Search Results (70)

The Survey Camera (SC) is the key instrument of the China Space Station Telescope (CSST), with its imaging performance significantly constrained by microvibrations from internal sources such as the shutter and cryocoolers. This paper proposes a systematic microvibration suppression scheme integrating disturbance source control, payload isolation, and transfer path optimization to meet the stringent requirements. The Cryocooler Assembly (CCA) compressor adopts a symmetric piston layout and a real-time vibration cancellation algorithm to reduce the vibration. Coupled with a vibration isolator designed by combining hydraulic damping and a flexible structure, it achieves a vibration isolation efficiency of 95%. The shutter adopts dual-blade symmetric design with sinusoidal angular acceleration control, ensuring its vibrations fall within the compensable range of the Fast Steering Mirror (FSM). And the finite element optimization method is used to optimize the dynamic characteristics of the Support Structure (SST) made of M55J carbon fiber composite material, to avoid resonance in the critical frequency bands. System-level tests on the integrated SC show that the RMS values of vibration force and torque within 8–300 Hz are 0.25 N and 0.08 N·m, respectively, meeting design specifications. This scheme validates effective microvibration control, guaranteeing the SC’s high-resolution imaging capability for the CSST mission. Full article

This paper presents an adaptive reinforcement learning (RL)-based control strategy for a wireless power transfer (WPT)-fed brushless DC (BLDC) motor drive, aimed at enhancing efficiency in industrial applications. Conventional control methods for BLDC motors often result in higher energy consumption and increased torque ripple under dynamic load and voltage variations. To address this, an adaptive RL framework is implemented with pulse density modulation (PDM), enabling the controller to augment motor speed, torque, and input power in real time. The system is modeled and tested for a 48 V, 1 HP BLDC motor, powered through a 1.1 kW WPT system. Training is carried out across 10 learning episodes with varying load torque and speed demands, allowing the RL agent to adaptively minimize losses while maintaining performance. Results indicate a significant reduction in torque ripple to a minimum of 0.20 Nm, stable speed regulation within ±30 rpm, and improved power utilization compared to existing controllers. The integration of RL with WPT provides a robust, contactless, and energy-efficient solution that is suitable for sustainable industrial motor-pump applications. Full article

In the realm of sustainable public transportation, the integration of intelligent electric bus propulsion systems represents a novel and promising approach to reducing environmental impact—particularly through the mitigation of NOx emissions and overall exhaust pollutants. This emerging technology underscores the growing need for advanced drive control architectures that ensure not only operational safety and reliability but also compliance with increasingly stringent emissions standards. The present article introduces an innovative analysis of energy-optimized dual-drive electric propulsion systems, with a specific focus on their potential for real-world application in emission-conscious urban mobility. A detailed dynamic model of a dual-drive electric bus was developed in MATLAB Simulink, incorporating a Fuzzy Logic-based decision-making algorithm embedded within the Transmission Control Unit (TCU). The proposed control architecture includes a torque-limiting safety strategy designed to prevent motor overspeed conditions, thereby enhancing both efficiency and mechanical integrity. Furthermore, the system architecture enables supervisory override of the Fuzzy Inference System (FIS) during critical scenarios, such as gear-shifting transitions, allowing adaptive control refinement. The study addresses the unique control and coordination challenges inherent in dual-drive systems, particularly in relation to optimizing gear selection for reduced energy consumption and emissions. Key areas of investigation include maximizing efficiency along the motor torque–speed characteristic, maintaining vehicular dynamic stability, and minimizing thermally induced performance degradation. The thermal modeling approach is grounded in integral formulations capturing major loss contributors including copper, iron, and mechanical losses while also evaluating convective heat transfer mechanisms to improve cooling effectiveness. These insights confirm that advanced thermal management is not only vital for performance optimization but also plays a central role in supporting long-term strategies for emission reduction and clean, efficient public transportation. Full article

This study investigates the role of toroidal vortex formation in torque-flow pumps and its influence on pump performance. A mathematical model of viscous fluid motion in toroidal coordinates was developed to describe the two-stage energy transfer mechanism, in which the impeller drives the toroidal vortex and the vortex subsequently imparts momentum to the main throughflow. The model identifies vortex deformation as a primary source of hydraulic losses. The theoretical framework was validated by computational fluid dynamics (CFD) simulations of a torque-flow pump. Analysis of the axial, circumferential, and vertical velocity components revealed a closed three-dimensional toroidal circulation loop within the free chamber, confirming the predictions of the mathematical model. A parametric study was conducted to assess the influence of impeller extension into the free chamber (Δb₂) on pump performance. Three characteristic regimes were identified. At Δb₂ ≈ 6 mm, the shaft power decreased to 120.3 kW (an 8.1% decrease compared to the baseline), with efficiency improving to 39.2%. At Δb₂ ≈ 10 mm, the pump achieved its best balance of parameters: efficiency increased from 34.0% to 42.8% (+8.7 percentage points), while head rose from 32.8 m to 38.5 m (+17.4%), with moderate power demand (122.3 kW). At Δb₂ ≈ 70 mm, the head reached 45.6 m (+39%), but power consumption rose to 146.9 kW (+12%), and the design shifted toward centrifugal-type operation, reducing reliability for abrasive fluids. Overall, the results provide both a validated mathematical description of toroidal vortex dynamics and practical guidelines for optimizing torque-flow pump design, with Δb₂ ≈ 10 mm identified as the most rational configuration. Full article

This paper presents a robust and computationally efficient fault classification framework for wind energy conversion systems (WECS), built upon a Robust Random Vector Functional Link Network (Robust-RVFLN) and validated through real-time simulations on a Real-Time Digital Simulator (RTDS). Unlike existing studies that depend on high-dimensional feature extraction or purely data-driven deep learning models, our approach leverages a compact set of five statistically significant and physically interpretable features derived from rotor torque, phase current, DC-link voltage, and dq-axis current components. This reduced feature set ensures both high discriminative power and low computational overhead, enabling effective deployment in resource-constrained edge devices and large-scale wind farms. A synthesized dataset representing seven representative fault scenarios—including converter, generator, gearbox, and grid faults—was employed to evaluate the model. Comparative analysis shows that the Robust-RVFLN consistently outperforms conventional classifiers (SVM, ELM) and deep models (CNN, LSTM), delivering accuracy rates of up to 99.85% for grid-side line-to-ground faults and 99.81% for generator faults. Beyond accuracy, evaluation metrics such as precision, recall, and F1-score further validate its robustness under transient operating conditions. By uniting interpretability, scalability, and real-time performance, the proposed framework addresses critical challenges in condition monitoring and predictive maintenance, offering a practical and transferable solution for next-generation renewable energy infrastructures. Full article

Horizontal wells in shale formations, such as those in the South Pars gas field (Iran) and the Bakken shale (Canada/USA), are essential for production from ultralow-permeability reservoirs but remain limited by poor hole cleaning, high torque, and unstable fluid transport. This study integrates real-time field data from South Pars with Drillbench simulations in the Bakken to develop practical strategies for improving drilling efficiency. A water-based mud system (9–10.2 ppg, 29–35 cP) supplemented with 2 wt.% sulphonated asphalt was applied to mitigate shale hydration, enhance cuttings transport, and preserve near-wellbore injectivity. Field implementation in South Pars demonstrated that adjusting drillstring rotation to 90 RPM and circulation rates to 1100 GPM reduced torque by ~70% (24 to 7 klbf·ft) and increased the rate of penetration (ROP) by ~25% (8 to 10 m/h) across a 230 m interval. Simulations in the Bakken confirmed these improvements, showing consistent torque and pressure trends, with cuttings transport efficiency above 95%. Inducing controlled synchronous whirl further improved sweep efficiency by ~15% and stabilized annular velocities at 0.7 m/s. Overall, these optimizations enhanced drilling efficiency by up to 25%, reduced operational risks, and created better well conditions for field development and EOR applications. The results provide clear, transferable guidelines for designing and drilling shale wells that balance immediate operational gains with long-term reservoir recovery. Full article

One of the key issues in vehicle sustainability is their energy efficiency. The article concerns the complex issue of predicting the tractive efficiency of heavy off-road vehicles depending on the parameters of the transfer case. As part of the research, a mathematical model of an off-road truck with simplified drive system was developed and implemented in MATLAB/Simulink environment. Multiple simulations for various parameters were performed. Based on the simulation results, efficiency maps were plotted depending on parameters such as the friction coefficient in the differential mechanism, torque bias of the differential, load distribution and drawbar pull of the vehicle. The results showed that the vehicle generally achieves the highest traction efficiency with the differential operating in locked condition and confirmed that the optimal torque bias is close to the load ratio. However, taking into account the multipass effect shifts this value towards the front wheel, while taking into account the bulldozing effect shifts it towards the rear wheel. Simulated vehicle showed higher efficiency when heavily loaded at higher differential friction, while when lightly loaded, higher efficiency at lower friction. Thanks to its high degree of parameterization, this model can be used to help optimize the drive train of off-road vehicles traveling in various terrains from the energy consumption point of view, leading to more sustainable operation. Full article

This study addresses a documented gap in detailed, cost-effective, and performance-validated electric vehicle (EV) powertrain solutions. It presents the complete design, construction, and simulation-based validation of a high-efficiency electric powertrain for a Shell Eco-marathon Urban Concept vehicle. Novel contributions of this work include a unique drivetrain architecture: a BLDC motor with a modular two-stage chain drive and a custom lithium-ion battery pack. The design is optimized for compactness and reliability under stringent budget and packaging constraints. A comprehensive Simulink-based vehicle dynamics model was developed for robust validation. This model enabled the estimation of energy consumption, torque profiles, and battery State of Charge under realistic drive cycles. The system demonstrated a remarkably low energy consumption under competition conditions, signifying high efficiency with <50 Wh/km consumption and full compliance with technical regulations. Furthermore, the hardware is thoroughly documented with detailed build instructions, CAD models, and a full bill of materials. This promotes reproducibility. This research offers a validated, low-cost, and replicable electric powertrain. It provides a transferable framework for future Shell Eco-marathon teams and advances lightweight, cost-effective solutions for real-world low-speed electric mobility applications, such as micro-EVs and urban delivery vehicles. Full article

During machining, most of the mechanical energy is converted into heat. A substantial part of this heat is transferred to the cutting tool, causing a rapid rise in tool temperature. Excessive thermal loads accelerate tool wear and lead to displacement of the tool center point, reducing machining accuracy and workpiece quality. This challenge is particularly pronounced when machining titanium alloys. Due to their low thermal conductivity, titanium alloys impose significantly higher thermal loads on the cutting tool compared to conventional carbon steels, making the process more difficult. To reduce temperatures in the cutting zone, cutting fluids are widely employed in titanium machining. They have been shown to significantly extend tool life. Cutting fluids are broadly categorized into cutting oils and water-based cutting fluids. Owing to their distinct thermophysical properties, these fluids exhibit notably different cooling and lubrication performance. However, current research lacks comprehensive cross-comparative studies of different cutting fluid types, which hinders the selection of optimal cutting fluids for process optimization. This study examines the influence of three cutting fluids—emulsion, cutting oil, and synthetic oil-free fluid—on tool wear, temperature, surface quality, and energy consumption during flood-cooled end milling of Ti-6Al-4V. A novel experimental setup incorporating embedded thermocouples enabled real-time temperature measurement near the cutting edge. Tool wear, torque, and surface roughness were recorded over defined feed lengths. Among the tested fluids, emulsion achieved the best balance of cooling and lubrication, resulting in the longest tool life with a feed travel path of 12.21 m. This corresponds to an increase of approximately 200% compared to cutting oil and oil-free fluid. Cutting oil offered superior lubrication but limited cooling capacity, resulting in localized thermal damage and edge chipping. Water-based cutting fluids reduced tool temperatures by over 300 °C compared to dry cutting but, in some cases, increased notch wear due to higher mechanical stress at the entry point. Power consumption analysis revealed that the cutting fluid supply system accounted for 60–70% of total energy use, particularly with high-viscosity fluids like cutting oil. Complementary thermal and CFD simulations were used to quantify heat partitioning and convective cooling efficiency. The results showed that water-based fluids achieved heat transfer coefficients up to 175 kW/m²·K, more than ten times higher than those of cutting oil. These findings emphasize the importance of selecting suitable cutting fluids and optimizing their supply to enhance tool performance and energy efficiency in Ti-6Al-4V machining. Full article

Permanent magnetic couplings provide critical advantages for deep-sea systems through static-sealed, contactless power transmission. However, conventional metallic isolation sleeves incur significant eddy current losses, limiting efficiency and high-speed operation. Limited torque capacities fail to meet the operational demands of harsh marine environments. This study presents a novel permanent magnet coupling featuring a ceramic isolation sleeve engineered for deep-sea cryogenic ammonia submersible pumps. The ceramic sleeve eliminates eddy current losses and provides exceptional corrosion resistance in acidic/alkaline environments. To withstand 3.5 MPa hydrostatic pressure, a 6-mm-thick sleeve necessitates a 10 mm operational air gap, challenging magnetic circuit efficiency. To address this limitation, an improved 3D magnetic equivalent circuit (MEC) model was developed that explicitly accounts for flux leakage and axial end-effects, enabling the accurate characterization of large air gap fields. Leveraging this model, a Taguchi method-based optimization framework was implemented by balancing key parameters to maximize the torque density. This co-design strategy achieved a 21% increase in torque density, enabling higher torque transfer per unit volume. Experimental validation demonstrated a maximum torque of 920 Nm, with stable performance under simulated deep-sea conditions. This design establishes a new paradigm for high-power leak-free transmission in corrosive, high-pressure marine environments, advancing applications from deep-sea propulsion to offshore energy systems. Full article

This paper presents a novel transposed MRAM architecture (WinEdge) specifically optimized for Winograd convolution acceleration in edge computing devices. Leveraging Magnetic Tunnel Junctions (MTJs) with Spin Hall Effect (SHE)-assisted Spin-Transfer Torque (STT) writing, the proposed design enables a single SHE current to simultaneously write data to four MTJs, substantially reducing power consumption. Additionally, the integration of stacked MTJs significantly improves storage density. The proposed WinEdge efficiently supports both standard and transposed data access modes regardless of bit-width, achieving up to 36% lower power, 47% reduced energy consumption, and 28% faster processing speed compared to existing designs. Simulations conducted in 45 nm CMOS technology validate its superiority over conventional SRAM-based solutions for convolutional neural network (CNN) acceleration in resource-constrained edge environments. Full article

This paper addresses inherent limitations in unmanned aerial vehicle (UAV) undercarriages hindering vertical takeoff and landing (VTOL) capabilities on uneven slopes and obstacles. Robotic landing gear (RLG) designs have been proposed to address these limitations; however, existing designs are typically limited to ground slopes of 6–15°, beyond which rollover would happen. Moreover, articulated RLG concepts come with added complexity and weight penalties due to multiple drivetrain components. Previous research has highlighted that even a minor 3-degree slope change can increase the dynamic rollover risks by 40%. Therefore, the design optimization of robotic landing gear for enhanced VTOL capabilities requires a multidisciplinary framework that integrates static analysis, dynamic simulation, and control strategies for operations on complex terrain. This paper presents a novel, hybrid, compliant, belt-driven, three-legged RLG system, supported by a multidisciplinary design optimization (MDO) methodology, aimed at achieving enhanced VTOL capabilities on uneven surfaces and moving platforms like ship decks. The proposed system design utilizes compliant mechanisms featuring a series of three-flexure hinges (3SFH), to reduce the number of articulated drivetrain components and actuators. This results in a lower system weight, improved energy efficiency, and enhanced durability, compared to earlier fully actuated, articulated, four-legged, two-jointed designs. Additionally, the compliant belt-driven actuation mitigates issues such as backlash, wear, and high maintenance, while enabling smoother torque transfer and improved vibration damping relative to earlier three-legged cable-driven four-bar link RLG systems. The use of lightweight yet strong materials—aluminum and titanium—enables the legs to bend 19 and 26.57°, respectively, without failure. An animated simulation of full-contact landing tests, performed using a proportional-derivative (PD) controller and ship deck motion input, validate the performance of the design. Simulations are performed for a VTOL UAV, with two flexible legs made of aluminum, incorporating circular flexure hinges, and a passive third one positioned at the tail. The simulation results confirm stable landings with a 2 s settling time and only 2.29° of overshoot, well within the FAA-recommended maximum roll angle of 2.9°. Compared to the single-revolute (1R) model, the implementation of the optimal 3R Pseudo-Rigid-Body Model (PRBM) further improves accuracy by achieving a maximum tip deflection error of only 1.2%. It is anticipated that the proposed hybrid design would also offer improved durability and ease of maintenance, thereby enhancing functionality and safety in comparison with existing robotic landing gear systems. Full article

Industry 4.0 is propelling modern industries forward due to its reliability, stability, and performance. Electric motors (EMs) are utilized in multiple industries for their efficiency, precise speed and torque control, and robustness. Detecting faults in motors at an early stage is crucial to ensure maximum productivity. Recently, DL has been implemented as a data-driven approach for detecting faults in motors. However, due to the limited availability of labeled fault data, the performance of the DL model is constrained. This issue is addressed by leveraging transfer learning (TL), which uses knowledge from a larger source domain to improve performance in a smaller target domain. In this paper, a multiple fault detection (FD) model for EMs is proposed by combining the ideas of deep convolutional neural networks (CNNs) and TL. A one-dimensional signal-to-image conversion technique is suggested for converting the vibration signal to images, and an Inception-ResNet-v2-inspired FD model is proposed for detecting bearing faults in the motor. The proposed method achieved a mean accuracy of more than 99%. Full article

In response to the absence of an effective variable speed control strategy for tractors equipped with hydro-mechanical continuously variable transmission (HMCVT) during rotary-tillage operations, this study investigates the power transfer and fuel economy characteristics of the rotary-tilling tractor during operation. A dynamic analysis of the rotary-tilling tractor is conducted, and a dynamic model for the rotary-tilling tractor is developed. This model comprehensively incorporates factors such as the transmission efficiency of the HMCVT, the horizontal cutting force of the rotary tillage, and the torque coupling relationships between the various transmission subsystems and utilizes a backward modeling approach with dual inputs: walking load and rotary-tillage load. Based on the measured data of the effective fuel consumption rate from 64 engine groups within the study, a BP neural network model of the engine’s fuel characteristics is developed. Furthermore, it is proposed that fuel consumption per kilometer of rotary-tillage operation be used to characterize the fuel economy of the rotary-tilling tractor. The results demonstrate that the increase in forward speed concurrently enhances both the productivity and fuel economy of the rotary-tilling tractor. This finding provides a theoretical foundation for developing a variable speed control strategy for the rotary-tilling tractor. Full article

Compression via pressure waves is an effective but specific way of compressing gases. This paper presents a broad overview of work related to the use of unsteady processes in the construction of micro-engines. The main advantages of wave rotors, such as a low rotor speed, self-cooling channels, high compression in a single stage, and the possibility of operating at a very small geometric scale, are addressed, and their disadvantages, such as the requirement of the precise synchronization of wave processes and poor torque-generation properties, are also outlined. This review highlights the possibility of operating at a geometric scale, which conventional solutions have failed to achieve. In the thermodynamic cycle of a micro-engine, a compression process carried out in an unsteady manner is superior in efficiency to stationary solutions. On the contrary, in the expansion process, fluid inertia is an obstacle to the full utilization of the thermal energy transferred to the fluid in the combustion chamber. The best solution is, therefore, a favorable combination of both features, leading to unsteady compression and steady-state expansion in the heat engine cycle. This article presents an overview of the existing technical solutions and published research results devoted to the construction of pressure wave compression micro-engines: patents, scientific publications describing various research methods, numerical calculations, and the experimental results of unusual technical solutions. Characteristic solutions and problems arising in the development of these methods, which range from superchargers to autonomous engines, are presented and discussed. Directions for further research are suggested. Full article