In transmission systems, bearings play a critical role, and their hydraulic losses have a marked influence on overall efficiency and thermal behavior. This study investigates the variation patterns of hydraulic losses in ball bearings under oil-jet lubrication across different operating conditions. A test rig was established to measure bearing hydraulic losses, and a CFD model incorporating oil-air two-phase flow was developed and validated against measurement results. The CFD results show good consistency with the experimental measurements, yielding average discrepancies of 15% at an injection speed of 2.5 m/s and 18% at 10 m/s. The effects of injection velocity and oil temperature on bearing hydraulic losses were systematically analyzed. The results show that hydraulic losses positively correlate with rotational speed and injection velocity, while negatively correlating with oil temperature. For bearings where the cage is guided by the outer ring(OR), the cage contributes more than 85% of the total hydraulic losses, primarily due to the high shear stress in the narrow clearance between the cage and the OR land. To address this, a cage structure with reduced hydraulic losses was proposed. Compared with the original cage, the novel cage reduces bearing hydraulic losses by 59.7% at 70°C. This work underpins the theoretical analysis of hydraulic losses in rolling bearings and offers practical guidance for high-speed ball bearing cage structure optimization.

Planetary bearings are critical components in planetary transmission systems. As transmission systems evolve toward higher speeds, the lubrication of planetary bearings faces significant challenges. In this study, a specialized test rig was developed to visualize the oil flow in a planetary bearing cavity under a stationary carrier condition, a configuration featuring outer ring rotation and central oil supply. The experimental results reveal the oil flow patterns and distribution characteristics within the bearing cavity. Additionally, a dynamic-static fluid domain coupled numerical model was established to simulate the oil-air two-phase flow field in the rotating bearing domain. This model was used to analyze the variations in oil distribution inside the bearing cavity and the oil volume fraction(OVF) on component surfaces under different speeds. The research results indicate that the bearing cavity is fully filled with oil at low speeds. As the speed increases, the oil near the roller end faces on the inner ring side begins to decrease, and an arc-shaped oil film forms along the inner side of the cage. With further speed increase, this oil film expands radially outward. At 9000 r/min, only a small amount of oil remains distributed near the outer ring. Increasing the oil flow rate further enhances the OVF on these surfaces, which can alleviate oil starvation in the lubrication zone between the rollers and the inner ring under highspeed conditions. However, higher flow rates also lead to increased churning losses in the planetary bearing. The research results provide theoretical guidance for the lubrication design of planetary bearings in transmission systems.

This article investigates the transient flow behavior and distribution patterns of lubricating oil within high-speed bearings through in situ visualization. An experimental setup, comprising a transparent bearing and a visualization platform, was developed. Experiments were conducted under varied rotational speeds using two lubricants with different viscosities. A corresponding numerical model was established to simulate the lubrication flow field. The research results indicate that the two lubricants exhibit distinct transient flow characteristics inside the bearing. At lower speeds, spherical oil droplets form on the cage surface, which then deform, elongate, and are ejected. As speed increases, the oil transitions to finer filaments or accumulates on the outer ring, depending on the oil viscosity. The oil volume fraction (OVF) on the inner ring, cage, and balls decreases with increasing rotational speed. In contrast, the variation of OVF on the outer ring follows different patterns under ambient and high-temperature conditions, as well as with different lubricants. Overall, the effective oil volume retained inside the bearing cavity is relatively limited, ranging from approximately 0.5 mL to 7.8 mL. The findings of this study provide theoretical guidance for the design of oil-jet lubrication systems in high-speed bearings.

The pressure pulsation in axial piston pumps generates noise and vibrations, negatively impacting their service life and operational stability. One of the most critical factors influencing pressure pulsation is the groove design of the valve plate. Based on the original valve plate, an optimized valve plate is proposed to enhance the performance of the axial piston pump. The flow areas of the piston chambers are calculated for two types of valve plates, and the pressure pulsations are analyzed using both a numerical model and piston pump testing machine. The pressure pulsation characteristics of the original and optimized valve plates are compared under different rotational speeds and load pressures. Additionally, the impact of the optimized valve plate on the volumetric efficiency of the axial piston pump is evaluated. The results indicate that the optimized valve plate effectively reduces pressure pulsation by increasing the flow area of the piston chamber. Specifically, the test results show a 69.13% reduction in pressure pulsation at a rotational speed of 2850r/min and load pressure of 30MPa. However, the optimized valve plate also increases the leakage within the valve plate pair, leading to a decrease in volumetric efficiency. The volumetric efficiency is observed to drop by 7.39% at 1000r/min and 30MPa. This research designs an optimal valve plate to reduce pressure pulsation, which decreases the noise and vibration of axial piston pumps.

Skid-steering vehicles (SSVs) are widely used, and clarifying the impact of the propulsion system on steering capability is crucial for improving performance. SSVs with hydrostatic propulsion systems (HPS) steer by building up pressure to overcome resistance, making pressure a key factor. However, the strong coupling between HPS and vehicle dynamics complicates the analysis of steering pressure. To address this, this article establishes a coupling model between HPS and vehicle dynamics and analyzes the dynamic reaction of HPS during steering. Global sensitivity analysis (GSA) then identifies the main parameters affecting pressure characteristics. Based on these results, a method for predicting steering capability is proposed. The model's accuracy, parameter influence, and the effectiveness of the prediction method are verified through vehicle tests. Results demonstrate the model accurately reflects the interaction between motion state and HPS response. Vehicle speed is a key factor influencing pressure overshoot, which rises substantially with increased speed. Considering pressure overshoot enables accurate prediction of steering capability. This study provides a theoretical foundation and application support for forward design and control of SSVs.

Planetary gear transmission (PGT) is widely used in vehicle transmission systems. The complex internal lubrication structure and kinematic relationships within vehicle PGT lead to an uneven distribution of lubricant flow among the planetary gear sets (PGS), compromising transmission efficiency and reliability. This study investigates lubricant flow allocation in a multi-stage PGT through an integrated experimental and numerical approach. A visualization test bench was developed to measure the flow rate to each PGS, and a Volume of Fluid (VOF)-based computational fluid dynamics (CFD) model was established and validated experimentally. The effects of inlet oil pressure, temperature, and rotational speed on lubricant flow allocation to sun gears and planetary bearings were analyzed. Results reveal that lubricant flow allocation among PGS components is uneven, with planetary bearings receiving a higher proportion than sun gears. Increasing inlet pressure generally enhances flow rates across all PGSs, except for the PGS2 planetary bearings at 12000 r/min, where a decrease is observed. Elevated oil temperature promotes flow rate to the sun gears, while its effect on bearing flow varies with rotational speed. Within the planetary bearings, oil distribution is governed by both oil passage flow rate and bearing's speed. As speed increases, the oil volume fraction at the inner ring decreases significantly, showing a reduction of 86.16% at 12888 r/min compared to 3222 r/min. This indicates a risk of lubrication starvation under high-speed conditions. These findings provide quantitative insights for the lubrication design of multistage planetary transmissions.

Hybrid aerial-aquatic vehicles encounter severe thrust fluctuations and power interruption when crossing the water-air interface. Ducted propellers are widely used in water-air integrated propulsion, yet most studies focus on single-medium conditions and lack systematic research on trans-media thrust dynamics and continuous control. This paper establishes a thrust model considering equivalent fluid density and immersion depth, and proposes an optimized Finite Control Set Model Predictive Control (FCS-MPC) strategy with time-delay compensation, over-current constraints and switching frequency penalty. An aquatic-aerial trans-media test platform is built for verification, and comparative simulations are conducted. Results show that the model achieves high accuracy, and the proposed FCS-MPC significantly reduces steady-state error, suppresses thrust drop, and avoids power interruption during water exit. This work provides a theoretical basis and high-performance control scheme for HAAV propulsion systems.

The quantification of the nonlinear evolution of gear flow field structures over wide temperature ranges is crucial for gearbox lubrication and reliability design. Conventional experimental methods are costly, numerical simulations demand substantial computational resources, and traditional data-driven models lack effective integration of physical constraints. To address these limitations, a physics-informed gradient boosting tree (PI-GBT) approach for fast and accurate prediction of gear flow field structures is developed. Data are acquired using a temperature-adjustable visualized test rig for churning oil flow, with six key flow field structure sizes summarized as prediction targets. The PI-GBT integrates fluid dynamics constraints into gradient boosting trees, and its performance is compared with Gaussian process regression, physics-informed neural networks, and gradient boosting tree. The proposed model achieved superior predictive performance with R2 values ranging from 0.843 to 0.991, and partial dependence analysis revealed the dominant physical mechanisms governing each flow field structure size. The model achieves rapid prediction of flow field structures within a temperature range of-30 degrees C to 80 degrees C. It provides methodological support for optimizing efficient lubrication in gearboxes.

To address trajectory tracking deviations in tracked vehicles caused by significant unmodeled kinematic slip and dynamic terrain resistance uncertainties, this paper proposes a novel cascaded Model Predictive Control (MPC) architecture integrated with a Kinematic-Dynamic Dual Extended State Observer (Dual-ESO). Specifically, the inner-loop dynamic ESO estimates physical torque resistances, while the outer-loop kinematic ESO reconstructs time-varying geometric slips for active feedforward compensation. The proposed framework is comprehensively validated under significant compound disturbance scenarios, including continuous dynamic slips, step lateral skids, sudden yaw drifts, and abrupt terrain resistance surges. Simulation results demonstrate that the constructed Dual-ESO rapidly and accurately reconstructs the multi-source disturbances. Consequently, compared to the conventional cascaded kinematic MPC and Active Disturbance Rejection Control (ADRC) framework, the proposed architecture yields superior tracking precision, reducing both the Integral Time Absolute Error (ITAE) and the Root Mean Square Error (RMSE) along both the X and Y axes by over 73%.

Gearbox efficiency is essential for new energy vehicles. Most of the energy in a gearbox is consumed by a load-independent factor, e.g., churning loss, which, however, has not been deeply addressed. In this study, load-independent losses are inhibited by oleophobic treatment of the surfaces of a transmission component. A polytetrafluoroethylene (PTFE) coating was prepared via electroless chemical plating. The contact angle (CA) and surface morphology of the coated surfaces were tested to elucidate the loss inhibition mechanism at the oleophobic interface. A visualization test rig for measuring the churning oil flow was built with the function of controlling the temperature in the range of -30 to 80 degrees C. The moving particle semi-implicit (MPS) method was used to further investigate the mechanism of oleophobic surface regulation. The oil velocity and pressure distributions, slip characteristics, and flow field around the coated surface were investigated. An analytical flow model was established to determine the flow structure and quantify its relationship with oil properties and surface characteristics. The results showed that the CA increased from 7.8 degrees to 31.2 degrees when the surface was coated with PTFE. The average reduction in the churning torque test values ranged from 20% to 36% across a wide temperature range of -30 to 80 degrees C, with a maximum of 50.7% at 40 degrees C. The simulated slip lengths ranged from 2.9 to 16.0 mu m at different rotational velocities. The coating reduced the oil velocity and pressure, as well as the viscous shear and differential pressure resistance, on the surface of the rotating component. This study thus provides scientific support for improving the efficiency of gearboxes used in complex engineering.

This article proposes a novel dual-motor coupling drive system, consisting of two motors, a planetary gear mechanism, and a one-way clutch, with functional requirements for torque coupling mode at low speeds, speed coupling mode at medium to high speeds, and the ability to autonomously switch between modes. Based on the lever diagram theory model, the speed characteristics of the planetary gear mechanism are analyzed. Configuration feature matrices, variable-cell operation matrices, and dynamic characteristic matrices are constructed to achieve automatic generation and optimization of the configurations, resulting in 24 optimized configurations. Taking a 10-ton class 4 × 4 wheel hub drive special vehicle as a reference, the configuration that achieves the maximum transmission range is selected, and initial parameter matching is performed. The dynamic characteristics of the drive system are analyzed, and the initial parameters are used to form parameter optimization constraints. An objective function balancing both economy and reliability is established, and parameter optimization research is conducted using a genetic algorithm with an elite strategy. Compared to the original parameters, after optimization, the proportions of high-speed operating points for the first and second planet carriers are reduced by 78.52

Abstract The challenge of low electric outputs of triboelectric nanogenerators limits their large-scale practical applications. Although considerable efforts have been focused on improving the output, e.g., enhancing the surface charge densities of tribo-materials, the improvements are either too weak or too complicated. Here, we show that optimizing the running-in process with dimethyl sulfoxide solvent can increase the charge density of polyimide-based triboelectric nanogenerators to 2.5 mC m −2 , a fourfold enhancement compared with untreated devices. The solvent-assisted running-in process removes the worn radicals, debris, or transferred materials on the contact surface, reducing electron transfer hindrance issues. Through time-of-flight secondary ion mass spectrometry, molecular dynamics simulations and density functional theory analyses at the molecular and electronic levels, the results indicate that running-in friction further induces the breakage of the N–C bonds in polyimide, resulting in the freedom to release amide groups. Together with the function of dimethyl sulfoxide-driven extraction, the amide-containing chains rearrange into “molecular brushes” towards contact surfaces, among which the highly electron-withdrawing C = O bonds are thus exposed and capture electrons from the counter tribolayer. This solvent-assisted running-in strategy improves electrical output in engineering polymers without material modification and clarifies how tribological running-in can be used to regulate triboelectric performances.

This paper proposes a systematic design method for a dual-motor coupling drive system (DMCDS) based on dual-planetary gearsets. A D-matrix framework is developed to generate topological configurations and derive the corresponding kinematic equations in torque coupling (TC) and speed coupling (SC) modes. Screening rules are introduced to eliminate infeasible configurations, especially those with circulating power. Then, an optimization model is established for parameter matching, in which the Analytic Hierarchy Process (AHP) is used to determine the weights of the optimization indices and Particle Swarm Optimization (PSO) is adopted to search for feasible parameter sets. The results show that 10 configurations satisfy the design constraints. TC mode simulation results further indicate that the selected configurations avoid circulating power and show better coupling-mechanism efficiency than the reference configuration.

The gear-churning flow field significantly affects gearbox lubrication and efficiency. Yet the evolution mechanisms across wide temperature ranges remain poorly understood, limiting lubrication design for underwater vehicles and renewable energy systems. The study links vision-based flow fields to churning torque through a structure-to-torque pathway. A temperature-adjustable visualization test rig for oil flow is built to capture flow field evolution and measure churning torque. The reverse hill-shaped oil domain is parameterized by width c1 and height h1, and the oil domain volume is approximated as 'I approximate to Ks center dot b center dot c1 center dot h1. A mechanistic-data hybrid model is constructed to predict (c1, h1) based on (v, & micro;, 6, B). The model integrates analytical formulations classified by viscosity regime within a physics-informed neural network (PINN) framework. A shape factor is introduced into Changenet's classical churning torque calculation theory. Consequently, an improved prediction strategy is developed to predict churning torque based on the flow field structure. Prediction accuracy comparable to that of a standalone PINN is achieved by the hybrid model. Physical consistency is preserved under extrapolation to -38 degrees C and 100 degrees C. The predicted c1 and h1 values can be used as inputs for the improved churning-torque prediction model. The proposed strategy links input parameters, flow-field structures, and churning torque. The proposed strategy can reduce the dependence on costly experiments and laborious numerical simulations, providing a methodological foundation for torque prediction in engineering transmissions.

Skid-steering vehicles (SSVs) have a wide range of applications, and coordinated control (CC) of the propulsion system is a key to improving steering capability. SSVs equipped with hydrostatic propulsion systems (HPSs) drive and steer by building up pressure, so pressure determines their steering capability. However, the strong coupling between HPS and vehicle dynamics poses a challenge for CC. To address this issue, this article proposes a CC strategy based on a machine learning (ML)-enhanced pressure observer. First, an ML approach is employed to refine the HPS's efficiency model, thereby improving the accuracy of pressure estimation. A CC strategy is then developed to adjust the engine operating point, ensuring that the pressure demands of both the driving and steering systems are simultaneously satisfied. Finally, the effectiveness is verified by vehicle tests. Results show that the strategy enhances steering capability and reduces fuel consumption by approximately 10.98%, with a moderate increase in temperature of 1.25 degrees C (from 88.5 degrees C to 89.75 degrees C). This work provides both theoretical and practical support for the design and control of future SSVs.

To obtain the real pressure distribution of the valve plate pair, a novel experimental system with 18 pressure measurement points is developed. The measurement points are strategically positioned based on numerical results. The pressure measurement layout includes 9 points each in high-and low-pressure areas, with focused attention on transition areas, grooves and inner/outer sealing bands. The feasibility of the experimental method is also analyzed. The comprehensive pressure measurements are conducted under various rotational speeds and load conditions. Based on the acquired data, the pressure distribution and time-frequency characteristics in four grooves are analyzed. The results indicate that the proposed experimental method is feasible. Alternating high pressures are observed in the grooves. Pressure overshoots occur in the high-pressure groove near the top dead center. In addition, multiple pressure peaks are detected in the groove due to pressure shocks. These findings contribute to a deeper understanding of the pressure behaviours of the oil film in the valve plate pair.

Graphene-based nano lubricant additives have attracted much attention due to their structure and exceptional physical properties. However, some issues still hinder graphene’s practical application for grease lubricants: graphene-based additives are difficult to disperse in grease, and lubrication failure is easy under extreme working conditions. In this study, basic lead (II) carbonate/graphene (Pb3(CO3)2(OH)2#G) nano-composites are synthesized by a facile solution reaction method. To improve the dispersity, the Pb3(CO3)2(OH)2#G is modified by a silane coupling agent (SCA) via the mechanochemical method (Pb3(CO3)2(OH)2#G-SCA). The tribological properties of base greases can be significantly improved via adding a few of Pb3(CO3)2(OH)2#G-SCA (0.5wt.%). Especially, the COF and wear depth of greases could be reduced respectively by 30% and 60% at elevated temperature (150 °C). The grease with Pb3(CO3)2(OH)2#G-SCA can still provide good lubrication properties at a higher temperature (175 °C). It is believed that the improved lubrication property with Pb3(CO3)2(OH)2#G-SCA is due to the synergistic effect between graphene sheets and basic lead (II) carbonate nanoparticles. This work opens a good way to prepare graphene-based lubricant additives for high temperature applications.

The importance of heavy-load friction pairs is highlighted by the extensive use of heavy machinery in large engineering projects. Their performance under mixed lubrication conditions directly impacts efficiency, reliability, and service life. Accurately and effectively establishing a lubrication characteristic model for the oil film in friction pairs and solving it is of paramount importance. Currently, there is a lack of systematic analysis and summaries of models in this field. This work comprehensively reviews the modeling and solution methods, as well as the core challenges, associated with the oil film characteristics of heavy-load friction pairs under mixed lubrication. It also provides detailed descriptions of typical applications for each method. Finally, based on previous research, this paper outlines future development directions. The review aims to provide model guidance for improving the lubrication performance and extending the service life of heavy-load friction pairs, promoting the application of mixed lubrication theory in engineering practice.

Electric vehicles exhibit variable speed motion when encountering road obstacles. This inevitably makes the electric powertrain in a non-inertial system. Most existing electric powertrain models overlook the non-inertial effects induced by vehicle motion. This study proposes a modeling method for the electromechanical rigid-flexible coupling of the electric powertrain in a non-inertial system. Additional inertial forces are derived from vehicle motion parameters. A vibration test is launched to verify model effectiveness. Speed bumps, potholes, and randomly uneven roads serve as road excitations to analyze the vibration response and load characteristics of the powertrain. The results show that the equilibrium positions of components are significantly offset when encountering speed bumps and potholes. The position offset leads to fluctuations in bearing force. Under conditions of a randomly uneven road, random components are introduced into the bearing vibration signals and motor electrical signals, resulting in a increase in amplitude fluctuations. Furthermore, the structural parameters of speed bumps, potholes, and road profiles greatly influence the bearing force and vibration acceleration. The research results provide theoretical support for the structural design and life prediction of electric powertrains.