Browse Topic: Powertrains

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Cooperative Control of Two Free-Piston Engine-Generators for Vibration Reduction2026-01-5088To be published on 11/16/2026
The free-piston engine-generator (FPEG) is a promising power unit in vehicle-mounted energy conversion systems. However, inertial-force excitation caused by free-piston reciprocating motion remains a major constraint on its practical application. To address this issue, a hierarchical control architecture consisting of a single-engine motion control layer and a two-engine synchronization control layer is proposed for an opposed two-engine FPEG system. The single-engine motion control layer combines iterative learning control with displacement feedback and adaptive compensation with velocity feedback to regulate dead-center positions. The two-engine synchronization control layer introduces a Combustion State Observer (CSO) to estimate cycle-to-cycle indicated-work variations caused by stochastic combustion fluctuations and guide differential fuel-injection compensation. A simulation verification framework is established to evaluate the proposed strategy under compound disturbances. Relative to the single-engine case, the cooperative scheme achieves a 99.6% mean-square force reduction while maintaining 43.3% indicated thermal efficiency. The residual RMS inertial force is further reduced by 38.1% compared with the master–slave baseline. These results demonstrate that the CSO-based cooperative synchronization strategy is effective in reducing inertial-force excitation in two-engine FPEG systems.
Zhao, Bowen, Ren, Boyao, Xu, Zhaoping
Hybrid-Powered Tracked Vehicle Integrated Energy Management Strategy2026-99-212311/13/2026
To address the energy management strategy of hybrid tracked vehicles, and in order to achieve a more rational power distribution among the engine-generator set and the power battery, thereby improving overall fuel economy and system operating efficiency, this paper proposes an integrated energy management control strategy based on a rule-based strategy and deep Q-networks (DQN). Considering the structural characteristics and operating features of the series-hybrid tracked vehicle power system, a relatively comprehensive vehicle dynamics and energy management simulation model is established on the MATLAB/Simulink platform. We introduce a deep reinforcement learning method. The agent’s observation inputs are the vehicle’s operating state and power demand, whereas fuel consumption, battery limits, and various system operating restrictions are folded into the optimization objective. By continuously interacting with the model environment, the agent can continuously learn energy allocation strategies for the powertrain. After training is completed, the trained agent is tested under specific operating conditions, and the proposed integrated control strategy is compared with traditional constant-voltage control and a multi-point speed control strategy. Simulation results show that, under the same test conditions, the integrated control method can optimally adjust engine speed, thereby reducing the number of operating points in the low-efficiency range. While ensuring vehicle dynamic performance and system stability, this strategy can reduce fuel consumption by at least 3.66%, thereby demonstrating its feasibility and effectiveness in energy management for series-hybrid tracked vehicles.
Yan, Zhipeng, Shi, Feina, Zhao, Zhiying, Niu, Liye, Geng, Jiangbo
Comparative Study on Fitting Methods of Low-Temperature Road Driving Resistance on Chassis Dynamometer2026-99-210911/13/2026
The driving range of electric vehicles (EVs) under low-temperature conditions remains a critical challenge in the automotive industry—especially in high-latitude regions where prolonged low temperatures severely degrade user experience. In addition to the well-documented reductions in battery energy density and charging efficiency, the effect of low temperature on vehicle road driving resistance is equally significant, contributing an additional 15%–25% to overall energy consumption [1, 2]. Guided by mainstream international and domestic standards for simulating low-temperature road driving resistance, actual road tests and chassis dynamometer resistance fitting were conducted on four representative vehicle models—including compact sedans and mid-size SUVs—at 20 °C (normal ambient temperature) and -7 °C (typical low-temperature operating condition). The discrepancies between simulated resistance values from different methods and actual road test data were systematically analyzed, along with the underlying mechanisms. The results indicate that the low-temperature chassis dynamometer set resistances obtained using the Chinese current national standard (GB/T 18386-2021) and the United Nations Global Technical Regulation No. 15 (UN GTR No. 15) are largely consistent, with deviations of 5%–12% from actual road driving resistance. In contrast, the SAE J2264 method exhibits a substantial deviation of 25%–28% from actual low-temperature driving resistance. Notably, even the −7 °C driving resistances simulated by current mainstream methods still deviate to a certain extent from real-world low-temperature road resistance. This underscores the need for further investigation into the mechanisms by which transmission system resistance and tire rolling resistance influence overall low-temperature driving resistance, as well as the development of more precise correction models to improve the reliability of low-temperature range prediction.
Bai, Bateer, Deng, Shuxiang, Nie, Guole, Niu, Yazhuo, Zhang, Xianfeng, Li, Ping, Guo, Wencui
Understanding Thermal Pre-Ignition Mechanisms in Lean Premixed Spark-Ignition Hydrogen Engines Using a Robust Pre-Ignition Characterization Approach03-19-06-002911/10/2026
Hydrogen engines are a promising decarbonization pathway for the transport sector; however, their performance is constrained by the abnormal combustion phenomenon of pre-ignition (PI). While hydrogen PI shares similarities with the extensively studied “low-speed PI” observed in boosted gasoline engines, it exhibits distinct characteristics, notably higher frequency and lower individual cycle intensity. These differences arise from the thermochemical properties of hydrogen and differing operating strategies, most notably lean versus stoichiometric combustion. This study investigates the mechanisms of hydrogen PI, broadly divided into hotspot vs oil-induced pathways, in a heavy-duty, lean-burn, port fuel–injected, spark-ignition (SI) hydrogen engine. Experimental data at three combustion phasing conditions are analyzed to understand the dominant mechanisms. Retarding ignition timing increased PI frequency from under 5% to over 20% by extending the pre-spark window during which PI triggers could initiate combustion. Oil droplet autoignition is believed to be the primary PI mechanism under the tested conditions. For quantitative assessment of PI frequency, a median-based statistical approach is proposed to identify events based on early combustion onset and/or elevated peak pressure. This approach addresses limitations of conventional standard deviation–based outlier detection methods (like the Grubbs’ method), which are prone to statistical masking at the high-PI frequencies observed.
Bajwa, Abdullah Umair, Kalaskar, Vickey, Williams, Ryan
Design Strategy for Cislunar Space Navigation Constellations Based on Navigation and Autonomous Navigation Performance2026-99-062511/6/2026
This paper proposes a bi-objective design strategy for cislunar navigation constellations, simultaneously optimizing navigation performance for target users and the autonomous navigation performance of constellation itself. The design variables include orbital characteristic parameters and inter-satellite phases, while the objectives are defined as the worst-case Geometric/Position Dilution of Precision (GDOP/PDOP) for users and the constellation's aggregated Dynamic and Geometric Dilution of Precision (DAGDOP). To address phase jump issues, the optimization is formulated on a product manifold and solved using the Riemannian steepest descent algorithm via the Pymanopt toolbox. Three constellations are designed by this strategy, which are six-satellite constellation for the Lunar South Pole station, a twenty-satellite constellation for lunar surface and lunar orbit users, and an eight-satellite constellation for a LEO-to-DRO transfer trajectory. Simulation results demonstrate that the optimized designs achieve the required geometric visibility, maintain GDOP/PDOP below specified usable thresholds (e.g., max PDOP of 5.96 for the South Pole, max GDOP of 2.28 for the transfer), and exhibit stable autonomous navigation performance. The study confirms the feasibility of the proposed strategy for designing practical, high-performance navigation constellation deployments across diverse cislunar mission scenarios.
Chan, Meichen, Qiu, Haipeng, Hu, Jiaxin, Yang, Leping, Zhu, Yanwei, Chen, Yujie
Design and Optimization of an LQR-Based Multivariable Control System for an RBCC Engine2026-99-063211/6/2026
To achieve the key control objectives of thrust regulation and inlet protection for a rocket-based combined cycle (RBCC) engine under wide flight envelope, high-speed operating conditions, this study is based on a nonlinear component-level RBCC engine model developed in MATLAB/Simulink. A state space model is established using a least squares system identification method. By incorporating actuator dynamics, an augmented system model is formulated, and a Differential Evolution (DE) optimized Linear Quadratic Regulator (LQR) multivariable closed-loop control strategy is proposed. Simulation results show that the proposed strategy significantly improves both response speed and disturbance-rejection capability. Compared with the conventional LQR controller, the maximum oscillation of the inlet stability margin is reduced from 11% to 4.4%, and the thrust settling time is shortened by 83%. These results verify the feasibility of the proposed control method under complex operating conditions.
Zheng, Runtong, Han, Chongpeng, Xie, Zhenwei
Covariance-based Filtering and Smoothing Estimation under a Round-Robin Protocol2026-99-062711/6/2026
This paper focuses on recursive estimation for stochastic systems under the round-robin (RR) protocol. In recursive estimation, it is assumed that the state evolution process of the signal is unknown, and the relevant estimation research is only carried out relying on the mean and covariance functions of the process. To effectively avoid the occurrence of transmission channel conflicts and ensure the fairness of data allocation during transmission, this paper chooses to adopt the RR protocol to schedule and manage data communication. Specifically, this scheduling rule stipulates that only one sensor is allowed to acquire the network communication opportunity within a fixed time period, and the entire scheduling process is executed cyclically in a preset fixed order. Based on the observable information available in the system, this paper further designs and proposes a recursive estimation algorithm by means of the innovation method. Finally, a numerical simulation experiment is given to verify the effectiveness and feasibility of the proposed estimation algorithm.
Lin, Xiao, Li, Jiaxing, Du, Junhua, Wu, Meiyun
Impact of ESG Performance on Corporate Value in Low-Altitude Economy Enterprises2026-99-220911/6/2026
Low-altitude economy has already become an important strategic engine for high-quality development as a symbol of new productive forces. The impact of ESG performance on corporate value within the low-altitude economy (a strategic emerging industry), as well as its dual effects and situational specificities, is systematically and empirically examined in this paper using panel data from Chinese A-share listed companies from 2018 to 2023. The results show that the ESG performance of “low-altitude economy” enterprises has a significant impact on company value through two channels: investment in R&D and obtaining more government subsidies. Analyst coverage might be contradictory; too much analyst coverage may even counteract the advantage of ESG performance. Our results also reveal significant heterogeneity patterns. Value-enhancing effects of ESG are greater in low-pollution sectors, technology-based enterprises, non-State-owned companies, and companies located in central and western China. To foster sustainable, high-quality company business, this paper provides suggestions for implementing ESG and conceptually elaborates on how the low-altitude economy influences company ESG performance.
Lv, Xiaonuo, Chu, Yanchang
Multi-Dimensional Clustering with Multi-Weight Aggregation for Asynchronous Federated Learning in Low-Altitude Networks2026-99-221311/6/2026
Asynchronous federated learning (AFL) is essential for low-altitude networks due to its benefits in reducing communication bandwidth, lowering transmission delays, and preserving data privacy. However, the highly dynamic mobility of drones, combined with inherent heterogeneities in AFL, including variations in data volume, data distribution, and device capability, introduces severe challenges, such as inconsistent model update frequencies, biased local training, and inefficient global aggregation. Consequently, these issues lead to significant accuracy degradation and hinder practical deployment. In this paper, we propose a novel AFL framework tailored for low-altitude networks to address these challenges, which combines a multi-dimensional clustering mechanism with a multi-weight aggregation mechanism (MDC-MWA). To mitigate local model bias induced by data heterogeneity, the multi-dimensional clustering allows the cloud server to compute a comprehensive score for each drone based on multiple dimensions, including the label distribution, the gradient direction, and the local data proportion. It then employs K-Means clustering to partition drones into highly homogeneous subgroups, each managed by a dedicated roadside unit (RSU). Within each subgroup, after performing local updates, each drone synchronously uploads parameters to its RSU. Between these subgroups, to address inconsistent update frequencies caused by imbalanced computing capabilities, RSUs perform asynchronous training via the multi-weight aggregation mechanism, which updates the global model considering staleness weight and direction consistency weight. Experimental results demonstrate that the proposed method outperforms baseline approaches in highly heterogeneous scenarios, achieving a 4.74% absolute improvement in training accuracy on the CIFAR-10 dataset. This work provides a practical framework for distributed intelligent applications in dynamic and resource-constrained low-altitude networks.
Cai, Jiawei, Cui, Wei, Wen, Ying, Chen, Zhentao, Wu, Maoqiang
A Hierarchical Optimization Strategy for On-Orbit Energy Management and Attitude Control of Spacecraft2026-99-060511/6/2026
This paper addresses an energy-optimal attitude control strategy for space solar power satellites (SSPSs) during on-orbit energy transmission missions. The study focuses on a space solar power generation and energy transmission experimental satellite as the research object. First, the attitude dynamics of the satellite are modeled using the Lagrange method, and the satellite’s attitude control actuators, namely the single-gimbal control moment gyroscopes (SGCMGs), are also modeled to capture their dynamic behavior and constraints. Second, a PD controller based on quaternion and angular velocity error feedback is designed to achieve the desired attitude necessary for the energy transmission task. Subsequently, a hierarchical optimization approach is developed to obtain the energy-optimal attitude control strategy over one orbital period, considering multiple factors such as the satellite’s on-orbit energy consumption, the energy collection efficiency of the solar array in non-shadow regions, and the energy transmission efficiency between the satellite and the ground station. The optimization process is divided into two levels. In the first level, within the ground station’s visibility window, an energy balance analysis at different potential transmission moments is performed to determine the optimal transmission timing that maximizes the energy received by the ground station. In the second level, during the energy transmission phase, a cost function is formulated that incorporates pointing accuracy, pointing stability, and actuator energy consumption, and the controller parameters are globally optimized using the Adaptive Particle Swarm Optimization (APSO) algorithm. The simulation results demonstrate that the proposed hierarchical optimization method can significantly enhance the operational efficiency of on-orbit energy transmission, providing a practical engineering approach for the efficient on-orbit operation of future space solar power stations.
Wang, Ke, Zhang, Ning, Ma, Wenlai, Zhao, Yang
Rapid Thrust Evaluation of Solid Rocket Motor Nozzles Using Neural Network with Geometric Variations2026-99-061811/6/2026
To address the complexity of the influence of expansion-section geometry on the thrust performance of solid rocket motor nozzles and the low efficiency of numerical-simulation-based optimization, this study proposes a deep-learning-based method for rapid nozzle thrust prediction. With a representative 70-lb BATES nozzle as the research object, the expansion-section contour is parameterized using cubic spline functions. Combined with Latin hypercube sampling and two-dimensional inviscid numerical simulations, a nozzle geometry– thrust dataset covering a wide range of contour characteristics is constructed. On this basis, surrogate models based on a fully connected neural network, a one-dimensional convolutional neural network, and a two-dimensional convolutional neural network are developed, and the applicability of different network architectures to the nozzle thrust prediction task is systematically compared. The results demonstrate that convolutional neural networks outperform fully connected networks in terms of geometric feature representation capability and prediction stability. In particular, by explicitly modeling the spatial structural features of the nozzle contour, the two-dimensional convolutional model achieves a coefficient of determination close to unity on the test set, with an average relative error of 0.03%. Further hyperparameter sensitivity analysis clarifies the effects of batch size, number of training epochs, and learning rate on model convergence behavior and generalization performance. This work provides a feasible technical support for rapid thrust evaluation and efficient optimization-oriented nozzle design.
Yuan, Yuan, Wu, Wei-tao, Hua, Yue
Regenerative Braking Control Strategy for Electric Vehicle Based on Improved Ant Colony Algorithm2026-99-191911/6/2026
To address low energy recovery efficiency and inaccurate torque distribution of regenerative braking in electric vehicles, this paper proposes an optimized fuzzy control strategy for regenerative braking based on an improved ant colony algorithm. The design focuses on using the battery state of charge, real-time vehicle speed, and braking intensity as fuzzy control inputs, with the regenerative braking ratio as the output. By employing the improved ant colony algorithm to dynamically optimize the parameters of the fuzzy controller, the accuracy of electric motor braking force distribution is effectively improved; Building on this foundation, the introduction of the Elite Ant Guidance Algorithm enhances the speed of adaptive pheromone updates and dynamic path selection, thereby improving regenerative braking energy recovery efficiency. A MATLAB/Simulink simulation model was developed, and comparisons under the NEDC and UDDS test cycles demonstrated that, compared to traditional fuzzy control strategies, the optimized algorithm increases energy recovery efficiency by 12.8% and 8.1%, respectively, confirming the effectiveness and validity of the improved control strategy.
Yang, Zijiang, Zhang, Wei, Zhang, Jihong, Qi, Ye, Zhang, Zilei
Research on Load Distribution Methods for Planetary Gearboxes Based on Three-Dimensional Tolerance Analysis2026-99-190211/6/2026
Based on the Jacobian tensor and small displacement tensor theories, this paper establishes a three-dimensional tolerance chain analytical model for manufacturing and assembly errors in planetary gearboxes and proposes three methods for managing tolerance accumulation paths. Through tolerance analysis, the cumulative pitch error is quantified and incorporated into the nonlinear dynamic model of the planetary gearbox to determine the time-varying meshing force between the ring gear and planetary gear. This enables calculation of the theoretical load distribution coefficient while accounting for three-dimensional tolerance effects. To validate the model’s accuracy, a dedicated test bench was constructed, and dynamic stresses were measured using a root strain gauge array; the experimental load distribution coefficient was then derived. Comparison of simulation and experimental results shows that the deviation in the load distribution coefficient is only 7.4%, strongly confirming the reliability of the three-dimensional tolerance-dynamics coupled model. This study represents the first closed-loop verification from tolerance propagation to system-level load distribution, providing a theoretical foundation for tolerance design optimization and load distribution performance enhancement in high-precision planetary gearboxes.
Yu, He, Duan, Jiandong, Zhang, Jing, Shi, Wankai
XGBoost–Bayesian Optimization Method for Multi-Blade Centrifugal Fan2026-99-192111/6/2026
To overcome the trade-off between airflow rate and efficiency in a multi-blade centrifugal fan for automotive air-conditioning systems, as well as the low optimization efficiency of conventional simulation- or experiment-based approaches resulting from the large number of impeller design parameters, a surrogate-model-based optimization framework coupled with an intelligent optimization algorithm is proposed for impeller design. Latin hypercube sampling was employed to generate 120 samples within the design space, and an XGBoost model was integrated with a Bayesian optimization strategy to perform the optimization process. Validation results indicate that the prediction error of the surrogate model is less than 3%. Under the final optimized impeller configuration, the airflow rate is increased by 22% at the design operating condition, while the total pressure efficiency is improved by approximately 20%, satisfying the prescribed design requirements.
Yan, Yaqin, Yue, Chen
Modeling and Energy Consumption Characteristics Simulation Analysis of a Two-Speed Drive System for a Permanent Magnet Synchronous Motor2026-99-192711/6/2026
This study systematically analyzes the energy efficiency optimization requirements of the permanent magnet synchronous motor (PMSM) drive system for electric vehicles from three dimensions: motor topology, vector control algorithm, and two speed variable transmission mechanism. Firstly, analyze the electromagnetic structure of PMSM fixed rotor and compare the differences in magnetic circuit characteristics between surface mounted and built-in rotors, laying a theoretical basis for motor selection. Secondly, based on the id=0 control principle, a PMSM speed current dual closed-loop speed regulation architecture is built, and the PI regulator parameters are tuned according to the bandwidth characteristics of the current loop to ensure that the system has excellent dynamic response and speed following capabilities. Furthermore, key sub modules such as vehicle driving cycle, motor body, and two-speed transmission are integrated to construct a joint simulation environment. Evaluate the vehicle speed tracking accuracy and energy consumption level of the system under four typical operating conditions: NEDC, WLTC, CLTC-C, and CLTC-P, with a focus on revealing the mechanism of transmission ratio matching on the coverage range of the motor's high-efficiency zone. The core parameters of the simulation model in this article are calibrated based on the standard engineering parameters of mass-produced pure electric passenger vehicles and validated academic literature data. The model verification is completed by benchmarking the output results of existing mature simulation models to ensure the reliability of the simulation. Simulation data shows that the two speed transmission scheme significantly outperforms the single speed system in terms of energy consumption performance, and the optimal transmission ratio combination (8,5) can effectively broaden the high-efficiency working range of the motor, demonstrating optimal energy efficiency under WLTC and CLTC-P operating conditions. This study is mainly based on high fidelity simulation models for theoretical verification. Although bench tests have not been conducted, the model parameter calibration and verification process conforms to industry standards. The conclusion can provide theoretical reference and data support for parameter matching and energy-saving design of electric vehicle multi speed drive systems.
Liu, Chunhui
Determination Method of Engagement Position of SSS Clutch in NCB Steam Turbine and Analysis of Its Impact on Shaft System Vibration2026-99-190111/6/2026
An SSS clutch is incorporated into the shaft system of the NCB steam turbine in the gas-steam combined cycle unit. The benefit of this specific design is that the shaft system of the NCB steam turbine can disengage from and engage with the LP rotor during operation, enabling rapid and flexible adjustment between power generation output and heat supply. However, this mode of operation presents some special vibration issues in the shaft system. Analysis of the shaft vibration fluctuations that occur in NCB steam turbines before and after operating mode transitions indicates that this issue arises because the random engagement position of the SSS clutch induces changes in the shaft train’s balance and alignment conditions. Based on the measurement principle of shaft vibration phase and the dual keyphasor measurement system of NCB steam turbines, this paper proposes a novel methodology for determining the optimal engagement position of SSS clutches. This approach establishes quantitative correlations between shaft vibration characteristics and clutch engagement positioning, thereby enabling precise identification of the optimal engagement configuration. The research conclusions provide operational guidance for power plants to optimize shaft vibration in NCB steam turbines.
Song, Tongtong, Song, Yajun, Zhang, Wei, Si, Paiyou, Gao, Yibo
Design of a Gantry-Type Intelligent Grasping Device for Logistics Warehousing Based on MaixCam2026-99-192511/6/2026
Traditional warehousing suffers from low efficiency, high manual error rates, substantial labor costs, and complex deployment, while existing sorting devices remain poorly adaptable for small- and medium-sized operations. To address these issues, this paper presents an intelligent gantry-type grasping device for logistics warehousing based on the MaixCam. The device integrates mechanical design, computer vision, and electronic control. An Arduino Mega2560 serves as the main control board, with 57-series and 42-series stepper motors and servo motors driving the gantry and gripper. The mechanical structure adopts a miniaturized gantry architecture constructed from alloy steel, enabling operation in confined workspaces. A YOLOv5s model with transfer learning was trained for cargo box recognition using a dataset of 654 images collected under various lighting conditions and backgrounds. The model achieves a recognition accuracy of 93%–96% with inference times of 10–14 ms at 25–28 FPS. The proposed device provides a viable solution for automated sorting in small-to medium-sized warehouses, balancing recognition performance, power consumption, and cost.
Xiang, Chang’an, Zhou, Dan, Fan, Zhiwei
Study on Contact Stress Distribution at Curvic Couplings Fitting Surface under Pretightening Force2026-99-192411/6/2026
The curvic coupling configuration serves as a foundational element for the joining and torque transmission of aero-engine rotors. The uneven contact stress distribution at its fitting surface can cause tooth surface wear and failure, which in turn leads to the vibration of the entire engine. The curvic couplings are fixed by the pretightening force. The pretightening force greatly influences the contact stress distribution characteristics at the fitting surface. The influence of the pretightening sequence and times on the contact stress distribution characteristics under pretightening force is analyzed in this paper. To reduce the non-uniformity of the contact stress profile, a pretightening force correction model under different pretightening conditions was established. The impacts of the pretightening forces before and after correction on the homogeneity of the contact stress profile were compared. The results show that multi-time pretightening and an appropriate pretightening sequence improve the contact stress profile characteristics. Applying the corrected pretightening force significantly reduces the non-uniformity of the contact stress profile. Specifically, applying the corrected pretightening force multiple times in sequence is effective in further reducing the dispersion of contact stress distribution at the fitting surface. Pretightening in a diagonal sequence is more efficient in improving the homogeneity of contact stress. The research will contribute to precision manufacturing as well as the regulation of aero-engine rotor systems.
Liu, Enxiao, Zhang, Meng, Dong, Jiaxu, Li, Zhibin, Tong, Jinyu, Zheng, Jinde, Liu, Yongmeng
Noise Characterization and Root Cause Analysis of Valvetrain Noise Irregularities in a 1.2L Inline Three-Cylinder Engine2026-28-015811/5/2026
In recent years, global automotive manufacturers have been steadfastly engaged in the pursuit of advanced technical solutions to address the increasingly stringent noise pollution standards mandated by national and international regulatory authorities for their domestic and export markets respectively. Aligned with this overarching objective, the Engine Design and Development team at Maruti Suzuki India Limited (MSIL) has undertaken focused efforts to reduce powertrain-induced noise and vibration (NV). Recognizing that the engine unit’s principal static subsystems, namely the intake and exhaust assemblies and critical structural components such as the cylinder head (CH) and cylinder block (CB), serve as primary sources of acoustic emissions, special emphasis was placed on their refinement. Additionally, particular attention was directed toward the engine’s rotating and reciprocating components, especially the camshaft and crankshaft assemblies, to minimize overall measured sound pressure levels.
Singh, Amandeep, Singh, Jaspreet, Kumar, Narinder
A CI/CD-Integrated Digital Twin Framework for Scalable Validation of Automatic Transmission Application Software Using Platform-Based Architecture2026-28-018111/5/2026
Modern automatic transmission (AT) application software validation is predominantly dependent on Hardware-in-the-Loop (HiL) systems, resulting in significant time, cost, and scalability limitations within continuous integration/continuous deployment (CI/CD) workflows. These constraints intensify with increasing software complexity and the need to support multiple transmission variants across evolving hardware configurations. Existing validation approaches lack a scalable, software-centric surrogate capable of representing both control logic and physical system behaviour under real-time operating conditions. This study proposes a digital twin-based validation framework for AT application software, integrated within CI/CD pipelines. The framework restructures application software into a platform-based architecture enabling reuse across multiple transmission programs. A coupled plant model is developed to simulate drivetrain dynamics, ensuring system-level fidelity. The architecture also permits future data-driven augmentation for transient response correction and extended scenario coverage; however, the present study focuses on the baseline digital twin, hardware abstraction, and CI/CD validation workflow. A key contribution is the introduction of a hardware-adaptive abstraction layer, enabling the digital twin to accommodate variations in sensors, actuators, and control interfaces without full HiL dependency. Across 15 scenario hardware validation combinations, the reduced-order digital twin achieved a runtime gain of 1.20×–1.68× over the HiL proxy execution, with an average gain of approximately 1.46× and an average execution-time reduction of approximately 31% per validation case. The study demonstrates that integrating application software, plant models, and hardware-aware abstraction within a digital twin enables a transition from hardware-constrained validation to software-scalable paradigms. The framework provides a pathway toward efficient and adaptable validation in software-defined vehicle ecosystems. The proposed framework is aligned with ZF’s platform-based transmission software strategy, enabling reuse across multiple automatic transmission programs and supporting scalable validation of ZF powertrain control systems under evolving hardware configurations.
Gavara, Chandrakant, Sali, Rohan, Peddibhotla, Brahmaprakash, Wadkar, Swapnil P.
NV Enhancement of Automotive Powertrain through Hardware Refinement and ECU Parameters Optimization While Preserving Performance and Emissions Compliance2026-28-016311/5/2026
To comply with increasingly stringent emission norms and simultaneously enhance engine efficiency, durability, and power output, continuous improvements in engine performance have become essential for modern automotive engineering. However, these advancements often result in unintended consequences, particularly in the form of elevated noise and vibration (NV) levels, which negatively impact overall vehicle refinement and customer comfort. Managing NV without compromising performance has therefore emerged as a critical challenge in contemporary powertrain development. The study addresses the optimization of NV characteristics while maintaining engine functionality through a hybrid approach. This method combines transfer path of noise and vibration with a detailed evaluation of engine electronic control unit (ECU) parameters. By combining these analytical techniques, critical contributors to NV were identified, enabling the formulation of a targeted countermeasure strategy. Experimental validation was carried out on the engine intake system under controlled conditions to assess the effectiveness of proposed solutions. Results indicate that modifications to the intake system significantly reduce noise levels at the engine intake side, thereby improving acoustic comfort without adversely affecting combustion efficiency or power delivery. Furthermore, systematic optimization of ECU parameters contributed to smoother engine operation and reduced vibrational excitation across multiple operating points. The findings demonstrate that accurately targeting the appropriate engine subsystem and employing an integrated analytical-experimental framework can achieve balanced performance and acoustic refinement. This work highlights the effectiveness of integrated analytical and experimental methods for achieving balanced performance and acoustic refinement in advanced engines.
Singh, Karamdeep, Uniyal, Ravinder, Yadav, Manish, Mishra, Durga Prasad
Real-Time Exhaust Manifold Temperature Estimation Using Machine Learning–Based Virtual Sensors for Combustion Engines2026-28-019311/5/2026
Exhaust manifold temperature (EMT) plays a critical role in combustion control, engine performance, and thermal safeguarding of key hardware components in combustion engines. EMT is a primary power limiting constraint, as exceeding allowable temperature limits can lead to severe thermal damage to the exhaust manifold and turbine housing. Accurate estimation of EMT is therefore essential to ensure engine operation within allowable operating limits. EMT is typically measured using physical temperature sensors, which are prone to soot fouling, durability degradation, and calibration drift over time, while also increasing system cost and complexity. These limitations motivate the development of reliable virtual sensing approaches capable of replacing or augmenting physical EMT measurements. This work presents a machine learning–based virtual sensor for real-time estimation of exhaust manifold temperature, with a strong focus on production feasibility within resource constrained engine electronic control units (ECUs). Model development, training, and initial evaluation are conducted using data generated from a high-fidelity one-dimensional engine simulation environment that captures a wide range of steady state and transient operating conditions. The trained models are subsequently validated using engine measurement data to assess robustness and generalization under real world operating scenarios. Multiple lightweight supervised regression architectures are investigated to identify the best model that provides an effective balance between estimation accuracy and embedded implementation efficiency. Hardware implementation confirmed production feasibility, with the proposed EMT virtual sensor achieving deterministic real-time execution while requiring only 20% additional CPU utilization and 3.93ms worst-case execution time. The proposed framework establishes a feasible and scalable pathway for deploying machine learning–based EMT virtual sensors in engine controllers, enabling reduced reliance on physical exhaust manifold temperature sensors and supporting the transition toward intelligent, software defined combustion engine control systems.
Bayyavarapu, Chandu, Kamaraj, Keerthi Vallarasu, Mathur, Nilkumar, Gupta, Chirag, Prasad, Lakshmi, Arntz, David, Bergland, Nathaniel
Development and Validation of a Partially Scale-Resolving Three-Dimensional Computational Fluid Dynamics Model for Homogeneous Reactivity-Controlled Compression Ignition with Renewable Fuels03-19-06-002811/5/2026
Reactivity-controlled compression ignition (RCCI) is a promising combustion strategy for improving engine efficiency while reducing emissions. Within the framework of the dtec.bw MORE project, this study investigates an innovative homogeneous RCCI (hRCCI) combustion concept using port fuel injection of ethanol combined with early direct injection of octanol in a modified single-cylinder gasoline research engine. Although three-dimensional (3D) computational fluid dynamics (CFD) has been increasingly applied to low-temperature combustion (LTC) concepts, the use of partially scale-resolving approaches remains limited because of their higher computational cost and the resulting challenges for multi-cycle simulations in comparison to conventional Reynolds-averaged Navier–Stokes (RANS) simulations. To address this challenge, a CFD methodology in AVL FIRE M is developed that combines partially averaged Navier–Stokes (PANS) turbulence modeling with port and direct fuel injection, fuel-specific spray and evaporation behavior, wall-film formation and evaporation, and chemical kinetics. A novel reduced-species definition strategy is introduced to decrease the computational effort associated with chemistry and enable the application of the PANS approach over multiple engine cycles. After preconditioning cycles, nine consecutive cycles are simulated and analyzed to characterize combustion variability. The simulations reproduce the experimentally observed cylinder pressure and heat release rate trends with good agreement. The predicted cycle-to-cycle variations remain within the experimental minimum–maximum range and are tightly distributed around the experimentally observed mean cylinder pressure evolution. The predicted combustion duration agrees well with the experiments up to approximately 0–85% mass fraction burned. Beyond 85% burn, significant deviations occur, which are attributed to the increasing contribution of diffusion-controlled combustion and effects that are not fully captured by the present modeling framework. The results demonstrate that the proposed PANS-based methodology, together with the developed computational reduction strategy, enables computationally tractable multi-cycle 3D simulations while retaining the capability to resolve important flow–mixture–chemistry interactions. This study provides new insights into the combustion characteristics of dual-fuel hRCCI operation, while also demonstrating the influence of fuel injection parameters and identifying current modeling limitations. The proposed framework therefore provides a basis for further model development and combustion system optimization toward higher efficiency and reduced emissions.
Grundl, Larissa Michaela, Sundaram, Pravin Kumar, Tinschmann, Georg, Trapp, Christian
Oil Cooler Application Testing and NomenclatureJ1468_202611 (Current)11/4/2026
This SAE Recommended Practice is applicable to oil-to-air and oil-to-coolant oil coolers installed on mobile or stationary equipment and provides a glossary of oil cooler nomenclature. Such oil coolers may be used for the purpose of cooling automatic transmission fluid, hydraulic system oil, retarder system fluid, engine oil, etc. This document outlines the methods of procuring the test data to determine the operating characteristics of the oil cooling system and the interpretation of the results.
Cooling Systems Standards Committee
Prediction of Aero-Engine Exhaust Gas Temperature Using iTransformer2026-99-233510/30/2026
Exhaust gas temperature (EGT) is one of the key parameters for evaluating the thermal state of an aero-engine during flight operations. Precise EGT predictions are important in both managing engine health and optimizing performance. However, the nonlinear interactions among multiple operating parameters pose challenges for conventional prediction methods. An approach to EGT prediction presented in this paper is based on the iTransformer architecture. Unlike conventional time-series models that process temporal observations as tokens, this algorithm works with every single variable like a unique token and encodes the entire historical sequence of each variable. This design enables the model to capture inter-variable dependencies directly, thus increasing its power to capture multivariate time series. Two different datasets were used to validate the proposed approach and compared to various commonly used prediction models. The results indicate that iTransformer gives smaller prediction errors when the same conditions are met with MAE values of 0.5525°R and 0.4539K both on the two datasets. Despite the overall satisfactory performance, some prediction mismatches can be observed under extreme fast changing conditions of the engine operation. These results demonstrate that the proposed method can effectively characterize the complex interactions among engine variables and has potential for practical EGT prediction applications.
Hao, Mengfu, He, Yongbo, Li, Yifan
Study on Heat Transfer Characteristics of Supercritical Aviation Kerosene in a Rectangular Wavy Microchannel2026-99-234710/30/2026
In a conventional turbine-based combined cycle (TBCC) engine, the hot-end components and combustor wall surfaces bear extreme high- temperature thermal loads. To address this issue, researchers have been consistently exploring optimized cooling and heat transfer schemes. Relevant studies have shown that using aviation fuel as a heat sink can achieve effective thermal protection for such aero- engines. This paper carries out a numerical study on the flow and heat transfer characteristics of supercritical RP-3 aviation kerosene in a rectangular wavy microchannel, with a focus on the impacts of the wavelength-to-height ratio on heat transfer performance. The results show that the geometric structure of the wavy microchannel induces intense flow disturbances, which strengthen the internal energy exchange of the fluid and produce both longitudinal and transverse vortices. These vortices break and compress the thermal boundary layer, thus significantly enhancing the intensity of heat transfer. At the same time, the overall heat transfer performance is improved remarkably with relatively low resistance coefficients. Such excellent heat transfer characteristics can effectively mitigate thermal damage to high-temperature components, which is conducive to a notable improvement in their service life and operational safety.
Kou, Zhihai, Li, Xiangqiao, Wang, Xingbo
Research on an EPHM Methodology Based on Gas Path Performance Parameters2026-99-230510/30/2026
Gas path faults in aero-engines are a major factor affecting flight safety and maintenance costs. To achieve the transition from time-based maintenance to condition-based maintenance and enhance fault prediction and health management capabilities, this paper conducts research on intelligent diagnostic methods based on performance parameters for engine gas path components. Firstly, a component-level nonlinear steady-state model of a dual-spool turbofan engine is established, employing a variable specific heat capacity method to improve computational accuracy and provide a healthy baseline for diagnosis. Secondly, addressing the strong nonlinearity and measurement underdeterminacy in fault diagnosis, a diagnostic framework integrating a multi-population genetic algorithm and multi-operating-point analysis is proposed. The multi-population genetic algorithm effectively enhances global optimization capability and solution stability through parallel evolution, migration operators, and an elite population strategy; multi-operating-point data increases information content and strengthens fault isolation capability. Finally, simulation experiments under ground test conditions are conducted to validate the diagnosis of single-component faults in the low-pressure compressor, high-pressure compressor, high-pressure turbine, and low-pressure turbine. The results show that the proposed method can accurately invert component performance degradation, with a high fault identification accuracy rate, verifying the effectiveness of the proposed model and algorithm. This research provides a feasible technical solution for intelligent condition monitoring and precise diagnosis of aero-engines.
Cai, Na, Li, Ming, Li, BianJiang, Yu, GuangHui, Ma, ZhongYuan
Research on Fault Diagnosis of Civil Aircraft Engine Thrust Reverser Deployment Overspeed with Small Samples Based on Semi-Supervised Learning2026-99-231910/30/2026
Civil aircraft engine thrust reversers are easy to have overspeed faults when they are being deployed, therefore this condition is very important for flight safety and maintenance work efficiency. The low sampling frequency, about 1Hz, of onboard data recording systems, for example WQAR, together with external environment interferences such as sudden strong winds, therefore causes a quite large number of wrong and missed alarms in fault data. Therefore, the labeled data that can be obtained are not only few in number but also have low quality. In this article, a fault diagnosis framework which is based on semi-supervised learning is put forward to solve the problems of high labeling expenses and fault diagnosis under the condition of small samples. This framework makes use of a small amount of labeled data and a large amount of unlabeled data. It uses Semi-Supervised Support Vector Machines, Semi-Supervised Neural Networks, and Semi-Supervised Random Forests for dynamic self- training to realize classification of three kinds of states: “Normal State,” “Low-Speed Thrust Reverser Deployment Exceedance,” and “Medium-Speed Thrust Reverser Deployment Exceedance”. The experiment outcomes show that the Semi-Supervised Neural Network model which uses self-training method has the highest classification accuracy on the test set, achieving 94.8%. Further robustness analysis, such as label noise and feature noise disturbance experiments, indicates that this model displays the smallest performance lowering under noisy environments, hence it represents the best overall performance. This research gives an effective method for the diagnosis of engine thrust reverser function problems in an effective and strong way.
Yuan, Xiaojiang, Liu, Nan
Numerical Simulation and Geometric Parameter Optimization of Solid Propellant Single-Screw Extrusion2026-99-236010/30/2026
For the single-screw extrusion process of solid propellant, the geometric optimization of the homogenization section faces a core problem: the high coupling between pressure establishment, material transport and energy consumption, and it is difficult to achieve a balance between different performance indicators by traditional empirical methods. Therefore, a numerical optimization framework combining CFD simulation and genetic algorithm is constructed to systematically explore the optimal screw geometric configuration. Propellant slurries are regarded as non-Newtonian fluids and are described by the Arrhenius temperature-dependent Bird-Carreau model, on which the flow field, pressure field and temperature field are solved. The key geometric parameters such as outlet core diameter, pitch, front and rear wedge angle, and thread width are selected as the optimization variables, and the ratio of pump power to shaft power is used as the objective function of energy efficiency to measure the degree of mechanical energy conversion into effective pressure work, and thermal safety constraints are introduced to control the upper limit of propellant temperature. The optimization results show that compared with the initial configuration, the volume flow rate is increased by 123% and the energy efficiency is only slightly reduced under the premise of maintaining a stable pressure drop. The flow field analysis shows that the optimized structure enhances the resistance-led conveying capacity and effectively inhibits the backflow phenomenon. Further analysis shows that the design with a larger pitch and narrower thread can reduce energy consumption while increasing the output, but its pressure accumulation ability is significantly weakened, revealing the inherent trade-off between screw geometry and pressure generation, conveying efficiency and energy consumption. The resulting optimized configuration achieves a good balance between multiple properties, which provides a theoretical reference for the continuous extrusion process of high-performance solid propellants.
Tang, Zhuang, Jiang, Ye, Mei, Mei, Wu, Wei-Tao
Analysis of Dynamic Characteristics in the Tip Near-Stall Flow Field of a Transonic Axial Compressor Based on POD and DMD2026-99-236410/30/2026
Under the pre-stall condition of transonic axial compressors, intense unsteady flow within the tip clearance region acts as the primary mechanism initiating rotating stall and constraining the stable operating range of gas turbine engines. Conventional proper orthogonal decomposition (POD) alone only captures spatially coherent structures with optimal flow-field energy distribution, yet fails to directly characterize modal dynamic evolution and thus cannot fully uncover the inherent onset mechanism of compressor instability. Taking the NASA Rotor 67 transonic compressor rotor as the research object, this work obtains time-resolved unsteady flow-field data in the tip region near stall via high-fidelity numerical simulation. A combined POD and dynamic mode decomposition (DMD) framework is employed to synchronously extract spatial structural features and dynamic evolutionary laws of the flow field for instability mechanism analysis. Results demonstrate that the dominant POD mode corresponds to the tip secondary vortex induced by breakdown of tip leakage vortex, with a dominant frequency of 3495 Hz and its harmonics. DMD identifies a weakly growing dominant mode associated with the tip secondary vortex and a low-frequency mode linked to oscillations of the leakage vortex core; the mutual coupling constitutes the core trigger for flow-field instability.
Li, Wei
An Improved ResU-Net for Thermally Grown Oxide Layer Segmentation in Thermal Barrier Coatings2026-99-236110/30/2026
Thermal barrier coatings (TBCs) serve as the critical protective layer for gas turbine components. In complex service environments, the thermally grown oxide (TGO) layer formed between the top coat (TC) and the bond coat (BC), along with the evolution of its microscopic morphology, is a key factor determining the service life of TBCs. To address the complex morphology of TGO layers that challenges conventional segmentation methods, this paper proposes MSF-SA ResU-Net, a multi-scale feature fusion self-attention model based on the ResU-Net architecture, for the image segmentation of thermally grown oxide layers. Building upon residual connections, this model incorporates two key enhancement modules at the bottleneck layer: Multi-Scale Fusion (MSF) and Self-Attention (SA). During the feature processing stage, the MSF module effectively captures the multi-scale morphological features of the TGO layer through receptive fields of different sizes, solving the difficulty of extracting long-strip and irregular morphologies. Subsequently, the SA module recalibrates the fused features by calculating the global dependencies between them, enhancing the network's attention to TGO boundaries and micro-defects. Comprehensive experiments on an in-house dataset of 3,000 SEM images demonstrate that MSF-SA ResU-Net outperforms standard U-Net and contemporary segmentation architectures. Furthermore, due to the feature extraction capability of the ResNet backbone network, the model maintains high accuracy and exhibiting good convergence performance. This makes the architecture an effective solution for the microscopic analysis of thermal barrier coatings.
She, Weicen, Song, Yan
Research on the Identification Method of Flow Modes during the Hypersonic Inlet Unstart/Restart Process2026-99-236810/30/2026
In air-breathing hypersonic flight, when the flow conditions upstream and downstream are not appropriate, the air inlet is prone to failure to start, which can lead to engine stall or even flight failure. Therefore, real-time identification methods for air inlet flow modes must be developed. This paper takes the hypersonic inlet as the research object. In the wind tunnel experiment, the switching of the inlet unstarting/restarting was achieved by changing the Angle of attack, and the shadow images during the mode switching process and the pressure signals of multiple wall measurement points were obtained. The study shows that the traditional modal recognition method based on pressure amplitude, standard deviation, and power spectrum has a weak ability to recognize the starting/unstarting flow modes of the inlet in this paper. For this purpose, this paper proposes a flow mode recognition method based on pressure difference and standard deviation, which can achieve good recognition ability for each measurement point and has strong applicability. In addition, the method identifies the unstart point and the restart point separately instead of using a single detection threshold for judgment, significantly improving the accuracy of flow mode identification.
Si, Jinglin, Pi, Cuixuan, Xu, Shangcheng, Wang, Yunlong
Low-Cost and Low-Energy Pathways between Periodic Orbit Families in the CR3BP Earth-Moon System2026-99-235110/30/2026
The renewed global interest in cislunar space with potential breakthrough applications including Artemis & Gateway, Moon Village, Chang’e In-Situ Resource Utilization and lunar base & habitat construction justifies that there is a critical need for numerically robust and computationally efficient trajectory design framework. Several existing optimization methods in CR3BP system like Multiple Shooting, Invariant Manifolds, Sequential Quadratic Programming exists but in isolation, leaving a gap for integrating these techniques to a combined framework. This research addresses this gap by furnishing a complete modular framework that combines multiple shooting method with transcription for discretization, monodromy matrix-based approach for generating optimal pathways with linear interpolation technique for generating initial good guess for the transfer path. This work simultaneously optimizes the transfer trajectory on libration orbits eliminating priori phase selection. This method used SQP solver to accurately optimize minimum Δv with optimum time of flight transfers with novelty in flexibility to select departure and arrival points on orbit along with the inclusion of departure and arrival phase freedom. Results are validated by establishing benchmark cases with published data indicating this work achieves accuracy and numerical robustness. This work directly supports the robust design of low-cost missions for crewed, cargo and supply chain of future sustainable cislunar infrastructure.
Muhammad, Arsalan
Investigation on the Aerodynamic Characteristics of Nacelle Inlet Coupled with Fan Rotation Effect2026-99-235010/30/2026
As key aerodynamic components of an aircraft propulsion system, the design quality of the inlet and nacelle directly affects engine intake quality and overall aircraft stability. Nacelle design is trending towards greater compactness, making the coupling and matching between the inlet and fan increasingly critical. To investigate the mechanism by which fan rotation influences inlet aerodynamic performance, this study takes the NASA ROTOR 67 fan model as the research object and couples it with a specific civil aircraft nacelle model to conduct research on the effect of fan rotation on inlet performance. Through computational analysis of the flow field characteristics and aerodynamic performance of the inlet before and after coupling under cruise, high-angle-of-attack climb, and crosswind conditions, the results show that under cruise conditions, the inlet performance with and without the coupled fan is essentially consistent. Under high-angle-of-attack climb and crosswind conditions, the fan suction effect effectively mitigates open separation on the wall, disrupts the secondary flow vortices, and improves the exit flow field quality. After coupling with the fan, the total pressure recovery coefficient at the AIP plane shows significant improvement under both high-angle-of-attack and crosswind conditions. Fan rotation demonstrates a notable flow rectification effect under adverse inlet conditions, effectively enhancing inlet aerodynamic performance.
Yang, Fei, Zhao, Qiang, He, Bihai, Yan, Yan, Zhou, Leisheng
Layout Design and Verification of Deployable Radiators for Large-Scale Phased Array Antennas on High-Orbit Satellites2026-99-235410/30/2026
Active phased array antennas are widely deployed on various spacecraft platforms. As the demand for higher communication and data transmission capacity of spacecraft continues to grow, active phased array antennas have become increasingly large in scale, leading to a sharp rise in overall heat generation. Traditional thermal control schemes, which transfer heat to the satellite main structure via heat pipes, can no longer satisfy the heat dissipation requirements of large- scale array structures. To address the aforementioned technical bottlenecks, this paper proposes a layout design of deployable thermal radiators applicable to large phased array antennas for high-orbit communication satellites. Corresponding ground tests and on-orbit flight verifications are completed in this study. This work provides a feasible technical approach for realizing high-efficiency heat dissipation of large-scale space-borne phased array antennas operating in high-orbit environments.
Wu, Ruilan, Zou, Hengguang, Liu, Chang, Zhao, Feng, Wang, Ming, Lv, Lucang, Liu, Kun, Xing, Boyan
Numerical Diagnosis and Evidence-Chain Analysis of the Non-Sustained Ignition Process in a Hydrogen/Air Turbulent Diffusion Flame under an LES–PaSR Framework2026-99-232410/30/2026
This paper addresses non-sustained ignition in numerical simulations of hydrogen/air turbulent diffusion flames. A reproducible LES-PaSR case study was constructed on the OpenFOAM platform, and a box-shaped ignition core was applied using setFields. The work is positioned as a numerical diagnostic and benchmark workflow, not as an experimentally validated prediction of a stable flame. The evidence chain, consisting of three diagnostic indicators - the domain-wide maximum temperature, centerline statistics along the ignition axis, and slices at critical moments - tracks the complete ignition-peak decay process. Calculations show that the domain-wide maximum temperature (Tmax) reaches a peak of 2852.5 K at t = 3.13×10^–4 s and then rapidly drops to 956.4 K at t = 0.0015 s. The duration of Tmax ≥ 2000 K is 0.818 ms, while Tmax ≥ 1000 K lasts for 1.388 ms. Comparison between the centerline and cross-sections further indicates that the high-temperature OH reaction zone is mainly limited to the ignition core and its downstream neighboring region. Under the combined effects of convective transport and turbulent mixing, this region rapidly cools and dissipates, failing to form a stable self-sustained exothermic structure. Finally, three physically plausible explanatory pathways and corresponding sensitivity-case designs are proposed, providing a practical basis for subsequent parameter scanning, mechanism replacement, and future comparison with experimental or literature-reported data. A supplementary sensitivity case with the ignition-kernel temperature increased from 2200 K to 2400 K exhibits a higher peak temperature and delayed threshold crossings, yet the reacting structure remains non-sustained within the simulated time window. Tmax ≥ 2000KTmax ≥ 1000K
Liu, Jiaqi, He, Jiandong, Yuan, Youquan, Duan, Yu
Contact Mechanics and Release Dynamics Analysis of the Test Mass2026-99-233210/30/2026
The test mass is a cube made of a gold-platinum alloy that serves as the inertial reference for space-borne gravitational wave detection; its final residual velocity after locking and release must not exceed 5 μm/s. During the release process, multi-degree-of-freedom disturbances caused by the pull-off effect between the release mechanism and the test mass are the key factors affecting the residual velocity of the test mass. This paper focuses on the designed release mechanism to conduct research on the interaction relationship between it and the test mass. Three contact configurations are proposed, and corresponding contact mechanics models are established to analyze the impact of release on test mass disturbances under plunger offset and deflection, leading to the selection of the optimal configuration. Based on adhesion effects, a one-dimensional impulse transfer model and Lagrange dynamic equations are constructed to analyze the disturbance transfer mechanism during the release process. Minimal release impulse is achieved through systematic parameter optimization. It is concluded that the plunger-sphere/test-mass-plane configuration is optimal for disturbance decoupling and technical feasibility, with an optimized plunger radius of 10 mm and mass of 0.8 g, which significantly reduces adhesion and residual preload. Furthermore, simulation verification demonstrates that the residual velocity of the test mass after release is on the order of 10^–7 m/s, satisfying the low-disturbance requirements. The aforementioned conclusions provide significant theoretical support and design references for enhancing the release success rate of test mass release mechanisms and reducing release residual velocity.
Kang, Mingdi, Si, Jixing, Ouyang, Junyong, Lu, Yifan, Yue, Honghao, Yang, Fei
Permutation Test as a Novel Robust Statistical Approach for Gauging a Change in the Rate of Stochastic Preignition03-19-06-002710/23/2026
Multiple statistical methods were evaluated to determine the most suitable approach to gauge whether a gasoline deposit control additive (DCA) causes a statistically significant increase in rate of stochastic preignition (SPI) in a direct injection, turbocharged, spark ignition (SI) engine. SPI is an abnormal combustion phenomenon observed at highly boosted conditions in turbocharged SI engines. The high in-cylinder pressures observed during an SPI event have the potential to cause physical damage to the engine. The SPI rate is a function of engine operating conditions as well as fuel and oil properties. DCAs are commonly used in commercial gasoline at very low concentrations (20–200 ppm m/m) to prevent the buildup of carbon deposits in the combustion chambers and fuel systems. Since the effect of DCAs on SPI rate can be subtle and the data inherently stochastic, a controlled engine test methodology with robust statistical analysis is required to conclusively determine whether a gasoline detergent increases or mitigates the rate of SPI occurrence. Therefore, the TOP TIER™ Standardized Dynamometer Test Method to Evaluate Additized Detergent Gasoline for Stochastic Pre-Ignition (hereafter referred to as the TOP TIER™ Additive SPI Test Protocol) described herein is designed to gauge whether a gasoline additive causes a statistically significant change in the SPI rate at a controlled operating condition as compared to unadditized gasoline. This study focuses on the statistical analysis portion of the test protocol. Multiple statistical approaches were evaluated using data from the TOP TIER™ Additive SPI Test Protocol to determine the most appropriate and robust approach for detecting a statistically significant difference in SPI rates. The analysis included the two-sample (unpaired) t-test, linear mixed-effects models (LMMs), the Mann–Whitney U test, and the permutation test. The results indicated a combination of permutation paired with Wilkinson’s method as the most suitable approach.
Gopujkar, Siddharth, Davis, Richard, Zhang, Kui, Reilly, Veronica, Studzinski, William
Evaluation of Worst-Case and Mitigation of Pass-By Noise for Commercial Passenger Vehicle under Indian Standard 3028:2023 with Low-Cost Instrumentation2026-01-507110/23/2026
Stringent environmental noise regulations in India, specifically the transition to IS 3028:2023 (Part 2), have established revised pass-by noise (PBN) limits for commercial vehicles ranging from 74 dB(A) to 75 dB(A) based on gross vehicle weight (GVW) and engine power. Unlike passenger cars, heavy commercial vehicles (HCVs) are primarily driven by diesel engines where powertrain-induced vibration and cooling fan engagement significantly impact exterior noise levels. This study investigates the “worst-case” configuration within a commercial fleet, typically characterized by high gear ratios or unladen drive-away chassis that experience high acceleration rates. To solve this challenge in a cost-effective manner, a practical and low-cost approach was taken in this study: Smart Shielding Instead of Vehicle Hardware Changes: Instead of expensive engine/transmission or axle redesigns, simple noise shields were added having sufficient noise absorption capabilities made of basic sound-absorbing foam. By placing these “acoustic blankets” below or around the gearbox, engine block, or wheel arch, the noise was blocked at the source before it could reach the test microphones. The “Tape and Foam” Strategy: A simple method called masking was used in this study. By temporarily covering parts of the vehicle with a sound-absorbing shield one by one, it could be pinpointed exactly which part was the loudest—like a noisy intake or a vibrating exhaust—without needing costlier lab equipment. Economical Testing: High-end sensors were swapped with standard handheld sound-level meters and basic global positioning system (GPS) units to track speed and revolutions per minute (RPM) of the engine. Simplified instrumentation and software were used to analyze the frequency pattern generated during the test and thereby reduce the noise from affected components. Otherwise, costlier radar-based instrumentation is required for the evaluation of this revised PBN testing. Many test iterations have been performed on the test track to find the best shield placement before going for the final, official certification. Worst-Case Identification: To arrive at the worst-case vehicle, multiple vehicles having different lengths and drivelines were tested. The worst case was identified as having the maximum noise contribution during the testing for analysis. This paper emphasizes simplified techniques to bring noise to the specified limit values as per the revised noise standard.
Gupta, Mohit
Properties of Oxymethylene Ethers with Different Terminal Groups: A Mini-Review04-19-03-001610/21/2026
Methyl-terminated oxymethylene ethers (OMEs) have garnered significant attention as promising low-carbon alternatives to conventional petroleum-based diesel fuels. Nevertheless, their physicochemical properties frequently fail to satisfy the stringent specifications of current diesel fuel standards, which impedes their direct adoption in modern compression ignition engines. Structural modification of OMEs, particularly through the variation of terminal alkyl moieties, provides a viable strategy for tuning their properties to meet the required performance criteria. This review consolidates and critically evaluates the available literature on the physicochemical and performance characteristics of OMEs featuring diverse molecular architectures. In addition, it delineates existing knowledge gaps and identifies key areas warranting more in-depth future research. The number of published studies in this area is extremely limited, as research in this field is still essentially at an early stage; therefore, the present review has been classified as a mini-review.
Cherepanova, Anna D., Ukhanov, Denis A., Khrapov, Alexander G., Dement’ev, Konstantin I.
Methods and Devices for Measuring the Waveform of Large Friction Forces and Energy between the Bodies and Needles of Injector Nozzles of Marine Piston Combustion Engines04-19-03-001410/21/2026
In marine combustion engines, it is important to minimize fuel consumption and reduce toxic emissions. One method to achieve this is minimizing friction losses in the injection subsystem, which is why measuring them is necessary. Some friction force values in precision pairs are so high that they require specialized methods and measurement stations. This article presents innovative methods and devices for measuring high friction and high power forces between the body and the needle of injector nozzles in the presence of a lubricant. The scientific method consists of increasing the load applied to the needle pin located in the nozzle body until it is completely ejected from the body. The devices that determine the course and maximum value of the friction force utilize test benches for dynamic tensile strength testing samples, employing specially designed and manufactured holders. When the fastening of the pin holder proved insufficient due to slippage, a semicircular groove was made around the circumferential needle pin. Round balls were inserted into the pin’s innovative mounting screw holes, recessed into the circumferential groove by about half their diameter, which is an important contribution by the authors. The maximum friction force was determined from the recorded signal, depending on the displacement or time waveform. The friction force depends on the needle’s position relative to the nozzle body; therefore, it is recommended to take measurements in at least four planes and compute the average. Different friction force values are caused by errors in the roundness and concentricity of the injector nozzle body guide part relative to the needle, as well as deposit formation. This article presents the influence of the state of the friction surfaces, as determined by modern geometric measurements of the cooperating elements, including computed tomography scans and silicone casts, on the maximum friction force value and modeling.
Monieta, Jan, Komorowski, Adam
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
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
Coking Inhibition Characteristics of Dimethyl Disulfide during Supercritical Pyrolysis of n-Decane2026-99-299310/19/2026
Inhibition of coking from pyrolysis of hydrocarbon fuel is critical for ensuring the safe operation of high-speed aircraft. In this work, the inhibitory effects of dimethyl disulfide (DMDS) on coke during the supercritical pyrolysis of n-decane were investigated. Experiments using an electrically heated micro-reactor tube were conducted to study the influences of presulfidation and cofeeding methods with varying DMDS concentrations. The pyrolysis products were analyzed via gas chromatography, while pressure drop and coke mass were measured. The composition and morphology of coke were further characterized by energy-dispersive spectroscopy and scanning electron microscopy. The results show that the influence of DMDS on coke formation depends on its application method and concentration. At a DMDS concentration of 500 ppm, the coke inhibition rate reached 85.5% with presulfidation and 81.7% with cofeeding. However, with increasing DMDS concentration beyond 500 ppm, the amount of coke formation increases. Coke formation during supercritical pyrolysis of n-decane primarily involves metal-catalyzed coking and bulk-phase coking processes. The H2S and HS radicals generated from pyrolysis of DMDS react with transition metals such as Fe and Ni, thereby inhibiting the formation of metal-catalyzed filamentous coke. The presulfidation process forms a sulfide layer earlier than the cofeeding process, more effectively suppressing the generation of filamentous coke. However, excessively high DMDS concentrations can lead to its decomposition into sulfur-containing radicals such as thiol radicals (CH3S·), which incorporate into the coke matrix, enhance its reactivity, and promote coke formation. This work offers valuable insights for the application of DMDS as a coke inhibitor in endothermic hydrocarbon fuels.
Liao, Yan, Yao, Yixuan, Yang, Can, Huang, Qin, Chen, Yu
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
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
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
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
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
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
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