Browse Topic: Fuels and Energy Sources

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Aging Behavior of Double-Base Propellants under Negative Pressure Conditions2026-99-2320To be published on 10/30/2026
To investigate the effect of negative pressure environment on the aging behavior of solid propellants, a 60-day negative pressure accelerated aging test was carried out on SG-2 propellant with five working conditions: atmospheric pressure at room temperature, atmospheric pressure at 80°C, and negative pressure at 40°C/60°C/80°C. Combined with Fourier transform infrared spectroscopy (FTIR) and differential scanning calorimetry (DSC), the functional group evolution law and thermal decomposition kinetic characteristics of the periphery zone and core zone of the propellant were analyzed. The results show that the propellant exhibits significant inhomogeneous aging characteristics under negative pressure aging. The functional group structure in the periphery zone is more stable in the early aging stage; in the middle stage, components such as DNT and C2 in the core zone migrate to the periphery zone; in the late stage, the undegraded components in the core zone continuously supplement the periphery zone, making the functional group integrity of the periphery zone better than that of the core zone. DSC tests combined with Kissinger and Ozawa methods show that the thermal decomposition activation energy of the propellant decreases continuously with the increase of aging temperature under negative pressure environment, and the activation energy drops to 428.91 kJ/mol after aging at negative pressure 80°C. High temperature accelerates the volatilization of NG, the cross- linking of NC molecular chains and the consumption of stabilizer, leading to the easy breakage of O-NO₂ groups and the significant deterioration of thermal stability. This study clarifies that the aging mechanism of the propellant under negative pressure environment is the synergistic effect of component migration and diffusion, functional group decomposition and molecular chain cross-linking, which provides a theoretical basis for the storage and application of solid propellants in negative pressure service scenarios such as deep space exploration.
Gao, Peizhe, Deng, Hanyu, Tang, Yuqing, Yuan, Yichao, Shen, Nianyu
Optimization Method for UAV Scheduling Based on Beidou2026-99-2352To be published on 10/30/2026
Currently, UAVs are increasingly used in remote sensing monitoring, logistics and distribution, emergency rescue and recreational aerial photography, etc., which puts higher requirements on wireless networks, i.e., how to allocate limited wireless resources in real-time, efficiently and fairly to ensure that a large number of UAVs can work together in complex environments and maintain high-quality communication services. This paper investigates an optimisation method for UAV scheduling based on the BeiDou satellite navigation system, which improves the accuracy and efficiency of UAV mission execution by utilising the high-precision positioning and time synchronisation services provided by the BeiDou system. The results of the experiment showed that as the number of missions increased from 10 to 50, the average mission completion time increased from 8.3 to 12.5 minutes, the average speed increased from 30 to 34 km/h, the average energy consumption increased from 0.8 to 1.2 kWh, the average distance flown increased from 12 to 22 km, the communication success rate decreased slightly from 99.2 to 98.2%, the resource utilization rate increased from 85.1% to 87.5%. These results show that the method performs well in terms of task completion time, energy consumption, communication success rate and resource utilisation, which provides strong support for the application of UAVs in the fields of logistics and distribution, emergency rescue, and so on.
Ji, Hongbin, Jiang, Kexin, Zhang, Dongxue, Bai, Yanhui, Liu, He, Zhang, Shuangna
Numerical Diagnosis and Evidence-Chain Analysis of the Non-Sustained Ignition Process in a Hydrogen/Air Turbulent Diffusion Flame under an LES–PaSR Framework2026-99-2324To be published on 10/30/2026
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Liu, Jiaqi, He, Jiandong, Yuan, Youquan, Duan, Yu
Trajectory Optimization for Non-Cooperative Target Spacecraft Based on Sequential Convex Programming2026-99-2330To be published on 10/30/2026
Autonomous operations near space targets that do not cooperate present great challenges because position and attitude planning must be linked. A target of this type lacks navigation aids or communication systems, which makes relative motion planning much more difficult. Although methods based on convex optimization work well for problems with three degrees of freedom, like planetary landing, their use in integrated operations with six degrees of freedom is limited by constraints that are not convex. To solve this problem, this paper proposes a new framework for servicing spacecraft using sequential convex programming. The primary contribution is the extension of convex methods to high dimensional trajectory planning while adding a robust trust region constraint based on trajectory deviation. This mechanism reduces the chance of finding no solution during convex approximations. It improves reliability and convergence when solving complex problems. The approach first creates a continuous optimal control problem with an index that balances energy use and the angle of the line of sight. Nonlinear dynamics are simplified using first order Taylor expansions. Constraints for the field of view and collision avoidance are modeled using spherical and ellipsoidal regions. The non convex problem is changed into a sequence of discrete convex subproblems and solved through iterations. Numerical simulations show that the servicing spacecraft can safely approach the target with stable attitude while meeting all physical limits. The method using sequential convex programming with a trust region demonstrates great potential in optimizing computational efficiency alongside strong numerical stability, laying a solid foundation for future real-time autonomous trajectory generation in complex orbital environments.
Wang, Yuzhi, Yao, Zihao, Wang, Qian, Han, Ziwen, Zhang, Chao, Zhang, Yumei, Li, Shunli
A Study on Energy Management Strategies for Range-Extended UAVs Based on A-ECMS2026-99-2333To be published on 10/30/2026
An adaptive equivalent consumption minimization strategy (A-ECMS) is proposed for a hydrogen fuel-cell range-extended UAV hybrid power system composed of a PEM fuel cell, a lithium-ion battery and a supercapacitor. The equivalent factor is updated online by a PID-based SOC feedback mechanism to improve the adaptability of conventional ECMS under variable flight loads. Under the same mission profile and the same initial and terminal SOC constraints, A-ECMS consumes 4.6277 g of hydrogen, reducing hydrogen consumption by 46.90%, 67.51% and 58.42% compared with PID control, conventional ECMS and state-machine control, respectively. Fuel-cell power fluctuation and battery SOC deviation are also reduced.
Li, Mengda, Liu, Zitong
Study on Heat Transfer Characteristics of Supercritical Aviation Kerosene in a Rectangular Wavy Microchannel2026-99-2347To be published on 10/30/2026
In a conventional turbine-based combined cycle (TBCC) engine, the hot-end components and combustor wall surfaces bear extreme high- temperature thermal loads. To address this issue, researchers have been consistently exploring optimized cooling and heat transfer schemes. Relevant studies have shown that using aviation fuel as a heat sink can achieve effective thermal protection for such aero- engines. This paper carries out a numerical study on the flow and heat transfer characteristics of supercritical RP-3 aviation kerosene in a rectangular wavy microchannel, with a focus on the impacts of the wavelength-to-height ratio on heat transfer performance. The results show that the geometric structure of the wavy microchannel induces intense flow disturbances, which strengthen the internal energy exchange of the fluid and produce both longitudinal and transverse vortices. These vortices break and compress the thermal boundary layer, thus significantly enhancing the intensity of heat transfer. At the same time, the overall heat transfer performance is improved remarkably with relatively low resistance coefficients. Such excellent heat transfer characteristics can effectively mitigate thermal damage to high-temperature components, which is conducive to a notable improvement in their service life and operational safety.
Kou, Zhihai, Li, Xiangqiao, Wang, Xingbo
Numerical Simulation and Geometric Parameter Optimization of Solid Propellant Single-Screw Extrusion2026-99-2360To be published on 10/30/2026
For the single-screw extrusion process of solid propellant, the geometric optimization of the homogenization section faces a core problem: the high coupling between pressure establishment, material transport and energy consumption, and it is difficult to achieve a balance between different performance indicators by traditional empirical methods. Therefore, a numerical optimization framework combining CFD simulation and genetic algorithm is constructed to systematically explore the optimal screw geometric configuration. Propellant slurries are regarded as non-Newtonian fluids and are described by the Arrhenius temperature-dependent Bird-Carreau model, on which the flow field, pressure field and temperature field are solved. The key geometric parameters such as outlet core diameter, pitch, front and rear wedge angle, and thread width are selected as the optimization variables, and the ratio of pump power to shaft power is used as the objective function of energy efficiency to measure the degree of mechanical energy conversion into effective pressure work, and thermal safety constraints are introduced to control the upper limit of propellant temperature. The optimization results show that compared with the initial configuration, the volume flow rate is increased by 123% and the energy efficiency is only slightly reduced under the premise of maintaining a stable pressure drop. The flow field analysis shows that the optimized structure enhances the resistance-led conveying capacity and effectively inhibits the backflow phenomenon. Further analysis shows that the design with a larger pitch and narrower thread can reduce energy consumption while increasing the output, but its pressure accumulation ability is significantly weakened, revealing the inherent trade-off between screw geometry and pressure generation, conveying efficiency and energy consumption. The resulting optimized configuration achieves a good balance between multiple properties, which provides a theoretical reference for the continuous extrusion process of high-performance solid propellants.
Tang, Zhuang, Jiang, Ye, Mei, Mei, Wu, Wei-Tao
Permutation Test as a Novel Robust Statistical Approach for Gauging a Change in the Rate of Stochastic Preignition03-19-06-002710/23/2026
Multiple statistical methods were evaluated to determine the most suitable approach to gauge whether a gasoline deposit control additive (DCA) causes a statistically significant increase in rate of stochastic preignition (SPI) in a direct injection, turbocharged, spark ignition (SI) engine. SPI is an abnormal combustion phenomenon observed at highly boosted conditions in turbocharged SI engines. The high in-cylinder pressures observed during an SPI event have the potential to cause physical damage to the engine. The SPI rate is a function of engine operating conditions as well as fuel and oil properties. DCAs are commonly used in commercial gasoline at very low concentrations (20–200 ppm m/m) to prevent the buildup of carbon deposits in the combustion chambers and fuel systems. Since the effect of DCAs on SPI rate can be subtle and the data inherently stochastic, a controlled engine test methodology with robust statistical analysis is required to conclusively determine whether a gasoline detergent increases or mitigates the rate of SPI occurrence. Therefore, the TOP TIER™ Standardized Dynamometer Test Method to Evaluate Additized Detergent Gasoline for Stochastic Pre-Ignition (hereafter referred to as the TOP TIER™ Additive SPI Test Protocol) described herein is designed to gauge whether a gasoline additive causes a statistically significant change in the SPI rate at a controlled operating condition as compared to unadditized gasoline. This study focuses on the statistical analysis portion of the test protocol. Multiple statistical approaches were evaluated using data from the TOP TIER™ Additive SPI Test Protocol to determine the most appropriate and robust approach for detecting a statistically significant difference in SPI rates. The analysis included the two-sample (unpaired) t-test, linear mixed-effects models (LMMs), the Mann–Whitney U test, and the permutation test. The results indicated a combination of permutation paired with Wilkinson’s method as the most suitable approach.
Gopujkar, Siddharth, Davis, Richard, Zhang, Kui, Reilly, Veronica, Studzinski, William
Methods and Devices for Measuring the Waveform of Large Friction Forces and Energy between the Bodies and Needles of Injector Nozzles of Marine Piston Combustion Engines04-19-03-001410/21/2026
In marine combustion engines, it is important to minimize fuel consumption and reduce toxic emissions. One method to achieve this is minimizing friction losses in the injection subsystem, which is why measuring them is necessary. Some friction force values in precision pairs are so high that they require specialized methods and measurement stations. This article presents innovative methods and devices for measuring high friction and high power forces between the body and the needle of injector nozzles in the presence of a lubricant. The scientific method consists of increasing the load applied to the needle pin located in the nozzle body until it is completely ejected from the body. The devices that determine the course and maximum value of the friction force utilize test benches for dynamic tensile strength testing samples, employing specially designed and manufactured holders. When the fastening of the pin holder proved insufficient due to slippage, a semicircular groove was made around the circumferential needle pin. Round balls were inserted into the pin’s innovative mounting screw holes, recessed into the circumferential groove by about half their diameter, which is an important contribution by the authors. The maximum friction force was determined from the recorded signal, depending on the displacement or time waveform. The friction force depends on the needle’s position relative to the nozzle body; therefore, it is recommended to take measurements in at least four planes and compute the average. Different friction force values are caused by errors in the roundness and concentricity of the injector nozzle body guide part relative to the needle, as well as deposit formation. This article presents the influence of the state of the friction surfaces, as determined by modern geometric measurements of the cooperating elements, including computed tomography scans and silicone casts, on the maximum friction force value and modeling.
Monieta, Jan, Komorowski, Adam
Properties of Oxymethylene Ethers with Different Terminal Groups: A Mini-Review04-19-03-001610/21/2026
Methyl-terminated oxymethylene ethers (OMEs) have garnered significant attention as promising low-carbon alternatives to conventional petroleum-based diesel fuels. Nevertheless, their physicochemical properties frequently fail to satisfy the stringent specifications of current diesel fuel standards, which impedes their direct adoption in modern compression ignition engines. Structural modification of OMEs, particularly through the variation of terminal alkyl moieties, provides a viable strategy for tuning their properties to meet the required performance criteria. This review consolidates and critically evaluates the available literature on the physicochemical and performance characteristics of OMEs featuring diverse molecular architectures. In addition, it delineates existing knowledge gaps and identifies key areas warranting more in-depth future research. The number of published studies in this area is extremely limited, as research in this field is still essentially at an early stage; therefore, the present review has been classified as a mini-review.
Cherepanova, Anna D., Ukhanov, Denis A., Khrapov, Alexander G., Dement’ev, Konstantin I.
Fine-tuned Large Language Model Enhanced Nonlinear Model Predictive Control for Spacecraft Attitude Stabilization2026-99-296610/19/2026
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Guo, Zili, Gao, Sihong, Liu, Yuhan, Wang, Pengyu, Guo, Yanning
The Emerging Strategies of Energy Management System for Fuel Cell Hybrid Aircraft in the Low-Altitude Economy2026-99-291910/19/2026
The low-altitude economy has been established as a strategic emerging industry, driving the development of various new aircraft types, including electric vertical take-off and landing (eVTOL) vehicles and industrial unmanned aerial vehicles (UAVs). In this development, proton exchange membrane fuel cell (PEMFC)/lithium-battery hybrid propulsion systems face challenges in balancing fuel economy, stack durability, and implementability under stochastic aerodynamic loads. Six energy management strategies (EMS) are systematically evaluated in this study, namely Thermostat, Fuzzy Logic, State Machine (SM-EMS), Power Following (PF-EMS), Dynamic Programming (DP-EMS), and a proposed load-disturbance-based method (LD-EMS). These strategies are tested on three distinct platforms, including a 2 kW fully simulated system, a 2 kW hardware-based setup incorporating a real PEMFC stack and Li-FePO4 battery, and a 30 kW hybrid testbed. Experiments were conducted under synthetic stochastic load profiles representative of gust-induced power transients. The results indicate that LD-EMS achieves a total equivalent hydrogen consumption of 2.71 g (close to the DP-EMS optimum of 2.64 g and 19 % lower than SM-EMS) while reducing fuel cell state-of-health degradation to only 0.0005 % over the test cycle, which is an order of magnitude better than PF-EMS and SM-EMS. On the 30 kW platform under two distinct challenging profiles, LD-EMS maintains fuel cell efficiency above 90 %, keeps the stack operating in high-efficiency zone, and limits power switching events to 97 and 212 respectively over test cycles, demonstrating robust scalability and transient suppression capability without requiring prior mission knowledge. A five-dimensional evaluation framework is introduced to compare the six EMS. In accordance with this framework, platform-specific selection guidelines are established. Thermostat EMS is recommended for small industrial UAVs where hardware simplicity dominates; LD-EMS is the optimal choice for passenger eVTOL under unpredictable gust conditions; and SM-EMS is preferred for commuter/regional aircraft operating on fixed, repetitive routes.
Gao, Zibo, Chigan, Dongdong, Xiao, Yizhuo, Li, Yuansheng, Ji, Guoming, Han, Qing, Li, Zhi-peng
Coking Inhibition Characteristics of Dimethyl Disulfide during Supercritical Pyrolysis of n-Decane2026-99-299310/19/2026
Inhibition of coking from pyrolysis of hydrocarbon fuel is critical for ensuring the safe operation of high-speed aircraft. In this work, the inhibitory effects of dimethyl disulfide (DMDS) on coke during the supercritical pyrolysis of n-decane were investigated. Experiments using an electrically heated micro-reactor tube were conducted to study the influences of presulfidation and cofeeding methods with varying DMDS concentrations. The pyrolysis products were analyzed via gas chromatography, while pressure drop and coke mass were measured. The composition and morphology of coke were further characterized by energy-dispersive spectroscopy and scanning electron microscopy. The results show that the influence of DMDS on coke formation depends on its application method and concentration. At a DMDS concentration of 500 ppm, the coke inhibition rate reached 85.5% with presulfidation and 81.7% with cofeeding. However, with increasing DMDS concentration beyond 500 ppm, the amount of coke formation increases. Coke formation during supercritical pyrolysis of n-decane primarily involves metal-catalyzed coking and bulk-phase coking processes. The H2S and HS radicals generated from pyrolysis of DMDS react with transition metals such as Fe and Ni, thereby inhibiting the formation of metal-catalyzed filamentous coke. The presulfidation process forms a sulfide layer earlier than the cofeeding process, more effectively suppressing the generation of filamentous coke. However, excessively high DMDS concentrations can lead to its decomposition into sulfur-containing radicals such as thiol radicals (CH3S·), which incorporate into the coke matrix, enhance its reactivity, and promote coke formation. This work offers valuable insights for the application of DMDS as a coke inhibitor in endothermic hydrocarbon fuels.
Liao, Yan, Yao, Yixuan, Yang, Can, Huang, Qin, Chen, Yu
Emergence and Regulation of Scale-Free Correlation in UAV Swarm under Communication Energy Constraints2026-99-298310/19/2026
This paper studies how scale-free correlations, a key feature for efficient group response, emerge in collective motion under communication energy constraints. A two-dimensional Boids model integrated with a point-to-point wireless communication energy consumption model is used. The model dynamically determines, based on a limited communication power budget, an individual’s interactive neighbors, where neighbors are selected based on two different mechanisms: distance-based and probability-based, until the total communication cost reaches the budget. Simulations of flock sizes ranging from 30 to 230 individuals confirm that scale-free correlation persists, even under strict power constraints, which is shown by a correlation length ξ proportional to the flock’s linear size L. Notably, the ratio ξ/L, which reflects the robustness of collective correlation, displays a non-monotonic dependence on the available communication power. Initially, increasing power enhances ξ/L by expanding effective interaction ranges and improving information transmission. However, beyond a threshold, further power increase causes a slow drop in ξ/L, likely due to signal interference from excessively many or distant connections. This finding demonstrates that communication power is a critical, tunable engineering parameter regulating collective coordination, analogous to interaction range or neighbor number in biological models. The results imply that for engineered swarms, maximizing communication resources is not always beneficial; instead, an optimal power allocation exists to maximize coordination performance, balancing connectivity with efficient, localized interactions.
Zhao, Shiping, Gan, Qingzhong, Liu, Jinglei, Liu, Zhihao, Zhang, Liang
An Electromagnetic-Thermal-Mechanical Coupling Model of the Three-Coil Wear Debris Sensors for Wide-Temperature and Kinematic Analysis2026-99-298510/19/2026
Real-time monitoring of metal wear debris in lubricating oil is crucial for accurately assessing aerospace equipment health and preventing catastrophic mechanical failures. Although three-coil differential inductive sensors are widely used due to their high sensitivity and robust structure, their detection performance inevitably degrades under the influence of multi-physics coupling effects inherent in complex industrial environments. Existing analytical models were primarily limited to single electromagnetic field simulations, failing to capture the intricate electromagnetic-thermal-mechanical interactions, which reduced analytical accuracy and hindered the optimization of sensor designs for extreme conditions. To overcome these challenges, this study established a comprehensive parametric simulation model to conduct a rigorous electromagnetic-thermal-mechanical coupled analysis of the differential sensor. Specifically, the research analyzed the underlying mechanisms by which wide temperature variations from -55 °C to 200 °C and specific debris kinematics exert varying degrees of influence on the induced voltage. Quantitative results indicated that both the isolated thermal and mechanical fields altered the voltage by a maximum of 0.649%, demonstrating that the sensor maintains a relatively stable response across extreme thermal gradients. Furthermore, the analysis revealed that increased debris velocity decreased the induced voltage amplitude due to the intensified motion-induced eddy current effects. Notably, in complex multiple debris scenarios, the strong dominant signals generated by ferromagnetic wear debris severely masked the weaker responses from non-ferromagnetic ones, indicating a substantial missed detection risk under mixed contamination conditions. Ultimately, this research successfully filled the critical simulation gap for evaluating these sensors under multi-physics coupling, providing robust theoretical guidance for their reliable deployment in complex industrial applications.
Shi, Xinfa, Duan, Chenhao, Zhen, Huanyi, Zhao, Yihe, Li, Min, Wang, Xiaozhang, Zhang, Qing, Li, Zhikang, Zhao, Libo
Rapid Trajectory Optimization for Mars Aerobraking Campaigns2026-99-294010/19/2026
Aerobraking is a key technology for reducing propellant consumption in deep space exploration missions. Targeting the Mars aerobraking trajectory optimization problem, this paper proposes a rapid trajectory optimization method based on a high-precision analytical approximate solution. First, a Mars aerobraking dynamics model is established. Based on the assumptions of a linear flight path angle and a linear altitude rate, a high-precision analytical approximate solution for Mars aerobraking trajectories is derived. Simulation results verify that the proposed analytical solution satisfies the accuracy requirements for Mars aerobraking trajectory optimization. Based on this analytical solution, the state transition function of the aerobraking trajectory optimization problem is reconstructed, and the Sequential Quadratic Programming (SQP) algorithm is employed for the optimization. Numerical simulation results demonstrate that the proposed method requires less than one minute to optimize an aerobraking campaign consisting of 80 atmospheric passes. Compared with traditional optimization methods, it exhibits significant advantages in computational efficiency when dealing with aerobraking trajectory optimization problems characterized by long durations and multiple velocity pulses.
Ding, Yuancheng, Dong, Jie, Cui, Hutao, Chen, Zheng
Task Allocation and Trajectory Optimization for Mother-Daughter Satellite Clusters Observing Non-Cooperative Constellations via Improved Genetic Algorithm2026-99-291710/19/2026
Over the past decade, the rapid deployment of Low Earth Orbit (LEO) mega-constellations has significantly reshaped the spatial distribution of the near-Earth environment and increased orbital density to historically high levels. While popularizing space access, the accumulation of defunct or non-cooperative satellites raises severe concerns regarding space sustainability and the Kessler syndrome. Consequently, the ability to conduct active, multi-target close-proximity inspection is becoming an essential capability for Space Situational Awareness (SSA). Traditional monolithic servicing strategies rely on sequential point-to-point orbital transfers, which have to face heavy computation cost and restrictive fuel constraints when targeting multi-planar distributed networks requiring continuous out-of-plane maneuvers and phasing adjustments. In order to overcome these limitations, the paper proposes a coordinated mother-daughter satellite cluster architecture. A primary mother satellite serves as a deployment hub, while a swarm of highly maneuverable daughter satellites executes sequential "Observe-and-Return" missions, gathering high-fidelity SSA data. Assigning these multi-target inspection missions to a limited fleet creates an NP-hard combinatorial challenge, further compounded by strictly non-overlapping operational time windows and rigid propellant boundaries. To navigate this high-dimensional search space, the study introduces an improved Genetic Algorithm (GA) featuring a dynamic chronological decoding mechanism. Furthermore, to eliminate secular positional drifts during orbital integration, a high-fidelity five-impulse maneuver sequence is established, embedding an autonomous Lambert-based positional compensation mechanism. Simulation results indicate that the proposed method yields scalable, fuel-feasible, and load-balanced kinematic baselines for autonomous target characterization across large-scale constellations. Additionally, an event-triggered dynamic re-planning mechanism is utilized to robustly adapt to uncooperative evasive maneuvers in highly dynamic real-world space scenarios.
Sheng, Beining, Tian, Yang, Li, Tieying, Shan, Yiming
Closed-Loop Steam-Injected SOFC-GT Propulsion System with Thrust Compensation for High-Altitude Hydrogen UAVs2026-99-292710/19/2026
To address the requirements of high thermal efficiency and strict thermal control for high altitude long endurance unmanned aerial vehicles, as well as the problems of large additional water load and difficult high altitude condensation in traditional steam injected cycle aero engines, this paper proposes a closed loop steam injected cycle liquid hydrogen solid oxide fuel cell and gas turbine hybrid power system, which uses the cryogenic energy of liquid hydrogen fuel and external high altitude ram air to realize the condensation, collection and reuse of water vapor. This paper establishes a coupled thermodynamic and aerodynamic model, evaluates the benefits of the steam injected cycle at the design point, and analyzes the thermodynamic and aerodynamic characteristics of the system under off design conditions. The results show that the closed loop steam injected cycle effectively improves the work capacity of the turbine and the power generation efficiency of the system. At the design point, the rated net output power and power generation efficiency of the system reach one thousand two hundred and fifteen point zero kilowatts and sixty-six point two eight percent respectively. In addition, the system recovers kinetic energy by using the Meredith effect, which greatly offsets the aerodynamic drag caused by the introduction of ram air. Even when the flight speed exceeds Mach number zero point six four, the system can completely offset the aerodynamic drag and even generate additional thrust. Power margin analysis proves that the system still has sufficient power reserve to complete the flight mission under cruise conditions. This study provides a theoretical basis for the power and thermal control design of high altitude long endurance hydrogen powered unmanned aerial vehicles.
Kang, Qiming, Shen, Yiling, Li, Chengjie, Qin, Jiang, Ji, Yongbin, Jiang, Junwen
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
Performance Study of an Onboard Power Generation System with Liquid Hydrogen Intercooling and Recuperation Based on Aviation Fuel Cells2026-99-292910/19/2026
Electrification in aviation imposes higher requirements for the power density and operational efficiency of onboard power systems. Conventional auxiliary power units currently face bottlenecks in both efficiency and emissions. Hybrid power systems consisting of proton exchange membrane fuel cells and gas turbines are considered a promising solution because they enable cascaded energy utilization. Integrating such hybrid systems with the main turboshaft engine represents an important technical path for improving performance. However, extracting interstage bleed air from the main engine compressor leads to propulsion power loss, and the performance of the fuel cell is significantly influenced by temperature and pressure. Therefore, quantifying the trade-off between the cost of bleed air and the gain in power generation is essential for verifying the feasibility of this technology. This paper proposes a thermodynamic model coupling a main turboshaft engine with a fuel cell and gas turbine subsystem. In this model, a novel thermal management strategy employs liquid hydrogen to cool interstage bleed air. Prior to entering the cathode, the bleed air undergoes cooling via heat exchange, while the high-temperature turbine exhaust stream concurrently preheats the hydrogen before it reaches the anode. Bleed air losses are quantified through a segmented compression work calculation, and the influence of bleed air pressure ratio, current density, and fuel utilization on overall system performance is systematically examined. System net benefit is defined as the net generated power minus the associated propulsion power penalty. The results indicate that, with suitable parameter coordination, a positive net benefit can be realized. Under typical operating conditions, the system attains a net benefit of thirty-two point two kilowatts. The proposed coupling architecture offers a theoretical reference for the design of hydrogen-based hybrid propulsion systems in aviation.
Jiang, Junwen, Li, Chenjie, Shen, Yiling, Qin, Jiang, Ji, Yongbin, Kang, Qiming, Jiang, Xinyang
Detecting Fuel Adulteration in Otto-Cycle Vehicles Using On-Board Diagnostics Data and Machine Learning–Based Anomaly Detection04-19-03-001510/15/2026
Fuel adulteration increases operating costs, reduces vehicle efficiency, and contributes to air pollution. Fuel-quality verification typically requires laboratory infrastructure or dedicated sensors that are not available to most end users. In our previous work, we demonstrated that a software-only approach based on standard on-board diagnostics (OBD) signals and supervised machine learning can detect water adulteration in hydrated ethanol under real-world driving conditions with high accuracy. However, supervised classifiers remain challenging because fuel-trim dynamics vary across vehicles due to powertrain calibration, component aging, and operating environments, which can limit model generalization. This work addresses this limitation by introducing a detection framework that learns a vehicle-specific baseline of normal operation using gradient boosting regression (GBR) and flags anomalous events through residual-based cumulative sum (CUSUM) monitoring. The baseline model is trained using compliant-fuel data, and the CUSUM decision threshold is calibrated from temporally ordered normal-operation data using an expanding-window procedure with an initial warm-up segment. Across two vehicles, the proposed framework achieved recall values of 99.77% and 84.38%, with F1 scores of 99.88% and 91.53%, respectively, while maintaining zero false positives under compliant-fuel operation.
Marchezan, André Ricardo, Giesbrecht, Mateus
Development and Validation of Quasi-Dimensional Multi-Zone Combustion Model for Homogeneous Reactivity-Controlled Compression Ignition with Renewable Fuels—Part 2: Complete Model and Validation03-19-05-002410/14/2026
As a part of the project, the homogeneous reactivity-controlled compression ignition (hRCCI) concept is being investigated along with the development of 0D/1D combustion simulation models. The proposed concept employs early direct injection of octanol as the high-reactivity fuel in combination with port fuel injection of ethanol as the low-reactivity fuel. In the previous parts of the publication, testing results and the in-cylinder fuel and temperature distribution predictions were studied. Low-temperature combustion (LTC) concepts such as hRCCI are strongly governed by autoignition chemistry of the fuels and oxidizer, making the explicit consideration of chemical kinetics essential for predictive simulations. In addition, the hRCCI combustion process exhibits high sensitivity to a wide range of control parameters, including intake temperature, intake pressure, excess air ratio, premixed fuel ratio, and direct injection parameters, posing further challenges to model robustness. To address these challenges, a predictive and robust quasi-dimensional multi-zone combustion model for LTC engines is developed. The model couples a 0D/1D flow framework implemented in GT-POWER with detailed chemical kinetics solved using a Python–Cantera interface for user-defined combustion modeling. The combustion framework incorporates dedicated sub-models to account for fuel evaporation, interzonal heat transfer, wall heat transfer, spatial distribution of directly injected octanol, and temperature stratification across the zones. The model’s predictive capability is validated against experimental data from a single-cylinder research engine under variations in intake pressure, intake temperature, premixed ratio, and the start of direct octanol injection. The simulation results show strong agreement with experimental measurements, demonstrating the robustness and predictive accuracy of the developed modeling approach. The proposed simulation framework provides a valuable tool for the future development and optimization of low-temperature combustion engine concepts aimed at improving efficiency and reducing emissions.
Sundaram, Pravin Kumar, Grundl, Larissa Michaela, Trapp, Christian Thorsten, Tinschmann, Georg
Development and Validation of Quasi-Dimensional Multi-Zone Combustion Model for Homogeneous Reactivity-Controlled Compression Ignition with Renewable Fuels—Part 1: Fuel and Temperature Stratification Prediction03-19-05-002310/9/2026
As part of the dtec.bw MORE project, serial hybrid powertrains featuring alternative combustion regimes, specifically homogeneous reactivity-controlled compression ignition (hRCCI), are under investigation to maximize thermal efficiency while minimizing NOx and soot emissions. The proposed hRCCI concept utilizes dual-fuel stratification, employing early direct injection (DI) of octanol (high-reactivity fuel) alongside port fuel injection (PFI) of ethanol (low-reactivity fuel). While 0D/1D engine modeling is essential for developing predictive powertrain simulation frameworks, conventional models often lack the robustness required to capture the complexities of low-temperature combustion (LTC). This study addresses this limitation by developing a multi-zone “onion skin” quasi-dimensional model. Since for LTC, ignition and heat release rates are highly sensitive to thermal and chemical stratification, capturing these gradients is critical. 3D computational fluid dynamics (CFD) simulations are capable of capturing thermal and chemical stratifications to a high degree of accuracy, whereas 0D simulation models, in general, do not consider them. The primary contribution of this work is the translation of high-fidelity 3D CFD data into a computationally efficient quasi-dimensional environment. A simplified 3D CFD architecture was utilized to map the effects of various operating parameters on mixture distribution. Using these results, a regression learning model was trained to predict octanol and temperature stratification within the combustion chamber. Validation against simulation data demonstrates that this coupled machine learning and multi-zone approach provides a robust, predictive tool for evaluating advanced LTC concepts within larger system-level simulations.
Sundaram, Pravin Kumar, Grundl, Larissa Michaela, Trapp, Christian Thorsten, Tinschmann, Georg
Latency-Aware Optimal Scheduling Scheme for Computational Offloading12-10-01-000210/9/2026
Proactive safety and vehicle automation typically requires high energy use from sensors and energy-intensive computing from sensor data processing. For high-quality, reliable perception and localization within a driving environment at the vehicle level, incoming data from multiple sensors need to be fused using advanced computational algorithms, which demand a high compute load. Alternatively, computational offloading of automated driving tasks shifts energy consumption from the vehicle to cloud infrastructure, where renewable energy sources, such as hydropower or solar power, can be utilized more efficiently. Herein, an optimal scheduling strategy for autonomous driving tasks via the cloud layer is formulated as a mixed-integer linear programming (MILP) problem and verified using measurement-informed task graphs. It is shown that cloud-based computational offloading enables energy-efficient operation while maintaining task deadlines to ensure the timely availability of perception and localization information, which is consistent with prior studies in the literature. Simulation results demonstrate that on average, 35.78% of the computational load was offloaded to the cloud, which can achieve significant energy savings for the onboard system. The compute operations achieved an average energy savings of 35.65%, while total system savings ranged from 26.16% to 30.67% under different cloud energy efficiency scenarios, highlighting the advantages of offloading compute-intensive tasks. The framework was further evaluated using multiple directed acyclic graph (DAG) configurations to assess its scalability and adaptability. Critical tasks, such as sensor fusion, were executed exclusively on the vehicle to ensure real-time responsiveness.
Sharma, Sachin, Meyer, Richard, Feinberg, Ben, Asher, Zachary
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.
Effects of Methane Addition to Diesel in Dual-Fuel Mode Combustion Utilizing the Advanced Fuel Ignition Delay Analyzer04-19-03-001310/8/2026
With the rising pressure of a global energy transition to cleaner energy systems, the transportation sector faces a challenge in maintaining its current structure and adapting to all the required changes. Dual-fuel technology emerges as a promising alternative to keep the viability of the sector while utilizing environmentally friendly fuels alongside traditional hydrocarbons, without deep structural changes in the current framework. This work investigates the impact of the use of methane gas coupled with diesel fuel, specifically focusing on its influence on the ignition delay time (IDT) in a dual-fuel combustion setting. The investigation employed the Advanced Fuel Ignition Delay Analyzer (AFIDA), a constant-volume combustion chamber capable of automatically measuring multiple samples in a single run. Methane gas was introduced into the chamber at molar concentrations of 1%, 2%, and 3% and at initial pressures of 5 and 10 bar, with temperature values ranging from 653 to 723 K. With the same amount of diesel being injected for all experiments, it was possible to replace up to 40% of the total energy release with methane during the combustion process. Compared to pure diesel, the IDT values of the methane–diesel mixtures were only affected in low-temperature settings. At higher temperatures, the IDT values remained largely consistent with those of pure diesel, suggesting that higher substitution ratios of methane are feasible without compromising the ignition delay. This work also uncovered that the percentage of energy replaced by methane does not have a direct correlation with IDT or peak pressure values.
Pacheco Virginio, Thiago, Eraqi, Basem, Sakleshpur Nagaraja, Shashank, Sarathy, S. Mani
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
A Shared-Hardware Battery Management System for Solar-Assisted and Capacitive Balancing in Unmanned Surface Vehicles12-10-01-000110/7/2026
This article presents a hybrid battery management system for unmanned surface vehicles, integrating three operational modes: solar-to-cell balancing, capacitive balancing, and solar-to-pack charging—within a shared architecture. The system prioritizes solar-to-cell balancing when solar energy is available, capacitive balancing when charging without solar input, and solar-to-pack charging when cells are balanced. This approach eliminates additional hardware by utilizing a shared-hardware architecture. A 14.8 V battery pack composed of four 3.7 V Li-ion modules was simulated and prototyped to validate the system. Experimental and simulation results confirm improved cell balancing, reduced state-of-health deviation, and extended operational time, demonstrating superior performance, sustainability, and adaptability over conventional battery management system solutions for unmanned surface vehicles and similar platforms.
Blair, Raymond, Kyger, Kenton, Duan, Chen
Considerations for Hydrogen Fuel Cells in Airborne ApplicationsAIR7765A (Current)10/5/2026
The scope of this joint EUROCAE/SAE report is to compile the considerations relating to airborne application of hydrogen fuel cells. This document provides a comprehensive analysis of the use of hydrogen as a fuel by describing its existing applications and the experience gained by exploiting fuel cells in sectors other than aviation. The use of hydrogen fuel cells in aircraft can help in meeting aviation environmental targets (including noise pollution) and can be vital to achieving efficient electrically propelled air vehicles. The experience gained with mature fuel cells in terrestrial applications and the handling of other gases in aviation, as presented herein, will help in alleviating safety concerns and in demystifying the usage of hydrogen in aviation.
AE-7F Hydrogen and Fuel Cells
Thermoelectric Generators for Battery Charging: Waste Heat Utilization with Minimized Back Pressure13-07-02-000910/1/2026
Waste heat recovery has become a critical research area in the quest for improving automotive energy efficiency. Internal combustion engines lose a large amount of their energy as heat through exhaust gases. Thermoelectric generation technology presents a promising approach to capturing and converting this waste heat into useful electrical energy. In this work, a theoretical study on the application of thermoelectric generators (TEGs) for battery charging by converting waste heat from internal combustion engine exhaust into usable electrical energy is proposed. A prototype system incorporating TEG modules was designed focusing on the minimization of back pressure; flow of exhaust gas is ensured through a circular internal cross-section. Thermal simulations were performed using Ansys Workbench, and computational fluid dynamics (CFD) analysis was conducted to quantify the back pressure. Two heat exchanger materials, aluminum and copper alloys, were evaluated for their heat transfer performance. The results indicate that copper achieves superior heat transfer, with hot-side temperatures approximately 8.6% to 23.9% higher than aluminum. However, aluminum remains a viable alternative due to its lightweight and cost-effectiveness. With the cold side being maintained at 91°C to simulate realistic engine coolant conditions, the experiment shows that a series-parallel configuration of six TEG modules (three in series × two in parallel) can effectively generate the necessary voltage (13–15 V) and current (3.5–7 A) to charge a 12-V automotive battery. CFD analysis confirmed that the circular internal geometry produces low back pressure, with pressure drops of 28 Pa, 63 Pa, and 168 Pa for inlet velocities of 25 m/s, 40 m/s, and 70 m/s, respectively. This research underscores the potential of TEG-based battery charging systems in enhancing energy efficiency, though further development is required for real-world automotive integration. Future work could focus on on-vehicle testing, optimizing thermoelectric materials, and integrating advanced cooling mechanisms and maximum power point tracking controllers to improve overall system viability.
Satheesh, Amal, Satheesh, Akul, Pillai, Ashwin S., Mahisankar, J.S., Sreejith, B.J.
Simulation of Liquefied Petroleum Gas Truck Accidents during Heatwave Periods Using the Areal Locations of Hazardous Atmospheres Program2026-01-507910/1/2026
In this study, the effects of heatwaves (HWs) on liquefied petroleum gas (LPG) leaks were analyzed using the Areal Locations of Hazardous Atmospheres (ALOHA) program. For this purpose, data from an accident at a gas station in the Eryaman District of Ankara in January 2024 were utilized. Approximately 40 m3 of LPG was released during the incident, but no explosion occurred. The accident was simulated using atmospheric data from the accident date in the ALOHA program. In the simulations, emissions of propane and butane—the primary components of LPG—were modeled separately. To simulate the LPG leak during a HW, a HW was first defined based on daily maximum temperature data. The threshold was set at the 90th percentile, and temperatures persisting for three or more consecutive days were classified as a HW. Using this definition, a four-day HW in Ankara in July 2024 was identified. The atmospheric conditions during this HW were input into the ALOHA program for simulation. The study compared the simulation results of the LPG leak in January with those during the HW period. The findings showed that the sub-explosion areas for propane and butane during the HW were 2% (95% CI: 0.91–1.15, p > 0.05) and 9% (95% CI: 0.84–1.42, p < 0.05) larger, respectively, than those during the accident in January. As a result, the study highlights the need for stricter safety measures during summer months when transporting explosive materials.
Öztürk, Yunus
Exhaust Emissions Tests of Small Gasoline Engines Used as Drives for Power Generators and Handheld Machinery in Real-Operating Conditions2026-01-508010/1/2026
The paper presents the results of investigations on the exhaust emissions carried out under real-world operating conditions of gasoline engines used in lawnmowers and power generators. During the operation of these engines, the authors measured the emissions of the following exhaust gaseous components: CO, HC, NOx, and CO2. For the measurements, the authors used Axion R/S+, a PEMS (Portable Exhaust Emission System) analyzer. The presented method is a new approach to exhaust emissions measurements performed on small engines. The emission coefficient, as a related value of the emission of harmful compounds and CO2, was proposed. Additionally, some remarks related to the measurement method were made. The paper presents the modal analysis of the investigations of the exhaust emissions from engines and the total mass of gaseous compounds. Moreover, the obtained results of the exhaust emissions from the power generator engine were compared with the applicable emission standards, and the real emissions of CO and HC+NOx were, respectively, about 10% and 38% higher than Stage II standards. Based on the investigation results, the authors considered the possibilities of using the said measurement method in real-world operating conditions, applying the PEMS equipment for small gasoline engines.
Lijewski, Piotr, Markiewicz, Filip, Fuć, Paweł, Dobrzyński, Michał, Wiśniewski, Sławomir
Response Surface Optimization of Alkylphenolate Additive AKI-152 for High-Performance Motor Oils in Oil and Gas Applications04-19-03-00129/22/2026
The behavior of detergent–dispersant additives in lubricating oils depends upon their chemical composition and synthesis, particularly for lubricants used in rotary equipment under harsh conditions, in the upstream and downstream oil and gas industries. Alkylphenolate-based additives are extensively used, among others, due to their high alkalinity and good dispersion stability. However, their performance is extremely sensitive to synthesis parameters, making experimental optimization time-consuming and resource-intensive. In this study, an alkylphenolate-based additive (AKI-152) was synthesized and optimized systematically via a response surface methodology (RSM), derived from a central composite design (CCD). The influence of three important process variables, namely the alkylphenol/amino mass ratio, reaction temperature, and Ca(OH)2/CO2 mass ratio, was assessed with respect to the total base number (TBN), kinematic viscosity, and corrosivity of the final product. A quadratic regression model was developed and validated, showing good agreement between predicted and experimental results. Analysis of variance (ANOVA) indicated that the alkylphenol/amino ratio and Ca(OH)2/CO2 ratio exert the strongest influence on TBN, while temperature also contributes significantly within the investigated operating range. Numerical optimization identified a stable optimum region corresponding to TBN values of approximately 160 mgKOH/g, viscosity values close to 54 mm2/s, and corrosivity values below 0.76 g/m2 under the selected optimization criteria. No separate experimental run was performed to verify the selected numerical optimum, as the optimization was conducted within the experimentally investigated CCD space using the developed and statistically evaluated response surface models. These results demonstrate that the applied modeling approach can be effectively used to define suitable synthesis conditions for high-performance lubricant additives.
Gasimov, Rahib, Naghiyeva, Elmira, Sujayev, Afsun, Gadirov, Ali, Nasibova, Nigar
Parametric Screening of Hybrid Powertrain Architectures for High-Energy Laser Vehicles: Application to Foxhound and Boxer2026-01-75529/22/2026
The US Army and several NATO allies have committed funds for directed energy weapons including high energy lasers (HEL), which require substantial electrical power. Silent Mobility and Silent Watch requirements mandate hybridization, which also provides the electrical capacity needed for a HEL. This paper introduces a HEL framework of classes A-E based on target types and fluence physics. It estimates installed HEL mass and power demand by class, and applies rapid powertrain screening to hypothetical hybrid variants of the UK vehicles Foxhound and Boxer. Results show that HELs up to Class B (60 kW) and D (300 kW) laser output can be supported with minimal powertrain modifications by Foxhound and Boxer respectively, and upgrades to support Class C (150 kW) and E (500 kW) are containable within the payload of each vehicle. A rapid methodology is presented to determine what powertrain architecture is needed to support a given HEL.
Salis, Rupert Tull
Physics-Constrained Procedural Generation of Synthetic Environments for the Robust Validation of Autonomous Maneuver and Logistics2026-01-75499/22/2026
The validation of Autonomous Ground Vehicles (AGVs) and intelligent logistics planners is frequently compromised by the ”Sim-to-Real” gap, where simulation environments fail to replicate the physical friction of operational deployment. Ideally, valid test cases must enforce strict mobility constraints and impose realistic sustainment penalties; however, many current generation tools rely on idealized terrain interactions and infinite-resource assumptions. We present a real-time procedural framework designed to generate high-friction validation environments that stress-test the robustness of the System Under Test (SUT). The architecture integrates gradient-based terrain analysis with a stochastic contested logistics model. It ingests synthetic heightmaps to precompute mobility corridors, ensuring that every generated evaluation episode adheres to vehicle-specific traversability limits. Simultaneously, a logistics kernel enforces fuel consumption scaled by terrain gradients and models supply chain interdiction as a parameterized Bernoulli process. We validate this framework through a ”Digital Twin” methodology, demonstrating that terrain-aware generation eliminates invalid initialization states (0% mobility violations) while the logistics model induces operationally relevant failure modes in the SUT. This unclassified, open-architecture approach supports DoD Verification, Validation, and Accreditation (VV&A) requirements by providing deterministic, reproducible edge cases for autonomous system evaluation.
Soykan, Bulent, Rabadi, Ghaith, Bochenek, Grace, Paul, Victor J.
Atomistic Molecular Dynamics Study of Linear and Branched Imidazole-Functionalized Polymers2026-01-75489/22/2026
We present atomistic molecular dynamics simulations of linear and branched fluorinated polymer chains, with and without imidazole functionalization, designed as a model for solvent-free proton-conducting membranes for high-temperature fuel cell applications. Simulations conducted over a temperature range of 300 to 550 K, and diffusion-based relaxation times reveal that glass transition temperatures depend on polymer architecture: the branched and functionalized systems exhibit transitions near 400 K compared to 500 K for the linear chain. Fluorine-fluorine radial distribution functions demonstrate that branching disrupts local packing order, while imidazole substitution creates specific intra-chain interactions. Radius-of-gyration distributions reveal that branching significantly increases chain extension and creates multiple conformational families, whereas imidazole groups stabilize compact conformations at low temperatures that transition to more diverse states upon heating. These findings provide molecular-scale insight into how polymer architecture controls thermal transitions and structural organization in model high-temperature polymer electrolyte membranes.
Ganta, Sujith, Alim, Twaha, Rakesh, Leela, Mueller, Anja, Mellinger, Axel, Burye, Theodore, Sebastian, Talia
Time-Dependent Power Flow Modeling for Non-Passive Loads in Battery Electric Propulsion Architectures2026-01-75639/22/2026
Traditional Linear Circuit Analysis (LCA) relies on steady-state voltage assumptions that are fundamentally incompatible with battery-exclusive propulsion architecture. Whilst LCA remains valid for hybrid systems, where an auxiliary source actively regulates the State-of-Charge (SOC), it fails when analyzing non-passive, constant-power loads. In pure electric architecture, the time-dependent decay of the discharge voltage forces a continuous, non-linear increase in current to satisfy mechanical power demands. A time-dependent power flow methodology is introduced to resolve this theoretical divergence. Using the conservation of energy operating explicitly within the power domain, the time-dependent coupling of current and voltage can be modeled. This approach supersedes steady-state approximations for higher fidelity predictions for component efficiency, system heat generation, and battery capacity requirements for pure electric propulsion systems. Citation: N. Ingarra, K. J. Kobus, J. G. Kobus “TIME-DEPENDENT POWER FLOW MODELING FOR NONPASSIVE LOADS IN BATTERY ELECTRIC PROPULSION ARCHITECTURES” In Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium (GVSETS), NDIA, Novi, MI, Aug. 11-13, 2026.
Ingarra, Nicholas A., Kobus, Krzysztof (Chris) J., Kobus, Jadon G.
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
An Assessment of Biomanufacturing in Forward Deployed Locations2026-01-75579/22/2026
Biomanufacturing uses microorganisms to produce chemicals or materials of interest, much like a brewery uses fermentation by yeast to produce the alcohol in beer. Biomanufacturing relies upon synthetic biology to reprogram yeast or other microorganisms to produce something of greater value, such as fuel, food, or pharmaceuticals. Industrial biomanufacturing has made significant advances and the products it can deliver include reactive coatings and textiles, sensors, optical materials that can bend light, and new therapeutics such as antimicrobials and vaccines. The convergence of synthetic biology, robotics, and artificial intelligence is opening the way to produce materials never before possible in the commercial market. These same technologies create the opportunity for the miniaturization of this technology to fit into ever more compact spaces, bringing forward deployment of these mini-factories closer and closer to the point of need.
Ahern, Brooke, Crumbley, Annie, Walker, Anne, Grodecki, Joseph
Exploring the Benefits of Multiple Injections in a Premixed Charge Compression-Ignition Engine Operated with Modified Injector Orientation and Diesel–Gasoline Blends03-19-05-00259/22/2026
The current study examines the combined effects of injection strategy, injector configuration, and fuel blending on the combustion performance and emission behavior of a light-duty compression-ignition (CI) engine operated in premixed charge compression-ignition (PCCI) combustion mode. Experiments were conducted in PCCI combustion mode using a diesel–gasoline blend (D80G20, 80% diesel and 20% gasoline by volume). A modified injector configuration, with a split-injection scheme comprising pilot and main injection events, was implemented to enhance mixture preparation and control combustion characteristics. The baseline configuration utilized PCCI mode with diesel (D100) and an inclined injector orientation. The results indicate that blending gasoline into diesel prolongs ignition delay and facilitates charge premixing, hence improving the stability of the PCCI combustion regime. Using a vertically oriented injector with a symmetric spray pattern significantly improves air–fuel mixing, and split-pulse injection enables more accurate control of combustion phasing. Among the tested strategies, the D80G20 blend, combined with a vertical injector and optimized split injection, achieved the highest brake thermal efficiency at 60% load, improving by 10.1% over the baseline case. In addition, unburned hydrocarbon (HC) and carbon monoxide (CO) emissions were significantly reduced by 54.1% and 49.4%, respectively. Additionally, the load extension was increased to 77%, which is limited to 60% of the engine-rated load in PCCI with diesel fuel. The current integrated approach provides a viable pathway to implement the PCCI mode to improve engine thermal efficiency and reduce pollutant emissions without significant hardware modifications, thereby supporting the transition to cleaner combustion technologies.
Ranjan, Ashish Pratap, Krishnasamy, Anand
Experimental Comparison Between Real and Simulated Battery Pack Efficiency in Light Quadricycles Using a Custom Inertia Dynamometer2026-24-00089/21/2026
This study compares the energy efficiency of a real battery pack and a simulated battery pack using a hardware-in-the-loop battery emulator, through experimental testing on a dedicated inertia dynamometer for light quadricycles. The investigated LiFePo4 battery pack has a nominal voltage of 48 V and a nominal capacity of 100 Ah. Initial characterization identified a reduced State of Health based on capacity (SOHC), with a measured usable capacity of 48 Ah (from the nominal 100 Ah) and a corresponding reduction in charge acceptance capability. The emulator was configured to replicate the degraded battery characteristics, including the open-circuit voltage (OCV)-SOC relationship, internal resistance, and current limitations, enabling a direct comparison between simulated and experimental dynamic behavior. The experimental setup was designed to overcome the limitations of conventional chassis dynamometers for low-mass, independent four-wheel-drive quadricycles operating without mechanical friction braking systems. Multiple driving cycles were reproduced using a PLC-based closed-loop control system, with data acquisition performed via CAN communication. The comparative analysis highlights significant differences during regenerative braking events. While the emulator accurately reproduces baseline electrical behavior under mild operating conditions, the aged battery exhibits strong limitations during both high-power acceleration and severe deceleration phases. In particular, increased internal resistance and transient electrochemical polarization lead to premature saturation of charge acceptance, resulting in rejection of high-frequency current transients. Consequently, the experimentally observed energy recovery is significantly lower than the theoretical values predicted by the emulator. In addition, due to the absence of mechanical braking, the reduced regenerative capability directly leads to speed tracking deviations, as the required braking torque cannot be fully achieved. These results identify battery degradation as a key physical constraint affecting both energy efficiency and dynamic braking performance, highlighting the importance of improved electro-thermal and aging-aware model calibration for realistic system-level simulations.
Sementa, Paolo, Vaglieco, Bianca Maria, Altieri, Nunzio
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
Analysis of Full Torque Determination in a Diesel Engine Operating in Dual Fuel mode with Hydrogen and Diesel2026-24-00149/21/2026
A 15kW diesel engine is modified in the laboratory to operate in dual fuel combustion mode. The engine is a three-cylinder, displacement of 1 Liter, originally fueled with diesel in its baseline configuration. The engine is modified by installing three PFI injectors, positioned toward the intake valves within the intake manifold. Hydrogen injection is synchronized with valve opening during the engine cycle using controlled delay units. The standard diesel injection system, managed by the original ECU, initiates combustion of the premixed air/hydrogen charge. The dual fuel operation is tested at 2000 rpm maximum torque. To maintain this condition, both diesel quantity through accelerator input and hydrogen flow via injectors duration are adjusted. Constraints included reducing diesel fuel and avoiding knock caused by excessive hydrogen. The engine operated reliably under all tested conditions. A maximum hydrogen energy substitution HES of 70% is achieved at high load, though higher values increased PPRR. A premixed equivalence ratio of 0.40 is identified as the limit before self-ignition occurred. To prevent this and achieve maximum power, an alternative strategy is introduced. Starting from diesel-only maximum torque, diesel is gradually reduced while hydrogen is increased. Rated torque is successfully achieved with an HES up to 45%. These results demonstrate that dual fuel operation can significantly reduce fossil fuel consumption while maintaining performance. It provided combustion stability and knock limits carefully managed through appropriate control of mixture composition. Further optimization could enhance efficiency and emissions performance in future applications.
Mancaruso, Ezio, Rossetti, Salvatore, Cameretti, Maria Cristina
Neural-Network-Enhanced Air-Standard Thermodynamic Modeling for Spark-Ignition Engines Fueled with Low Heating Value Alternatives2026-24-00169/21/2026
This study presents a computational framework that integrates an air-standard thermodynamic engine model with artificial neural networks to predict the performance of spark-ignition (SI) engines operating with alternative fuels of reduced lower heating value (LHV). A deterministic thermodynamic simulator was developed in Excel, incorporating engine geometric parameters (compression ratio, bore, stroke, displacement), operating speed, and fuel properties, with particular emphasis on LHV as the dominant energetic descriptor. The model computes in-cylinder states, thermal efficiency, indicated mean effective pressure, and power output under idealized air-standard assumptions. To extend predictive capability beyond fixed-parameter analyses, a feedforward neural network was trained using datasets generated from systematic parametric sweeps of engine geometry, speed, and fuel LHV. The neural network captures nonlinear interactions between compression ratio, combustion energy release, and performance indicators, enabling rapid estimation of engine response when substituting conventional gasoline with lower-LHV alternative fuels. Results demonstrate that the hybrid thermodynamic–neural approach accurately predicts trends in efficiency degradation and power reduction associated with decreasing LHV, while identifying compensatory design adjustments, particularly through compression ratio optimization. The methodology provides a low-cost and computationally efficient tool for preliminary evaluation of alternative liquid fuels in SI engines without resorting to complex CFD or experimental campaigns. This work contributes a transparent, reproducible modeling strategy suitable for early-stage engine design studies and fuel screening, supporting sustainable fuel transitions in spark-ignition propulsion systems.
Gutierrez, Marcos, Taco, Diana
Structural Robustness and Regime-Dependent Uncertainty in a Reduced-Order Physics Model for Vehicle Fuel Consumption Using Monte Carlo Analysis2026-24-00159/21/2026
Accurate prediction of vehicle fuel consumption typically relies either on simplified empirical correlations or on high-fidelity simulations that are computationally expensive. However, the structural robustness of reduced-order physics-based models under parametric uncertainty has not been systematically quantified. In particular, the interaction between model simplifications and uncertainty in vehicle and fuel properties across different operating regimes remains insufficiently investigated. This study presents a reduced-order physics-based framework derived from fundamental force and energy balances to estimate fuel consumption in L/100 km. The model includes aerodynamic drag, rolling resistance, inertial effects, drivetrain efficiency, and fuel lower heating value. Unlike purely empirical formulations, the proposed structure preserves physical interpretability while remaining computationally efficient. Monte Carlo simulations are employed to propagate simultaneous uncertainties in vehicle mass, drag coefficient, rolling resistance, engine efficiency, and fuel energy content. Thousands of randomized realizations are executed to quantify output variability, compute confidence intervals, and evaluate robustness indices. In addition, regime-dependent dominance transitions are analyzed by comparing urban and highway operating conditions. Results show that parameter influence is strongly dependent on speed regime: mass and rolling resistance dominate in low-speed conditions, while aerodynamic parameters become dominant at high speeds. Fuel energy content and efficiency exhibit nearly linear inverse relationships with consumption. The reduced-order structure demonstrates stable variance behavior under realistic uncertainty ranges, supporting its suitability for parametric studies and alternative fuel assessment. The proposed framework contributes a systematic evaluation of structural robustness in simplified physics-based fuel consumption models and provides a scalable methodology for uncertainty-aware automotive performance analysis.
Gutierrez, Marcos, Taco, Diana
Data-Driven System Dynamics and Chauvenet-Based Outlier Detection for Assessing Global CO₂ Emissions under Fossil Energy and Electric Vehicle Transition Scenarios2026-24-00209/21/2026
Understanding the structural drivers of global CO₂ emissions requires integrated analysis of fossil fuel production, total energy consumption, and electric vehicle (EV) deployment trends. This study presents a data-driven modeling framework combining system-dynamics formulation with statistical outlier detection implemented in Python to evaluate emission trajectories over a ten-year historical period. The methodology incorporates historical datasets of global CO₂ emissions, primary energy consumption, fossil fuel production, and EV manufacturing volumes. A computational routine developed in Python applies the criterion proposed by William Chauvenet to identify statistically inconsistent observations within the dataset, ensuring robustness prior to regression and correlation analyses. Carbon intensity (CO₂ per unit of energy) is calculated to assess decoupling behavior, while correlation matrices and elasticity indicators quantify the relative influence of fossil production and EV penetration on emissions. The dynamic structure expresses CO₂ emissions as a function of fossil energy share, total energy demand growth, and electrification rate. Sensitivity analysis evaluates the responsiveness of emissions to variations in these parameters. Results indicate that emission reductions are strongly dependent on carbon intensity evolution rather than EV growth alone. Outlier detection enhances model reliability by preventing anomalous years from biasing trend interpretation. The proposed framework provides a transparent and computationally efficient tool for emission diagnostics, transition scenario evaluation, and policy-oriented forecasting within the context of sustainable mobility and global energy transformation.
Gutierrez, Marcos, Taco, Diana
Optimal Eco-Driving for Electric and Conventional Refuse Trucks: A Comparative Analysis of Actual Speed, Energy Efficiency, and Travel Time2026-24-00319/21/2026
Achieving significant reductions in energy consumption and CO₂ emissions in the transportation sector is a key challenge for sustainable mobility, particularly for vocational trucks operating under demanding driving and duty cycles. Beyond technological advancements in powertrain design, energy efficiency can be improved through optimized driving strategies. In this context, eco-driving has emerged as an effective approach to reduce energy consumption by optimizing the speed profile under given operational constraints. Eco-driving optimization strategies are particularly well suited for predefined and repetitive driving cycles, such as those typically encountered in waste collection. This work presents a comparative analysis between electric and internal combustion engine powertrain configurations applied to refuse trucks and vehicles, highlighting the impact of intrinsic differences on optimal speed profiles, energy consumption, and travel time. Both configurations are required to follow identical routes characterized by speed limits, mandatory stops, and comfort-related constraints. To address the optimization problem, the conventional longitudinal dynamics equations are reformulated from a time speed domain to a spatial speed domain through spatial discretization. The spatial domain is subsequently discretized, enabling the formulation of an optimization problem solved using dynamic programming to determine the optimal speed profile along real-world routes. The optimization framework is based on the minimization of a cost function composed of two main terms, normalized energy consumption and travel time variation, and a shape factor introduced to balance the tradeoff between energy efficiency and travel time. The objective of the study is to compare the two powertrain configurations under identical routes and constraints, analyzing energy consumption and travel time, and to identify the optimal compromise between time and energy consumption for each case. The results provide insights into the effectiveness of eco-driving strategies and underline the influence of powertrain architecture on optimal driving behavior.
Giacobbo, Andrea, Beltrami, Daniele, Villani, Manfredi, Tribioli, Laura, Iora, Paolo, Uberti, Stefano
Simulation-Based Comparison of Powertrain Layouts for Light Commercial Vehicle Application2026-24-00329/21/2026
The transition towards cleaner solutions in the mobility and transport sector calls for new powertrain configurations. Besides the passenger vehicle segment, this also applies for the transportation of goods in road traffic. The most popular options are the electrification of vehicles and the utilization of renewable fuels. Hybrid powertrain configurations which allow the combination of the two solutions are also discussed. This paper focusses on light commercial vehicles (LCV) which can be used in a variety of transportation applications. Besides the reduction of CO2 emissions, other requirements apply for a powertrain for this type of vehicle. To ensure cost-efficient transportation of goods, the overall weight of the powertrain should not negatively affect the maximum payload of the vehicle. Time-consuming refueling processes should be kept at a minimum to enable a high uptime. Therefore, optimized solutions must always represent a compromise between these targets. To give an overview of the advantages and disadvantages of different powertrain solutions for different use cases, this paper compares different powertrain layouts for LCVs in both distribution- and long-range-application based on forward simulations. Besides a conventional diesel powertrain, which is used as a baseline, a diesel powertrain fueled by hydrotreated vegetable oil (HVO), a battery-electric powertrain, an electric powertrain with a diesel range-extender also fueled with HVO as well as a fuel-cell electric vehicle with a proton exchange membrane fuel cell (PEMFC) are investigated. All powertrain layouts are compared in terms of fuel consumption, CO2 emissions resulting from powertrain production, fuel production and operation as well as operation costs and the powertrain layouts impact on the payload.
Weimer, Niko, Knaup, Lars, Lavall, Philipp, Beidl, Christian, Rass, Florian, Barth, Sebastian
Tailoring ICEs Towards Future Global Market Requirements – Multi-Fuel Capability To Ensure Next Decade Market Success2026-24-00309/21/2026
The entire mobility industry currently faces enormous regulatory demands due to the Paris agreement and its corresponding initiatives to eliminate the business sector-related greenhouse gas emissions (GHG) emissions. A major focus is hereby set on wide-spread electrification of all kinds of applications, but from current perspective it is obvious that a quick and complete shift is highly unlikely, especially with view on heavy and challenging industrial and commercial applications. In line with this, it’s apparent that internal combustion engines (ICEs) maintain to play an important role in the overall propulsion system line-up. For compliance with the engaged CO2 reduction policies and efficiency improvement demands, a fast and broad replacement of fossil fuels needs to be realized. Due to the specific properties of carbon-neutral fuels and as well the variety of the range of industrial applications, different types of alternative fuels are considered. These novel fuels can be subdivided into preferred solutions for smaller or on-highway applications vs heavy off-highway and marine applications, or simply according to local or national preferences or policies. As of now, Hydrogen as well as Methanol/Ethanol is highly attractive for on-highway applications as well as construction/agricultural applications, the heavier and larger applications tend to more energy-dense energy carriers like NH3 and partially Methanol/Ethanol. In addition, to support a smooth transition to fully carbon-neutral operation, intermediate dual-fuel layouts are requested, partially requiring a full redundancy between classical Diesel operation and powering with new fuels. This complexity and variety in customer demands provide a major challenge for globally operating OEMs as future engines designs and definitions need to be developed under extreme cost pressure. The paper at hand delivers an interesting approach to design and develop modern ICE platforms for the anticipated multi-fuel case, aiming at superior key performance indicators concerning power output and efficiency, while maximizing the degree of commonality between the individual engine versions and variants. This flexibility and modularity needs to be incorporated in the base engine design, especially in the top end of the assembly, as it implicates different demands in air delivery and as well the transition from a diffusive combustion system to a pre-mixed combustion principle. This affects on one hand the installation of key sub-systems like fuel injection and ignition, but as well also the decision about an appropriate compression ratio and the definition of an adjusted in-cylinder charge motion. The article closes with recommendations for a future multi-fuel engine definition and an assessment concerning the major design changes in contrast to a refined and optimized Diesel engine layout.
Koerfer, Thomas, Dhongde, Avnish, Yadav, Jaykumar
Fuel Cell Electric Vehicle-to-Home Strategy for Residential Power Supply Continuity and Load Management2026-24-00269/21/2026
Power supply continuity for household appliances during high-demand peaks or periods of low solar generation remains a critical challenge for modern residential energy systems. Hydrogen-powered Fuel Cell Electric Vehicles (FCEVs) offer a compelling solution by extending their role from sustainable mobility to versatile mobile energy storage units. This study investigates the Vehicle-to-Home (V2H) operation of a high-performance fuel cell vehicle designed to provide backup power and peak-shaving capabilities in a domestic environment during high-demand or grid overload conditions. To evaluate this integration, a comprehensive MATLAB/Simulink simulation model was developed for a residential microgrid. The system comprises a photovoltaic array, a parallel battery energy storage system, and a Fuel Cell Electric Vehicle modeled according to the technical specifications of the Toyota Mirai, equipped with a high-efficiency 128 kW fuel cell stack (330 cells) and a dedicated 5.6 kg hydrogen storage system. The domestic electrical installation is designed for a maximum power absorption of 6 kW, operating at a standard voltage of 230 V and a frequency of 50Hz. The simulation incorporates a realistic residential load profile representative of a typical working day, characterized by distinct morning and evening consumption peaks that challenge service stability under overload conditions. The implemented control algorithm optimizes energy resource allocation by prioritizing the stationary residential battery for standard peak shaving operations. The Fuel Cell Electric Vehicle is dispatched as a secondary high-capacity power source during critical overload phases, such as the simultaneous activation of multiple high-power appliances, or when low solar irradiance prevents the photovoltaic system from adequately recharging the battery storage system. Simulation results demonstrate that the Toyota Mirai-based FCEV effectively ensures service continuity, mitigating domestic overloads and compensating for the inherent capacity limitations of stationary storage. The findings show that the fuel cell system can fully sustain the 6 kW demand during prolonged deficit periods. In conclusion, the study confirms that integrating hydrogen-based mobility into the domestic energy mix significantly enhances the resilience and operational flexibility of renewable-powered residential applications, transforming the vehicle into a strategic asset for household energy security.
Federici, Leonardo, Pistritto, Antonino, Cozzolino, Raffaello
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