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Modeling and Analysis of Mechanical-Electrical Coupling in Flywheel Systems Considering Faults2026-99-292310/19/2026
Spacecraft flywheel systems are critical actuators for attitude control and stability maintenance, and their operating reliability is strongly affected by the health state of the supporting bearings. When local defects occur on the bearing raceway or rolling elements, the rolling contact state changes abruptly, which leads to time varying contact deformation, fluctuating support reaction force, and additional rotational resistance. Unlike many ground based rotating machines, spacecraft flywheel systems usually operate in compact and highly integrated configurations, where direct vibration measurement is difficult in practice. In contrast, motor current, voltage, and speed signals are easier to acquire and are therefore more suitable for condition monitoring. To describe how bearing defects propagate from the mechanical domain to electrical responses, a simplified electromechanical coupling model is developed for a flywheel rotor motor system with local bearing defects. First, a rolling element contact model is established using the defect induced deformation relation and Hertzian contact theory to derive the time varying bearing support force. Second, the fluctuating support force is mapped to an equivalent time varying load torque to represent the dominant pathway through which bearing defects influence the motor side. Third, the derived load torque disturbance is coupled with the transverse rotor dynamic equations, the rotational motion equation, and the motor dq axis model to obtain a simplified electromechanical coupling equation set. The proposed model preserves the main physical transmission chain from bearing defect to electrical response. The model provides a clear theoretical basis for analyzing fault propagation mechanisms and for developing current based diagnostic methods for spacecraft flywheel systems.
Wu, Haolong, Li, Yuqing
Graphene Solar Sail for LEO Deorbiting Based on Experimental Light Propulsion Modeling2026-99-292610/19/2026
Graphene materials have recently been shown to produce measurable propulsion when exposed to light, raising the possibility of using them to enhance solar sail performance for satellite deorbiting. The pendulum-based experiments on graphene samples under controlled laser illumination inside a vacuum chamber and a quantitative model that describes the propulsion force as a function of laser power, illuminated area, incident angle, and ambient pressure were carried out. The measured pressure dependence and its shift with sample characteristic size point to Knudsen forces as the dominant mechanism. Orbital dynamics simulations incorporating this model show that a graphene-based sail can deorbit a 100 kg satellite from 660 km altitude roughly 21% faster than a conventional membrane sail of the same area, because the graphene configuration combines atmospheric drag with light-induced propulsion in a hybrid decay process.
Zhu, Haidong, Liu, Xiang, Cai, Guoping
Edge-Intelligent Real-Time Evaluation System for Aerospace Manufacturing Skill Training2026-99-292010/19/2026
The evaluation of practical skills in aerospace manufacturing, maintenance, repair, and overhaul (MRO) conventionally relies on examinations or observations from instructors. However, these methods deliver slow feedback, reduce the efficiency of skill acquisition and require substantial instructional workload. To overcome these challenges, this study proposes an edge-intelligent real-time evaluation system for skill training in the field of aerospace manufacturing. Specifically, the system comprises five sensing modalities, which are then processed through a hierarchical three-layer structure. Then, the neural architecture search (NAS) is introduced to identify the optimal network structure and the quantization-aware training (QAT) approach is employed to improve the inference speed. In addition, temporal modeling is used to realize real-time inference and multi-level evaluation. Moreover, a conflict-aware adaptive fusion algorithm is introduced to ensure robust scoring under harsh workshop conditions and deliver interpretable feedback. Finally, federated learning and the differential privacy mechanism are used for cross-institutional model improvement without raw data exposure. Empirical results on turbofan engine MRO assembly, airframe structural component CNC manufacturing, and aviation maintenance human factors training show that the system achieves low latency, high expert correlation, improved learning efficiency and strong robustness, which offers a scalable and privacy-aware solution for competency-based vocational training in the aerospace manufacturing field.
Li, Xin, Li, Zhaokang, Yu, Lina
Adaptive Slicing and High-Reliability Transmission Method for Spacecraft On-Orbit Data2026-99-292210/19/2026
Spacecraft On-orbit data are characterized by large volumes, stringent timeliness requirements, and heterogeneous data values, posing significant challenges to traditional satellite-ground transmission systems. To improve transmission efficiency and reliability under dynamic link conditions, this paper proposes an adaptive data slicing and collaborative reliability enhancement method. First, a joint evaluation model integrating Data Impact and Link Health is developed to evaluate data importance and transmission conditions. Based on the evaluation results, the slice size, priority allocation, and redundancy configuration are dynamically optimized. Second, a distributed collaborative verification mechanism combining Reed–Solomon erasure coding and multi-node arbitration is introduced to enhance data integrity and recovery capability. Furthermore, a mission-driven elastic scheduling strategy is designed to facilitate efficient resource allocation in multi-user transmission scenarios. Experiments were conducted on 100 telemetry files with a total volume of 1.9 GB in a simulated satellite-ground communication environment. Experimental results demonstrate that the proposed method improves average throughput by 25.3% and achieves a reconstruction success rate of 99.7% across 1,000 packet-loss reconstruction trials.
Li, Cheng, Liu, Peng, Chen, Xi, Cui, Yan, Li, Han, Li, Xian, Wang, Zhihui, Yi, Xiu
Power Allocation for Uplink RSMA in LEO Satellite Systems2026-99-292110/19/2026
This paper focuses on power allocation for RSMA-enabled uplink transmission in LEO satellite systems. A representative cluster is selected for analysis, where the terminal with the best channel quality serves as the target user and transmits its information by means of two split streams. The remaining users are treated as weak users sharing the uplink access structure. Since satellite-ground links are affected by channel estimation errors and propagation uncertainty, the available channel state information (CSI) may deviate from the actual channel. To improve the reliability of uplink transmission, a bounded CSI error model is adopted, and the decoding conditions for different successive interference cancellation (SIC) stages are formulated in a robust form. On this basis, the target-user rate is optimized under transmit-power and decoding-reliability constraints. The formulated problem is difficult to solve directly because the power variables are coupled with the SINR and rate expressions. Therefore, a successive convex approximation (SCA) method is employed to transform the original problem into a series of solvable convex subproblems. The obtained results confirm that the proposed scheme brings a clear target-user rate gain over the NOMA benchmark under the same simulation setup. The results show the effectiveness of robust RSMA power allocation for uplink interference management in LEO satellite systems.
Yu, Xiaodi, Jin, Hang, Song, Yu, Hong, Tao, Ding, Xiaojin, Zhang, Gengxin
Research on Satellite Constellation Selection Method for GEO Multi-Satellite Relay Systems2026-99-295010/19/2026
Geostationary Earth Orbit (GEO) satellites, as a crucial infrastructure for global communication and emergency support systems, are highly valued due to their wide coverage, long communication distances, and large transmission capacity. However, the scarcity of orbital slots and the difficulty in quickly identifying available satellites in actual user scenarios have become the main bottlenecks restricting the communication efficiency of multi-satellite relay systems in geostationary orbit. To address these issues, this paper proposes an accurate and efficient method for selecting the set of available satellites for multi-satellite relay applications. We construct a spatial coverage model based on the H3 hierarchical discrete global grid system and a geometric model that characterizes the visible orbital arc of the user station. By comprehensively considering the geographic locations of gateway stations and user stations, satellite beam coverage boundaries, and the visibility constraints imposed by user terminal antenna pointing, the proposed method can accurately screen out qualified satellite sets that satisfy the end-to-end link condition of “gateway–satellite–user station”. Simulation experiments are conducted in the Ku-band to validate the effectiveness of the proposed scheme, with performance metrics including coverage probability, accessible satellite quantity distribution, and selection efficiency evaluated. The results show that the H3-based modeling approach effectively reduces computational complexity while ensuring high accuracy in visibility judgment. The proposed method significantly improves the accuracy and efficiency of satellite selection, and supports dynamic updates in mobile user scenarios. This work presents a reliable satellite selection algorithm, which can be used to support efficient resource scheduling and provide a strong guarantee for GEO multi-satellite relay communication.
Yu, Xinyue, Jiang, Yanzi, Lu, Yi, Hou, Yucheng, Su, Xingyu, He, Wenxi, Zhang, Jie
PPO-Based HAP Deployment for Throughput Maximization in SAGIN2026-99-292810/19/2026
Space-Air-Ground Integrated Networks (SAGINs) have attracted extensive attention as an effective solution for providing worldwide communication services and supporting diverse transmission requirements. Nevertheless, the highly dynamic wireless environment and fluctuating user distribution introduce considerable difficulties for efficient deployment of High-Altitude Platforms (HAPs). This work studies a throughput enhancement problem in a SAGIN architecture composed of a Low Earth Orbit (LEO) satellite, multiple HAPs, and terrestrial users. Considering practical communication constraints such as beam scheduling and subchannel assignment, the objective is to improve the overall data transmission capability through optimized HAP positioning. By interacting with varying network states, the proposed learning framework agent continuously learns suitable deployment policies for HAPs, thereby improving transmission performance and spectrum utilization efficiency. Numerical evaluations indicate that the policy optimization strategy achieves superior throughput performance and communication efficiency compared with traditional fixed deployment approaches.
Wang, Yin, Zhou, Keyan, Shao, Shuai, Zhang, Bin, Chen, Peifu, Wang, Jianfeng
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
Optimal Low-Thrust GEO-to-DRO Transfers via a Multi-Layer Homotopy Strategy for Cislunar Applications2026-99-293710/19/2026
Low-thrust transfers from Geostationary Earth Orbit (GEO) to Distant Retrograde Orbit (DRO) are numerically difficult to compute because the underlying two-point boundary value problem is strongly affected by nonlinear cislunar dynamics, discontinuous control behavior, and the high sensitivity of indirect methods to the initial costates. Within the framework of the Earth-Moon Circular Restricted Three-Body Problem (CR3BP), this paper formulates an indirect optimal control model for GEO-to-DRO low-thrust trajectory design and develops a multi-layer homotopy strategy to improve the solvability of the problem. In the minimum-fuel formulation, the optimal throttle generally follows a bang-bang structure, which makes the associated shooting equations highly sensitive and often causes convergence failure. To reduce this difficulty, a smoothing homotopy is first introduced into the performance index, allowing the solution to evolve continuously from a minimum-energy problem with smoother control characteristics toward the target minimum-fuel problem. On this basis, a thrust continuation procedure is adopted to transfer the converged solution from an auxiliary high-thrust case to the desired low-thrust regime. However, when the conventional discrete continuation scheme becomes ineffective in a local thrust interval, a nonlinear intra-interval thrust homotopy combined with pseudo-arclength continuation is further employed to pass through the problematic region and maintain continuous tracking of the solution branch. Numerical results show that the proposed method can successfully overcome the local breakdown encountered in classical continuation and eventually obtain the minimum-fuel optimal transfer trajectory from GEO to DRO. The study indicates that the proposed framework enhances the robustness and continuity of indirect optimization for low-thrust transfers in the CR3BP, and it provides an effective computational approach for the design of cislunar transfer trajectories.
Liang, Jintang, Zhang, Zexu, Wang, Yiyu, Mao, Yicheng, Li, Yingshuo
Research on the Flow Characteristics of the Airflow Field in an Open Fan Array2026-99-297910/19/2026
Small aerial vehicles operating at low altitude are frequently exposed to wind fields with strong spatial gradients and rapid temporal variations. Although conventional closed-section wind tunnels provide well-controlled test conditions, they are generally unable to reproduce the large-scale non-uniformity typical of urban low-altitude environments. Open multi-fan arrays provide a promising alternative because they can generate programmable inflow conditions over a relatively large test area. In this study, a 9 × 9 open fan array is investigated using the momentum-source method to reproduce representative inflow conditions, including uniform flow and shear flow. The numerical results reveal a persistent edge-dissipation effect: velocity decays more rapidly and turbulent kinetic energy is higher near the outer fans than near the array center. In the uniform-flow case, a relatively stable low-turbulence corridor develops downstream of the array. In the shear-flow case, the imposed asymmetry is preserved, while edge-induced losses become more pronounced near the perimeter. These results clarify the main flow structures generated by open multi-fan arrays and provide a physical basis for future wind-environment testing of aerial vehicles.
Lu, Yuexuan, Tu, Zhan, Li, Daochun, Li, Huadong, Liu, Yiliang
Adaptive Parameter Optimization for BP/LTP in Deep Space Communication Based on a Deep Q-Network2026-99-299610/19/2026
This study addresses the limited adaptability of Bundle Protocol/Licklider Transmission Protocol (BP/LTP) parameter configuration in deep-space communication environments through a cooperative optimization mechanism that operates under dynamic link conditions and diverse service demands. Conventional BP/LTP parameter settings typically rely on fixed thresholds or empirical rules, assuming relatively stable link states. However, in practical deep-space missions, the bit error rate, propagation delay, and available transmission rate all exhibit significant temporal variability. Moreover, variations in data size and reliability requirements further exacerbate the performance degradation caused by parameter mismatches. Owing to the multi-layer encapsulation and resource coupling of bundle size, block size, segment size, and the number of sessions, inappropriate parameter configurations can result in increased acknowledgment and retransmission overhead, underutilized link capacity, and prolonged end-to-end delivery latency. Traditional approaches are thus inadequate for achieving holistic, real-time, and joint optimization in such dynamic environments, necessitating adaptive parameter tuning mechanisms with link-state awareness. This paper formulates BP/LTP parameter optimization as a sequential decision process and proposes a method based on a Deep Q-Network (DQN) for adaptive parameter configuration. The state space includes transmitted data size, bit error rate, one-way propagation delay, and available transmission rate. Based on this state information, the DQN selects the bundle size and LTP block size from predefined candidate sets. The LTP segment size is derived from a mapping rule related to link conditions, and the number of concurrent sessions is calculated online using an analytical model. The method is evaluated on a satellite–ground simulation platform that consists of a BP/LTP sender, a BP/LTP receiver, and a computing unit for DQN parameter optimization. It is compared with three fixed parameter configurations in 36 experimental scenarios. The results show that, compared with the fixed configurations, the proposed method reduces end-to-end delivery latency, improves link utilization efficiency, and maintains more stable transmission performance under different link conditions and data scales.
Han, Yingxiang, Bian, Mingyue, Chang, Xiang, Cao, Suzhi, Yan, Lei
Adaptive Optimization of Fault Diagnosis Models Based on Reinforcement Learning and Robustness Quantification Feedback2026-99-299510/19/2026
Spacecraft operate in a highly complex in-orbit environment. Telemetry data from power systems is often plagued by multi-source disturbances such as plasma noise, electromagnetic interference, and communication packet loss, which places very strict demands on fault diagnosis model reliability. Using dynamic disturbance test manifolds and the comprehensive robustness quantification index (RQI) for evaluation, we found a critical vulnerability: baseline models such as the joint loss enhanced global sparse attention transformer (JLE-GSA-Transformer) perform well in resisting continuous signal disturbances, but their performance drops sharply when temporal structures are disrupted due to data missingness. This finding highlights that static diagnostic models have fragile robustness boundaries when operating under extreme non-stationary conditions. To solve this problem, this paper puts forward an adaptive optimization method that combines deep reinforcement learning (RL) with quantitative robustness feedback. By making use of the dynamic disturbance manifold, this method embeds the RQI into the reward function of the RL algorithm. Through continuous updates to the agent’s policy, it drives the adaptive adjustment of key parameters in the JLE-GSA-Transformer, mainly including the coding structure of global sparse attention (GSA) and the discriminative boundaries of temporal cosine-center joint loss. This closed-loop mechanism can significantly improve the stability, adaptability, and long-term reliability of the model when it works in complex environments with multi-source disturbances.
Liu, He, Wei, Cheng, Zhang, Zexu
Friction Dynamics Modeling and System Simulation of Large-Angular-Momentum Flywheels for Satellites2026-99-296410/19/2026
In response of the stringent requirements of high-resolution optical remote sensing satellites for attitude control stability and micro-vibration environment, this study focuses on the friction dynamics modeling and simulation analysis of large-angular-momentum flywheels across a wide speed range. To quantify the impact of flywheel friction disturbances on satellite attitude pointing accuracy, friction torque characteristic data were first acquired through ground testing over the full speed range, and a high-fidelity static fitting mathematical model was constructed using the least squares method. To further elucidate the nonlinear friction mechanisms in the low-speed regime—particularly during speed zero-crossings—the LuGre dynamic friction model was introduced, and its core parameters were identified and optimized. Comparative results demonstrate that the model exhibits high-precision characterization capabilities, with a deviation of less than 0.0015 Nm from measured data within the critical low-speed range of ±50 rpm. Subsequently, the established friction model was integrated into a satellite attitude control closed-loop system for digital simulation to quantitatively evaluate the disturbance of friction torque on system steady-state accuracy. The results indicate that under the closed-loop control compensation mechanism, the impact of flywheel friction on satellite attitude pointing accuracy is effectively suppressed, with the attitude angle deviation maintained within 0.002°, thereby meeting the engineering requirements for high-precision remote sensing imaging. This research provides a theoretical basis and data support for the optimization design of flywheel systems and the refined design of satellite attitude controllers.
Hu, Yuewei, Liang, Zhulin, Lu, Ming, Zhang, Pengbo, Hu, Xiaozhen
A Dynamic Primary/Backup Path Algorithm Based on Multi-Level Feedback Queue for Differentiated Services in LEO Satellite Networks2026-99-297710/19/2026
With the accelerated deployment of Low Earth Orbit (LEO) mega-constellations, such as Starlink and OneWeb, satellite networks are transitioning from providing best-effort connectivity to supporting stringent, mission-critical services, including autonomous driving coordination, ultra-high-definition video streaming, and real-time financial transactions. This paradigm shift imposes highly heterogeneous Quality of Service (QoS) requirements regarding latency, bandwidth, and reliability. However, traditional unified scheduling and static routing mechanisms are inadequate for handling the dynamic topologies and bursty traffic inherent in LEO environments, often leading to service starvation or excessive packet loss. To address these challenges, this paper proposes an integrated primary-backup path guarantee framework that tightly couples a Multi-Level Feedback Queue (MLFQ)-based dynamic scheduling algorithm with a Dynamic Weight Adaptive Routing Algorithm (DWARA). The MLFQ scheduler employs an aging-based priority promotion mechanism to dynamically adjust time slices, effectively preventing low-priority traffic starvation while ensuring ultra-low latency for Class A services. Concurrently, DWARA models QoS as a three-dimensional vector (Throughput, Delay, Reliability) and utilizes the eigenvector method to derive service-aware weights for path selection. To validate the efficacy of the proposed scheme, comprehensive simulations were conducted using STK and Python, emulating a 64-node polar constellation under varying fault conditions. The results demonstrate that the integrated framework significantly outperforms baseline algorithms. Specifically, it reduces the average blocking rate by up to 37% under scenarios with 10 faulty satellites compared to Dijkstra, while lowering end-to-end latency for delay-sensitive services to approximately 28 ms at a traffic arrival rate of 500. Furthermore, the framework achieves a 92% bandwidth satisfaction rate for high-throughput services and maintains near-zero packet loss for high-reliability transmissions, offering a scalable and robust QoS assurance solution for next-generation space-air-ground integrated networks.
Zhang, Hongyuan, Zhang, Pengfei, Zhou, Qihao, Gao, Zhao
Multivariate Satellite Telemetry Data Compression with Spatial Reduction Based on Linear Correlation-Guided Channel Selection and Receiver-Side Recovery2026-99-298910/19/2026
Satellite telemetry data compression is of great importance for preserving the integrity and effectiveness of telemetry information. As the number of telemetry parameters gradually increases, satellite states can be characterized from more comprehensive data dimensions. However, it is difficult to maintain long-term high-sampling-rate transmission for all channels constrained by telemetry bandwidth. This condition weakens the capability of telemetry data to capture satellite state variations in a sufficiently detailed manner. Therefore, it is still a challenge for selecting more representative telemetry channels and recovering the remaining dimensions. To address this issue, this paper proposes a data compression method based on linear correlation-guided channel selection and receiver-side Long Short-Term Memory Variational Autoencoder recovery, in which satellite telemetry data compression is achieved through spatial reduction. First, the Pearson correlation matrix of all channels is computed from telemetry data, and the structure among telemetry channels is analyzed based on a prior on pairwise linear relations. Second, a linear correlation-guided iterative channel selection strategy is developed under a fixed transmission budget. Candidate channels are scored by the residual correlation coverage matrix over the unselected channels, and the initially selected subset is further refined through local channel swapping to obtain a more globally representative transmitted subset. Finally, the transmitted channels are fed into the reconstruction model to recover the untransmitted channels, so as to ensure the transmission of telemetry information. Experiments are conducted on real multivariate satellite telemetry data under predefined transmission budgets. Results on 84-dimensional real operational satellite telemetry data show that the proposed method exhibits favorable data compression capabilities. Representative RMSE comparisons under different transmission budgets further showed favorable reconstruction performance, demonstrating the feasibility of the proposed method for telemetry data compression under limited communication resources.
Wang, Zhipeng, Zhang, Kuibin, Song, Yuchen, Peng, Yu
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 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
An Integrated Fault Diagnosis and Prediction Method for Planetary Gears Based on Ensemble Learning2026-99-294410/19/2026
Planetary gears are key transmission components in spacecraft drive systems and are prone to failures under long-term operation in harsh environments. To address the problem that fault diagnosis and life prediction are treated separately in existing research, this paper proposes an integrated diagnosis-prediction method. First, order tracking and time synchronous averaging are used to preprocess vibration signals, eliminating speed fluctuations and noise interference. Then, fault features are extracted via VMD/EEMD decomposition, and the gear health condition is identified through a deep convolutional neural network. Finally, ensemble learning prediction models are established separately for different fault states to realize life prediction. Experimental results show that the VMD+CNN method achieves higher diagnostic accuracy than traditional methods for gears in healthy, cracked, spalled, and pitted conditions. The ensemble prediction models matched with different states can further reduce the life prediction error. This method provides effective technical support for condition-based maintenance of spacecraft planetary gears.
Liu, Yanyan, Gao, Tongxin, Zhu, Yangsong
Acceleration Factor Derivation Using Test Bed and Field Failure Data of Automotive Engines2026-01-507710/19/2026
Reliability testing and validation are essential parts of any automobile development project. These tests mainly depend on two things: how much of the product’s target life is covered and whether enough samples are tested to capture variations. Today, most projects face tight timelines and cost constraints, which makes it important to design an optimized reliability test plan. Accelerated testing is widely used to reduce testing time, but finding the correct acceleration factor for a complex system like an automotive engine is difficult. Existing studies describe methods such as simple stress tests, step-stress tests, and degradation tests to shorten test duration. However, these methods need more samples at different stress levels to establish a clear relationship between stress and life and then calculate the acceleration factor. While such models work well at the component level, they become much more complicated at the system level because different components can have different acceleration behaviors. In this paper, a method is proposed to derive the acceleration factor by correlating engine test bed data with field failure and usage data. Test engineers often use standard accelerated test cycles for engines used in similar applications. As a result, organizations usually have historical test data and field data from earlier, similar products. The proposed approach models accelerated test data and field failure data separately and then links them to determine the acceleration factor. This derived factor can later be used in future engine development projects to convert test cycles into equivalent field mileage coverage. Weibull analysis and regression techniques are used to support the case studies presented in this work.
Koulage, Dasharath Baliram, Mondal, Kanchan
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
Automatic Transmission Intake Filter Test ProcedureJ2312_202610 (Current)10/9/2026
This test procedure is intended to apply to hydraulic pump suction filters and strainers used in automotive automatic transmissions that include hydraulic power pumps. The various paragraphs of Section 5 include a variety of tests and alternative tests that are not applicable to all filters and applications, so the engineer must specify which tests are to be performed for a particular application. These test procedures are intended to evaluate filter functional performance characteristics only; durability is not evaluated under this standard. Filter design requirements must be specified by the engineer on the filter assembly drawing, an applicable engineering specification, or summarized on an application data sheet similar to that found in this recommended practice. See Figure 6. Pressure circuit filters, both barrier and system contamination control types, are not covered under this standard. They are similar in design and construction to filters used in many hydraulic and lubricating applications. Testing for pressure filters is covered by the ISO and SAE standards listed in Section 2.
Automatic Transmission and Transaxle Committee
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
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
Effect of High-Energy Ignition and Spark Plug on Combustion and Fuel Economy of a Dedicated Hybrid Engine03-19-05-002610/6/2026
High exhaust gas recirculation (EGR) rates in dedicated hybrid engines (DHEs) cause combustion instability and fuel economy degradation. This study investigates a 2.0L turbocharged DHE with a high-tumble combustion system optimized by computational fluid dynamics (CFD) simulation. At the brake thermal efficiency (BTE) operating point (2750 r/min, brake mean effective pressure [BMEP] 11 bar), engine bench tests evaluated the effects of three ignition energy levels (120 mJ, 150 mJ, 200 mJ) and two spark plug configurations (1.1 mm nickel alloy and 0.7 mm pin-to-pin iridium) on combustion characteristics, fuel economy, the misfire-limited EGR rate (hereinafter the EGR misfire limit), and engine-out emissions. Results show that above 23% EGR, intake condensate weakens ignition and destabilizes combustion. Raising ignition energy to 200 mJ extends the EGR misfire limit from 23% to 28%, shortens ignition delay (CA0-10) and combustion duration (CA10-90) by 4.5°CA and 2.8°CA and reduces BSFC by 3.2 g/kWh. The 0.7-mm iridium plug outperforms the 1.1-mm nickel alloy plug above 27% EGR: CA0-10 and CA10-90 shorten by 2.9°CA and 2.5°CA, the EGR misfire limit extends by 0.5 percentage points, and BSFC improves by 0.9 g/kWh. The combined optimization extends the EGR misfire limit to 28.5% with a cumulative BSFC reduction of 4.5 g/kWh. HC emissions decrease with reduced spark plug gap, while NOx and CO remain insensitive to the ignition strategy. The coupled optimization of high-energy ignition and small-gap spark plug effectively overcomes ignition degradation under high EGR. The reduced breakdown voltage of the small gap and the sufficient energy reserve of high-energy ignition form a synergistic effect, providing quantitative design guidance for ignition systems in next-generation high-efficiency DHEs.
Wang, Peng, Ren, Siming, Cong, Rizhen, Deng, Xiaorong, Liu, Zonghui, Zhu, Yunfeng, Li, Hongzhou, Yan, Pingtao
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.
Development and Experimental Study of Vehicle Control System for Pure Electric Construction Machinery14-15-03-001910/1/2026
This article develops a comprehensive vehicle control system for pure electric wheel loaders, covering the entire development process. Based on a dual-motor and two-speed transmission configuration, the collaborative design of the hardware and software for the vehicle control unit (VCU) was completed. Vehicle control strategies were developed, including motor demand torque calculation, an overspeed protection algorithm, a gear shift control algorithm, an energy recovery strategy integrating coasting and braking, and control methods for the working system. Finally, the control strategies were verified and optimized through real vehicle tests. Experimental results indicate that the developed pure electric loader exhibits excellent performance. Compared with a diesel counterpart of the same tonnage, its maximum speed is increased by 19.4%, operational productivity (V-cycle loading cycles per hour) is improved by 8.7%, while the operating cost is only 35% of that of the diesel model. This study provides a solution validated by real vehicle tests for the development of vehicle control systems for pure electric construction machinery.
Xu, Haozhi, Ji, Shaobo, Che, Renhai, Tan, Yuchen, Hou, Defeng, Ren, Shuojin, Zhao, Jiayang
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
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
AI-Driven Predictive Sonification for Human-on-the-Loop Ground Vehicle Autonomy2026-01-75039/22/2026
Ground vehicle autonomy increasingly depends on human-on-the-loop (HOTL) supervision, yet supervisors are often overloaded by visual interfaces that can obscure emerging risks. This paper presents an AI-driven predictive sonification architecture that converts short-horizon forecasts of platoon behavior into structured auditory cues for supervisory monitoring. A forecasting engine predicts future vehicle interaction states and evaluates predicted and active violations to generate a composite risk indicator. When risk exceeds defined thresholds, a sonification module conveys risk magnitude and trajectory through changes in pitch, loudness, modulation, and spatial panning. The paper describes the system architecture, sonification design, operational use cases, and a planned human-subject evaluation. The proposed framework is intended to improve early awareness of emerging instability and support more timely supervisory intervention.
Plotzke, Zachary R., Mohammadi, Alireza, Cheung, Calvin M.
Development of a UAV Platform for Remote Inspection and Visualization2026-01-75119/22/2026
This paper details the development of an intelligence and inspection platform consisting of an attritable sub-250g UAV, a ground control station, and a visualization interface for users. The UAV architecture combines onboard obstacle detection and avoidance along with simultaneous localization and mapping to have full autonomous navigation inside of complicated GPS-denied environments. The ROS 2-to-Unreal Engine data pipeline allows for sensor fusion, data cleansing, and initial analysis as well as creation of a high-fidelity real-time 3D digital twin. The visualization interface allows users to easily identify critical features and turn data into intelligence to support decision making by soldiers and first responders.
Lee, Yeen K., Bainard, Sean, Shaughnessy, Michael, Bolger, Matt, Koepp, R. Tucker, Salehzadeh, Roya, Mallory, Stephen, Mynderse, James A., Guillen, Pedro, Hernandez, Margarita
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
Distributed Intelligence at the Tactical Edge: Enabling Contested Logistics in Degraded Networks2026-01-75589/22/2026
Contested logistics environments expose the limitations of both legacy fragmented systems and emerging Next Generation Command and Control architectures that assume persistent connectivity. In degraded or denied conditions, sustainment operations face latency, bandwidth constraints, and reduced decision velocity. Expanded decision support tools further increase reliance on timely, relevant data exchange. This paper argues that contested logistics requires distributed, mission-aware intelligence at the tactical edge. Low-power onboard compute enables real-time inference, adaptive data conditioning, and connectivity-aware transmission across Radio-Frequency and non-RF pathways. By selectively elevating critical information based on mission context and network state, edge-intelligent architectures improve survivability, bandwidth efficiency, and sustainment effectiveness in degraded networks.
Baumann, Edward, Pardee, Shawn
Methods for Designing Rotating Components for Compliance to ISO 1940 Balance Requirements using Generic 3D CAD Software2026-01-75659/22/2026
The benefits of specifying balance requirements in terms of an ISO 1940 balance quality grade instead of traditional mass-distance based requirements are discussed along with methods to convert ISO 1940 balance quality grades into permissible imbalance limits at the bearing supports. Methods are developed to determine the expected imbalance values at bearing supports using mass property data from generic 3D CAD software packages without the need for Finite Element Analysis. Practical exercises are presented using these methods to assess a part’s compliance to ISO 1940 while still in the conceptual 3D CAD design stage. These practical exercises cover the selection of appropriate geometric tolerances to ensure part balance without the need for post fabrication balancing as well as the design of nonsymmetrical components for ISO 1940 balance compliance. Citation: J. Srodawa, “Methods for Designing Rotating Components for Compliance to ISO 1940 Balance Requirements Using Generic 3D CAD Software,” In Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium (GVSETS), NDIA, Novi, MI, Aug. 11-13, 2026.
Srodawa, John
Stuck-Assist: A Large Multimodal Model-Based Stuck Recovery Assist for Driving on Off-Road Deformable Terrains2026-01-75139/22/2026
Recent advancements in off-road autonomy have shown significant progress in perception, planning, and control frameworks, including end-to-end learning approaches. Comprehensive results have been demonstrated in both simulation and real-world experiments; however, there are significant challenges in critical cases that need further evaluation. One such challenge is the immobilization of autonomous ground vehicles (AGVs) in unstructured off-road environments, which can significantly impact agriculture, space exploration, military operations, and search and rescue missions. Addressing this problem requires recovery strategies that are context-sensitive, adaptable to terrain and vehicle conditions, and effective in integrating multimodal inputs. To this end, this paper investigates the use of a large multimodal model (LMM) providing higher-level planning assistance with human-in-the-loop evaluations for vehicle recovery after immobilization in unstructured off-road terrain. The experimental simulation platform developed was based on the Algoryx (AGX) Dynamics engine for high-fidelity terramechanics interaction and vehicle physics combined with Unreal Engine 5. This platform was further integrated with a driving simulator equipped with steering wheel and pedal interfaces for human-in-the-loop experiments. We evaluated ten representative unstuck scenarios across two deformable terrains (loose sand and compact sand) under two modes: an unskilled baseline, where participants attempted recovery unaided, and a co-intelligence mode, where participants used LMM advisory instructions. The results show that LMM assistance improved stuck recovery rates by 70% compared to unaided and unskilled human driving.
Bhosale, Mayuresh, Whitson, Jordan A., Vahidi, Ardalan, Jia, Yunyi
Deep Learning-Based Rotor Temperature Estimation for Rare-Earth-Free Motors2026-01-75069/22/2026
This paper presents a deep learning-based approach for online rotor temperature estimation in electrically excited synchronous motors (EESMs). Accurate rotor temperature estimation is critical for ensuring safe operation, improving performance, and enabling reliable thermal management of electric traction motors. Recurrent neural network (RNN) architectures, including gated recurrent unit (GRU) and long short-term memory (LSTM) networks, are investigated to develop a data-driven thermal virtual sensor capable of capturing the temporal dynamics of motor operation. Experimental data collected from a 190 kW EESM prototype are used to train and evaluate the proposed models. A systematic training, testing, and 10-fold cross-validation framework is employed to assess prediction accuracy and generalization capability. The results demonstrate that the GRU-based model achieves higher prediction accuracy than the LSTM model while maintaining comparable inference latency. The proposed approach provides an efficient and lightweight solution for real-time rotor temperature estimation suitable for embedded motor control applications.
Tatari, Farzaneh, Aligoudarzi, Mohsen Mirza
Patching an Engine Control Module to Enhance Security2026-01-75219/22/2026
The architecture of Controller Area Network (CAN)-based protocols offers straightforward, centralized, and cost-efficient methods for various Electronic Control Units (ECUs) to communicate via the CAN bus. However, the CAN protocol was not designed with security as a priority. The CAN bus used in vehicles lacks built-in security features, (i.e., messages are broadcast without authentication or encryption). This makes CAN vulnerable to eavesdropping, spoofing, and replay attacks. Any compromised node can inject false messages (e.g., impersonating the brakes or engine controller) with no cryptographic checks to stop it. The protocol’s primary integrity safeguard, a Cyclic Redundancy Check (CRC), was designed solely for detecting transmission errors and is easily manipulated, offering no real protection against malicious adversaries. Implementing cryptography on CAN is challenging due to CAN’s most popular limited 8-byte data payload, real-time latency requirements, and the need for compatibility with millions of existing CAN devices. To address this issue, this study focuses on developing a Cryptographic Message Authentication Code (CMAC) Intrusion Detection System (IDS) implementation for CAN bus communication using existing ECUs.
Beer, Spencer, Jepson, Jake, Nogin, Aleksey, Daily, Jeremy
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
Processing and Validating CFD Data for Estimating Inlet Dynamic Total-Pressure DistortionAIR6345A (Current)9/21/2026
The processes addressed in this AIR apply to the acquisition and validation of dynamic total-pressure and distortion data from CFD models simulating turbulent flows in inlets. The results of these processes can be used in the formation of an inlet-flow-distortion methodology that addresses turbine-engine operability assessments.
S-16 Turbine Engine Inlet Flow Distortion Committee
Business Approach to Cope with Automotive Market Uncertainty2026-24-00249/21/2026
The global automotive industry is facing an unprecedented convergence of uncertainties driven by geopolitical tensions, evolving trade policies, emissions related regulations, and increasingly volatile consumer demand. Shifting emissions legislation, including the EU’s tightened CO2 targets and long-term plans to phase out internal combustion engines, is imposing strategic and financial pressures on automakers and suppliers as they navigate divergent regional regulatory trajectories. Demand side volatility further complicates the landscape. Consumer preferences are fluctuating due to economic pressures, infrastructure constraints, and uneven EV adoption patterns. While some markets show stagnation in battery electric vehicle uptake, hybrids are rising as consumers seek cost efficient alternatives amid uncertain energy and regulatory environments. Within this unstable context, the transition toward Software Defined Vehicles (SDVs) is emerging as a critical strategic response. SDVs, characterized by centralized computing, updatable software architectures, and over the air feature deployment, offer automakers greater adaptability in addressing regulatory shifts and market dynamics. By decoupling hardware from software cycles, SDVs enable faster innovation, reduced development risk, and new digital revenue models, while virtualization and AI driven analytics enhance development efficiency and lifecycle value.
Cavanna, Filippo, Potenza, Luca
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
Passive Thermal Management Through Vapor Chamber Integration of a PMSM E-Motor installed on UAV for Urban Mobility Applications2026-24-00109/21/2026
Thermal management is a critical design challenge for Permanent Magnet Synchronous Motors (PMSMs) employed in Unmanned Aerial Vehicle (UAV) propulsion systems, where high power density and compact integration lead to significant heat generation. Excessive temperatures can compromise efficiency, reliability, and component lifetime, making the development of effective and lightweight cooling solutions essential. This study investigates the integration of a vapor chamber as a passive thermal management solution for a commercially available PMSM intended for UAV applications, whose thermal performance is evaluated under external airflow conditions representative of low-speed flight and hovering. Unlike conventional active cooling systems, the proposed approach does not require moving parts, external power input, or additional control devices. Heat transfer is driven by phase-change mechanisms within a sealed enclosure: as the local thermal load increases, the working fluid evaporates in the hotter regions and condenses in the cooler ones, redistributing heat autonomously without external intervention — a self-regulating behavior particularly suited to the constraints of UAV propulsion systems. A simplified three-dimensional model of the motor housing was developed, and steady-state conjugate heat transfer simulations were performed in ANSYS Fluent to evaluate the thermal performance of the system. Three configurations were analyzed: a baseline motor without vapor chamber, a configuration with an integrated vapor chamber, and a configuration combining the vapor chamber with an external copper fin array. The vapor chamber was modeled using an equivalent porous-medium approach for the wick structure, coupled with a multiphase formulation to capture liquid–vapor interactions within the core. The results demonstrate that vapor chamber integration significantly reduces peak pole temperature, with reductions ranging from 38K to 159K (approximately 10% to 31% relative to the baseline configuration) depending on operating conditions. At higher thermal loads, the device transitions from a liquid-filled regime to an active two-phase operation, enhancing heat transfer through evaporation and condensation. The addition of an external copper fin array further improves thermal performance, achieving a maximum pole temperature reduction of 203K (approximately 33% relative to the baseline) under low-airflow, high-load conditions. A key finding of this study is the strong coupling between the external fin array and the internal phase-change behavior of the vapor chamber: by lowering the condensation-side temperature, the fins promote a more active two-phase regime, enhancing overall heat transfer performance beyond what either component achieves independently. These results highlight the potential of vapor chamber technology, particularly when combined with extended surfaces optimized for the dominant flight regime, as a lightweight, passive, and self-regulating cooling strategy for compact UAV electric propulsion systems.
Benedetti, Silvia, Lombardi, Simone, Federici, Leonardo, Chiappini, Daniele
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
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
Electrical Waveform Analysis of Spark Discharge for Monitoring Conditions Inside Prototype Prechambers2026-24-00139/21/2026
Using renewable fuels like hydrogen in internal combustion engines requires new combustion strategies and ignition systems like pre-chamber sparkplugs. This necessitates novel measurement and monitoring techniques to gain insights into the phenomena arising from the use of new fuels and components. For understanding the phenomenon of pre-chamber ignition, it is important to observe how sparks behave inside them. The spark-elongation under certain conditions inside a particular pre-chamber, its location at a given time during discharge, and the flow conditions during spark discharge are all significant factors in gaining insight into this phenomenon. However, such information is difficult to obtain from inside a pre-chamber due to the difficulty of gaining optical access. In such cases, the electrical waveform analysis could prove useful. During this study, the electrical parameters are used to calculate the spark length, providing information about the igniting volume inside a pre-chamber during the spark discharge. This was achieved by modifying the Kim and Anderson equation to meet the specific requirements of the study, which involved correlating it to the optical spark length obtained in a spark wind tunnel test bed under conditions similar to those in an engine. This modified equation was then used to calculate the spark length inside different prototype pre-chambers and sparkplug to compare and contrast the conditions. Information about the flow conditions inside the pre-chamber was also obtained from the spark length, given that the surrounding flow influences spark elongation. This methodology was first validated in the spark wind tunnel test bed before pre-chambers were tested in the engine. Testing different prototype pre-chambers provided valuable insights into the flow conditions, demonstrating the technique's effectiveness in understanding the factors that make a pre-chamber design suitable for a particular fuel and set of conditions, and why it is less effective in other situations. This study proves that electrical waveform analysis is a key tool for monitoring the performance of prototype pre-chambers designed for renewable fuels, such as hydrogen.
Kottakalam, Saraschandran, Nenzel, Markus, Rottenkolber, Gregor
Thermal Management of Pre-Chamber Spark Plugs for the Mitigation of Abnormal Ignition in Hydrogen-Fueled Engines – An Experimental and Numerical Study2026-24-00079/21/2026
The internal combustion engine will continue to contribute to global mobility, particularly when operated with carbon dioxide low-carbon fuels. Pre-chamber ignition systems are increasingly investigated to improve efficiency, emissions, and combustion stability. In combination with hydrogen as a carbon-free fuel, they extend the lean operating limit while ensuring reliable ignition under demanding conditions. A key challenge is the thermal management of pre-chamber spark plugs. While the thermal behaviour of conventional spark plugs is well understood, limited knowledge exists for pre-chamber systems. Chamber geometry, material selection, manufacturing, and installation strongly influence thermal loading, where elevated local temperatures may contribute to knock, pre-ignition, and material degradation. The objective of this study is to establish a system-level understanding of pre-chamber thermal behaviour. Experiments are conducted on a single-cylinder research engine using hydrogen and research octane number 95 (RON 95) as a reference fuel. Dedicated temperature measurements identify thermal hotspots and assess parameter sensitivities. For the investigated configuration (14:1 compression ratio (CR), 1500 revolutions per minute (rpm), 12 bar indicated mean effective pressure (IMEP)), measurements and conjugate heat transfer (CHT) simulations suggest wall temperatures are not the primary contributor to pre-ignition. Reduced pre-ignition is observed with increasing scavenging bore diameter, indicating a strong influence of mixture preparation and residual gas effects. A coupled CHT model is integrated into a computational fluid dynamics (CFD) simulation with moving boundaries. The model includes realistic wall thicknesses, temperature-dependent material properties, and calibrated boundary conditions, enabling cycle-resolved analysis of heat fluxes and temperature fields for pre-chamber optimization.
Nenzel, Markus, Alkezbari, Ahmad Anas, Rottenkolber, Gregor
A Computational Study of High Efficiency Wankel Rotary Engines using a Passive Pre-Chamber2026-24-00019/21/2026
Wankel rotary engines are renowned as compact machines with high power-to-weight ratios, which make them suitable for use as range extenders for battery electric vehicles or as propulsion systems for unmanned aerial vehicles. However, their overall efficiency and emissions still need significant improvement to meet to the stringent regulations comparable with classical reciprocating 4-stroke engines. With the aim of improving these shortcomings, this work focuses on the application of a passive pre-chamber in order to enhance the combustion phase and the overall efficiency and emissions of such engines. Computational fluid dynamics (CFD) simulations were conducted for the commercial AIE 225CS rotary engine, configured with port fuel injection and fully-premixed gasoline combustion. The engine was extensively tested in a previous project while different CFD models were validated against experimental data in previous studies by the same authors. In particular, the present work examines the engine performance with two pre-chamber configurations with different volumes. The volume and nozzle specifications were determined to have geometrical characteristics similar to those of the theory of Gussak, with volumes directly comparable with that of the two spark park plug recesses of the original engine, leading to significantly large nozzle diameters in the pre-chambers. In addition, the effect of spark advance was investigated to capture the development of the flame and jets and the resulting effects on the indicated pressure cycle. Consistent with previous findings, heat losses were found to be a critical aspect for the different configurations of engine. Nevertheless, the application of pre-chamber shows some potential to improve efficiency by accelerating combustion phase, leading to a relative increase of 7.4% on the indicated efficiency. This suggests an important new path in the development of Wankel engines as a viable solution to efficient utilisation of decarbonised and innovative future fuels in compact systems.
Vorraro, Giovanni, Im, Hong G., Turner, James
Experimental and Numerical Investigation of Hydrogen Direct Injection in a CI Engine2026-24-00049/21/2026
Compression ignition (CI) engines are widely used in the transportation sector due to their high torque and efficiency. However, the current climatic framework limits their application, favouring the adoption of low- and zero-carbon technologies. In this context, hydrogen represents a viable energy source for driving CI engines towards clean combustion. The benefits of hydrogen enrichment in diesel engines have been extensively investigated, particularly in port fuel injection (PFI) configurations. In contrast, the addition of a hydrogen direct injection system within a Common Rail engine remains largely unexplored. In this work, a piezo-actuated outward-opening direct injector fuelled by hydrogen was investigated through a combined experimental and numerical approach. The experimental campaign was conducted on an optically accessible single-cylinder research engine (SCRE), with the injector mounted in the cylinder head. Different injection strategies were explored in terms of duration, while the start of injection (SOI) was fixed at 2° after the inlet valve closure (IVC). In parallel, numerical simulations were performed to analyse the injection process into the engine. Firstly, a zero-dimensional model was developed to provide a preliminary estimation of the pressure within the system during the injection phase. Subsequently, computational fluid dynamics (CFD) simulations were performed to obtain a more detailed prediction of the injection process. The numerical framework reproduced the transient injection phase by modelling the near-nozzle jet development and its interaction with the in-cylinder charge. Based on the combined experimental and numerical results, the effective discharge coefficient of the injector is evaluated under different injection durations, enabling a quantitative assessment of its performance.
Episcopo, Domenico, Rossetti, Salvatore, Mancaruso, Ezio, Saponaro, Gianmarco, Lorusso, Leonardo, Camporeale, Sergio, Laera, Davide
Multi-Level CFD and System Simulation Approach for Optimization of Cooling Circuits in High Power Density Powertrains2026-24-00099/21/2026
This paper presents a CFD-based optimization workflow for the simulation and development of automotive cooling circuits, integrating three-dimensional steady-state analyses with one-dimensional transient modeling. The objective of the activity is to establish a robust methodology that links detailed component-level thermal characterization to system-level dynamic simulations, enabling the assessment of cooling performance under both driving and charging operating conditions. The thermal behavior of the cooling circuit components was first investigated using three-dimensional steady-state simulations performed with Ansys Fluent. For each relevant operating point, the fluid flow and heat transfer were resolved in full 3D, and temperatures were monitored at multiple locations within the components and along the circuit. The steady-state analyses provided spatially resolved temperature fields and heat transfer characteristics for a range of boundary conditions representative of real operating scenarios. From these results, temperature and performance maps were generated, describing the relationship between operating conditions, heat loads, and thermal responses of the components. These maps were then used for the calibration of one-dimensional models implemented in GT-Suite. The calibrated 1D models reproduce the thermal behavior observed in the 3D CFD simulations while allowing efficient simulation of the entire cooling system under transient conditions. This multi-level approach enables the combination of detailed local physics from CFD with the computational efficiency required for system-level dynamic analyses. Transient simulations were carried out in GT-Suite to evaluate the thermal response of the cooling circuit during both driving and charging phases. The driving phase accounts for variable thermal loads and flow conditions associated with vehicle operation, while the charging phase represents operating conditions specific to battery recharging scenarios. The calibrated 1D models were used to simulate the evolution of temperatures throughout the system over time, considering the interactions between components and the overall thermal inertia of the circuit. The results show that the designed cooling system is capable of maintaining component temperatures within the targeted limits across the analyzed operating conditions. The thermal containment is achieved for all components included in the cooling circuit under both dynamic driving and charging scenarios. The electric motor is oil-cooled and therefore is not part of the water-based cooling circuit addressed in this study. The proposed CFD-to-1D workflow provides a consistent and transferable methodology for the thermal development of cooling systems of high power density electrified powertrains. The novel contribution lies in (i) the application of the multi-level framework to a heavy-duty platform with SiC-based power modules and dedicated on-board charger developed within the Horizon Europe POWERDRIVE project, (ii) a DOE-based map generation strategy that preserves the conjugate heat transfer interactions between actively cooled components (power modules, OBC) and passively cooled neighbors (busbar, capacitors) within the reduced-order representation, and (iii) the integration of the reduced-order maps within a single transient system-level model covering both vehicle-at-rest charging and dynamic driving operating modes. This activity is carried out within the framework of the Horizon Europe project POWERDRIVE.
Chiappini, Daniele, Tribioli, Laura, Rodionov, Artem
Comparative Analysis of BEV Performance from Simulated Environment and Physical Hardware Platform2026-24-00059/21/2026
The proliferation of simulation environments has accelerated technological progress across various scientific domains by offering a cost-effective and time-efficient framework for data acquisition and analysis. In the automotive sector, high-fidelity modelling of vehicle components and driving scenarios bypasses the logistical constraints associated with hardware procurement and the intensive requirements of large-scale testing infrastructures. However, pre-calibrated or native software models often imply simplified hypotheses, missing relevant aspects of the entire powertrain-to-wheel energy chain. This study presents a comparative analysis of battery performance within a battery electric vehicle (BEV) by synchronizing virtual simulations with experimental hardware at the test bench. The methodology involves the concurrent modelling of the driving environment, the vehicle chassis, and the propulsion system, followed by the execution of identical driving cycles on a physical platform. The experimental setup comprises a fully instrumented BEV featuring an integrated electric motor and battery pack, specifically configured for high-precision signal acquisition. The virtual section starts with the development of a digital twin within a commercial simulation suite, parameterized according to the vehicle specific dynamic and energy requirements. This is followed by the integration of the electric propulsion system and a battery pack model based on the equivalent circuit model method. To ensure high fidelity, the battery model is experimentally calibrated via multi-step pulse discharge tests performed on the physical hardware. Subsequently, various driving scenarios from the simulated environment are translated into speed-time profiles and are replicated on the real vehicle using a PID-controlled actuator on the accelerator pedal. The battery pack that serves the vehicle is monitored during the cycle to collect information on the electrical performance. Finally, a comparison between the simulated and real battery behaviour is performed. This dual approach used in the present work, which compares the simulation accuracy against real-world performance, provides critical insights into the inherent advantages and technical boundaries of digital modelling in electromobility applications.
Sequino, Luigi, Sementa, Paolo, Altieri, Nunzio, Vaglieco, Bianca Maria, Sorrentino, Chiara
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