ability under small-sample and imbalanced data conditions. This study can provide new ideas and useful references for fault diagnosis of heavy-duty bearings in thin-seam shearers. Full article

Constant-speed control of hydraulic retarders is essential for improving driving safety and reducing driver workload on long downhill roads. For heavy-duty battery electric trucks (BETs), regenerative braking provides a fast-response braking source and enables energy recovery, offering the potential to improve both speed regulation and energy efficiency. This study proposes a two-mode constant-speed downhill control framework for BETs. In the retarder braking mode, a variable-argument proportional–integral–derivative (VAPID) controller is employed to regulate the hydraulic retarder, with its parameters optimized by an improved seeker optimization algorithm (ISOA). In the cooperative braking mode, a parallel dual-controller structure is adopted, where the retarder is governed by ISOA-VAPID and regenerative braking is regulated by a fuzzy-tuned PD controller according to real-time battery states. To further improve energy recovery, an optimization-based AMT gear-shifting schedule and coordinated strategy are incorporated. The proposed framework is validated through offline simulations, sensitivity analysis, and driver-in-the-loop experiments under constant-slope, variable-slope, and real-world downhill road conditions. Results show that the retarder braking mode outperforms benchmark methods in steady-state accuracy and dynamic response. In the cooperative braking mode, braking energy is effectively recovered while the battery charging load under unfavorable battery states is reduced. Moreover, AMT gear shifting improves energy recovery efficiency with negligible influence on constant-speed performance. Full article

To address the inefficiency of demolition robots at nuclear contamination sites due to frequent retreats to safe zones for attachment replacement, this study develops and experimentally evaluates a six-wheeled mobile platform for attachment-replacement support near the work area. Structurally, the prototype adopts a well-established passive rocker-bogie suspension architecture combined with six-wheel independent drive. The focus of this work is not to claim a new suspension topology, but to evaluate its engineering feasibility and drive-load margins for a heavy-duty nuclear support platform through multibody simulation and onboard-sensor measurements. A constrained multibody model was implemented in ADAMS/Simulink to represent rocker joints, wheel revolute joints, actuator limits, and wheel–ground contact. A full-scale prototype was tested on representative nuclear-facility terrain conditions, including a 20° slope and a 250 mm vertical step. The results show that the prototype completed both tests while the measured motor torques remained within the allowable drive range. The positive and negative torque signs observed on the left and right sides are explained by mirrored motor installation and coordinate definitions rather than by a special torque-distribution mechanism. This study provides a structural selection and experimental performance reference for mobile operation support in radiation environments. Full article

Hydrogen sampling is an essential part of ensuring reliable and accurate hydrogen fuel quality for expanding heavy-duty vehicle applications. Hydrogen sampling at refuelling stations is highly sensitive to operational conditions, especially temperature, pressure, storage homogeneity, and nozzle-purging procedures. The direct sampling method operates with a hydrogen fuelling station in maintenance mode and requires that parameters be set properly. This study investigated the impact of temperature, pressure, storage bank selection, and venting on hydrogen sample quality. This study shows that hydrogen sampling at refuelling stations is strongly influenced by operational parameters, with temperature and pressure mainly affecting the water content while other contaminants remain largely stable; storage bank composition and insufficient nozzle purging can also significantly bias results through contamination or non-representative sampling. To ensure reliable measurements, this study recommends conducting sampling under representative operational conditions, including matching the delivery temperature and nominal delivery pressure, verifying storage homogeneity, and applying adequate nozzle-purging procedures. However, further validation across different systems is still needed. Full article

Background: As global environmental issues and the energy crisis continue to intensify, diesel–natural gas dual-fuel engines have been extensively studied due to their stable combustion, low emissions, abundant natural gas reserves, and relatively low cost. Methods: Based on a modified YCK15 six-cylinder heavy-duty diesel engine, the experiments and GT-SUITE v2016 simulation were used to study the effects of NG substitution rate (NGSR) and diesel injection timing (DIT) on the combustion characteristics, power and emission performance of a diesel–NG dual-fuel engine running at 1800 rpm, with NGSR ranging from 0 to 50% and DIT ranging from 5 °CA BTDC to 17 °CA BTDC under four engine load conditions: 100%, 75%, 50% and 25%. Significant Findings: The results showed that the NGSR and DIT have considerable impact on performance enhancement and emission reduction. As NGSR increased, cylinder pressure decreased under high load and increased under low load. Under four loads, the temperature inside the cylinder revealed a downward trend, and the power and indicated thermal efficiency (ITE) decreased slightly, with power and ITE declining by less than 5% and 2%, but the fuel economy and emissions were well improved. Compared to 50% NGSR and pure diesel condition, brake-specific fuel consumption (BSFC) decreased by 5.63%, 4.60%, 2.98%, and 1.83%, respectively, and NO_x emissions decreased by 32.68%, 36.41%, 37.90%, and 38.99%, respectively. As DIT increased, cylinder pressure and temperature both increased under all four load conditions, and the power and ITE improved significantly, but this caused an increase in NOx emissions. Compared to DIT of 17 °CA BTDC with 5 °CA BTDC, power increased by 8.29%, 9.76%, 13.38%, and 16.51%, respectively, and ITE increased by 7.69%, 8.77%, 11.46%, and 12.77%, respectively. The response surface was established and performance optimized using the design of experiments (DOE) module in GT-SUITE v2016. At an NGSR of 50% and 100% loads, the optimized power was 0.431% higher than the pure diesel mode, ITE was 0.396% higher, brake-specific fuel consumption was reduced by 7.397%, and NO_x emissions were reduced by 27.027%. Full article

Background: Road transport accounts for 73% of transport-related greenhouse gas emissions within the EU, 27% of which are attributable to heavy-duty vehicles. In order to reduce emissions in the area of heavy-duty commercial vehicles, electrifying the fleet offers a perspective. As part of a cooperation between TU Berlin, Siemens and BLG Logistics within the Mobility2Grid research campus, an analysis was carried out to determine how an exemplary BLG depot for regional logistics transport with six diesel trucks can be converted to battery–electric trucks. Methods: This analysis was conducted under a fixed depot schedule with defined dwell times and charging opportunities, with the aim of developing practical recommendations for the acquisition of suitable vehicles and infrastructure. To this end, simulations were carried out using the eFlips consumption and depot simulation software developed at TU Berlin. Results and Conclusions The results show that electrification for regional logistics transport can already be fully implemented with the current state of the art technology and that neither very large batteries nor very high charging powers are required for technically feasible and economically balanced operation. Notably, the cost-optimal battery capacities identified (approximately 200–230 kWh) are currently smaller than those of commercially available 40 t electric trucks, revealing a gap between the model-optimal configuration and present market offerings. Based on the identified optimal configuration, a life cycle assessment (LCA) is conducted to evaluate the environmental impact of fleet electrification. Over a 10-year lifetime, the battery–electric fleet reduces cumulative greenhouse gas emissions by approximately 53% compared to the diesel baseline, with operational-phase savings clearly outweighing higher production-related emissions. The combined techno-economic and environmental assessment provides a structured decision basis for depot-centered fleet electrification. Full article

Heavy-duty freight transport remains one of the most difficult sectors to decarbonize due to its high energy demand, long-distance operation, and strong dependence on diesel fuel. In Chile, more than 90% of heavy trucks operate with diesel engines, contributing significantly to greenhouse gas emissions and local air pollutants. At the same time, Chile has favorable conditions for the development of green hydrogen due to its world-class solar and wind resources. This study presents a technical and economic assessment of green hydrogen fuel cell trucks recently introduced in Chile, comparing their operational performance with conventional diesel freight trucks. A techno-economic framework based on total cost of ownership, fuel consumption, operational range, fleet utilization, and hydrogen price scenarios was developed using information reported in public studies and official Chilean strategic documents. The results indicate that hydrogen trucks are technically suitable for long-haul and intensive-duty operations due to their rapid refueling capability and high operational autonomy. However, economic competitiveness remains strongly dependent on hydrogen price, fleet scale, infrastructure utilization, and vehicle capital cost. Under current market conditions, diesel trucks preserve cost advantages, while hydrogen trucks become increasingly competitive as hydrogen prices approach long-term target values and annual mileage increases. Chile’s renewable resource base positions the country as a strategic candidate for early adoption in mining, logistics corridors, and captive fleets. The study concludes that hydrogen freight transport can become a realistic decarbonization pathway if accompanied by targeted public policies, infrastructure deployment, and industrial scale-up. Full article

Electric trucks play a crucial role in achieving a zero-emission future. As battery electric technology advances, electric trucks are expected to become a cost-effective and sustainable alternative to diesel trucks. Long-haul trucks have unique driving patterns that affect their charging needs, and investigating the expected load profiles is fundamental to conducting a proper assessment of the impact of truck fleet electrification on the charging infrastructure. This article presents an agent-based modeling approach to estimate high-power charging station load profiles, leveraging open data and driver decision-making patterns. The methodology is implemented in a software tool, ABChargingSim, which includes heterogeneous charging logic (distinguishing between urgent mid-shift and long-dwell off-shift charging, as well as different driver triggers to initiate charging) alongside a vehicle’s SOC-dependent power tapering charging patterns. A case study along a Norwegian highway demonstrates the framework’s applicability for evaluating grid impacts under various heavy-duty transport electrification scenarios. The findings illustrate how driver behavior and heavy-duty vehicle charging processes shape expected load profiles, emphasizing the value of such simulation frameworks as essential decision-support tools for the strategic planning and operation of future high-power charging networks. Full article