Search Results (34)

Additive manufacturing technologies enable the design of complex lightweight structures for electric powertrain applications. This study evaluates the topology optimization and conceptual additive manufacturing of a real electric vehicle gearbox housing, aiming to reduce weight while maintaining structural stiffness. Based on an existing industrial component, a topology-optimized design featuring an X-shaped rib structure was developed. The manufacturing concept combines Laser Metal Deposition (LMD) with a pre-machined turned part. A comparative material study was carried out using finite element simulations to assess aluminum, magnesium, titanium, and stainless steel in terms of weight, deformation, and natural frequency. The results indicate that aluminum alloys offer the best balance of stiffness and weight due to their high specific modulus and favorable processability. The optimized design achieved a simulated weight reduction of approximately 21% with only a minor increase in rotational deformation. A cost analysis of different manufacturing methods suggests that, while conventional casting remains more economical at higher volumes, additive processes are becoming increasingly viable for small series. The study provides a theoretical foundation for future development of lightweight functionally integrated gearbox housings in electric mobility. Full article

In response to the growing demand for lightweight and high-efficiency industrial equipment, this study addresses the critical issue of lubrication failure in high-speed, heavy-duty gear reducers, which often leads to reduced transmission efficiency and premature mechanical damage. A three-dimensional transient multiphysics-coupled model of oil-jet lubrication is developed based on computational fluid dynamics (CFD). The model integrates the Volume of Fluid (VOF) multiphase flow method with the shear stress transport (SST) k−ω turbulence model. This framework enables the accurate capture of oil-jet interface fragmentation, reattachment, and turbulence-coupled behavior within the gear meshing region. A parametric study is conducted on oil injection velocities ranging from 20 to 50 m/s to elucidate the coupling mechanisms between geometric configuration and flow dynamics, as well as their impacts on oil film evolution, energy dissipation, and thermal management. The results reveal that the proposed method can reveal the dynamic evolution characteristics of the gear injection lubrication. Adopting an appropriately moderate injection velocity (30 m/s) improves oil film coverage and continuity, with the lubricant transitioning from discrete droplets to a dense wedge-shaped film within the meshing zone. Optimal lubrication performance is achieved at this velocity, where oil shear-carrying capacity and kinetic energy utilization efficiency are maximized, while excessive turbulent kinetic energy dissipation is effectively suppressed. Dynamic monitoring data at point P further corroborate that a well-tuned injection velocity stabilizes lubricant-velocity fluctuations and improves lubricant oil distribution, thereby promoting consistent oil film formation and more efficient heat transfer. The proposed closed-loop collaborative framework—comprising model initialization, numerical solution, and post-processing—together with the introduced quantitative evaluation metrics, provides a solid theoretical foundation and engineering reference for structural optimization, energy control, and thermal reliability design of gearbox lubrication systems. This work offers important insights into precision lubrication of high-speed transmissions and contributes to the sustainable, green development of industrial machinery. Full article

The paper provides an analysis of the energy efficiency of the swing drive system of hydraulic excavators, which integrally includes a hydraulic motor and a planetary reducer. The indicator of the drive’s energy efficiency is determined based on the efficiency of the hydraulic motor and the planetary reducer. The efficiency of the hydraulic motor is defined as a function of the specific flow, pressure, and the number of revolutions of the hydraulic motor. The efficiency of the reducer is determined using structural analysis of planetary gearboxes and the moment method. As an example, the results of a comparative analysis of the energy efficiency of the swing drive of a tracked hydraulic excavator, weighing 16,000 kg and having a bucket volume of 0.6 m³, are presented. From the set of possible generated variant solutions of the drive, obtained through the synthesis process based on the required torque and platform rotation speed, two extreme drive variants were selected for the analysis. In the first configuration, a hydraulic motor characterized by a low specific flow is combined with a three-stage reduction gear featuring a higher overall transmission ratio, whereas the second configuration integrates a high-specific-flow hydraulic motor with a two-stage reduction gear of a lower transmission ratio. The obtained results of the comparative analysis of the drive’s energy efficiency are presented depending on the change in the required torque and the rotational speed of the platform. Full article

Gearboxes are autonomous devices essential for power transmission in various mechanical systems. When a failure occurs, it can lead to an inability to perform the required functions, potentially resulting in a complete shutdown of the mechanism and causing significant operational disruptions. Consequently, deploying expert methods for fault detection and diagnosis is crucial to ensuring the reliability and efficiency of these systems. Artificial intelligence (AI) techniques show promise for fault diagnosis, but their accuracy can be hindered by noise and manufacturing imperfections that distort mechanical signatures. Thorough data analysis and preprocessing are vital to preserving these critical features. Validating approaches through numerical simulations before experimentation is essential to identify model limitations and minimize risks. A hybrid approach, combining AI and physics-based models, could provide a robust solution by leveraging the strengths of both domains: AI for its ability to process large volumes of data and physics-based models for their reliability in modeling complex mechanical behaviors. This paper proposes a comprehensive diagnostic methodology. It starts with feature extraction from time-domain analysis, which helps identify critical indicators of gearbox performance. Following this, a feature selection process is applied using the Fisher criterion, which ensures that only the most relevant features are retained for further analysis. These selected features are then employed to train an Adaptive Neuro-Fuzzy Inference System (ANFIS), a sophisticated approach that combines the learning capabilities of neural networks with the reasoning abilities of fuzzy logic. The proposed methodology is evaluated using a dataset of gear faults generated through energy simulations based on a six-degree-of-freedom (6-DOF) model, followed by a secondary validation on an experimental dataset. Full article

This study investigates the transient lubrication dynamics of subway gearboxes during acceleration phases through computational fluid dynamics (CFD) modeling. A simplified gearbox model with helical gears, bearings, and oil-guide channels was developed using STAR-CCM+^®. Simulations evaluated the effects of three acceleration levels (7.4 m/s², 4.4 m/s², and 3.2 m/s²) and three different oil temperatures (−10 °C, 10 °C, and 70 °C) on pressure distribution, churning torque, and oil supply dynamics. The results show that higher acceleration levels intensify transient pressure fluctuations in gear meshing regions and expedite oil supply initiation to bearings. However, the steady-state lubrication performance remains consistent across acceleration magnitudes. Elevated oil temperatures significantly decrease the initial churning torque of a gearbox but increase the steady-state churning torque. There exists an optimal temperature that maximizes the oil supply in the gear meshing zone. In addition, the initial oil supply times for bearings are slightly reduced under lower temperatures. These findings highlight the critical role of transient acceleration and temperature effects in gearbox lubrication optimization, providing insights for enhancing reliability under dynamic operating conditions. Full article

A tapered roller bearing (TRB) is a specialized type of bearing with a high load-to-volume ratio, designed to support both radial and axial loads. Lubrication plays a crucial role in TRB operation by reducing friction and dissipating heat generated during rotation. However, it can also negatively impact TRB performance due to the viscous and inertial effects of the lubricant. Extensive research has been conducted to examine the role of lubrication in TRB performance. Lubrication primarily influences the frictional characteristics, thermal behavior, hydraulic losses, dynamic stability, and contact mechanics of TRBs. This paper aims to collect and classify the scientific literature on TRB lubrication based on these key aspects. Specifically, it explores the scope of research on the use of Newtonian and non-Newtonian lubricants in TRBs. Furthermore, this study analyzes research based on TRB size and type, considering both oil and grease as lubricants. The findings indicate that both numerical and experimental studies have been conducted to investigate Newtonian and non-Newtonian lubricants across various TRB sizes and types. However, the results highlight that limited research has focused on non-Newtonian lubricants in TRBs with an Outer Diameter (OD) exceeding 300 mm, i.e., those typically used in wind turbines, industrial gearboxes, and railways. Full article

The toothless oil stirring disk is vital in modern transmission technology, particularly in fields like aviation, aerospace, and nuclear power, significantly impacting equipment performance. Oil-stirring lubrication is widely used in internal systems due to its simplicity and high reliability, but oil-stirring losses during lubrication contribute to increased system temperatures, affecting lifespan and performance. Accurate simulation of the two-phase flow during the lubrication process of high-speed toothless oil stirring disks is crucial for extending the lubrication system service life. This paper proposes a dynamic modeling approach for the lubrication of high-speed toothless oil stirring disks, integrating the volume of fluid (VOF) model and the RNG k-ε turbulence model, alongside spring smoothing and dynamic mesh reconstruction techniques. The model explores fluid flow and oil distribution in high-speed, toothless oil stirring pans, investigating the effects of different stirring pan speeds and oil heights on lubrication performance. Results indicate that stirring pan speed and oil height are key to improving lubrication efficiency. At high speeds, centrifugal force and gravity cause the lubricating oil to detach from the stirring pan surface, continuing to splash due to inertia. At 3200 r/min and an oil level of 20 mm, a stable oil film forms in the gearbox. Higher stirring pan speeds generate greater turbulence, enhancing lubrication effectiveness. The findings offer theoretical insights for dynamic lubrication system modeling and support gearbox design and optimization in aerospace and similar fields. Full article

Variable tooth thickness gears have significant effects on the characteristics of the flow field inside the gearbox and the lubrication efficiency under high-speed operating conditions due to their complex parameters, such as tooth profile, cone angle, rotational speed, and oil injection speed. To investigate the impact mechanism of oil injection velocity on the working flow field of high-speed variable tooth thickness gears under varying parameters, this paper establishes an oil injection lubrication model under high rotational speeds of variable tooth thickness gears, based on computational fluid dynamics (CFD) methods and the Volume of Fluid (VOF) model, combined with the dynamic mesh technique. This paper analyzes the lubrication issues at the initial oil injection moment of involute variable tooth thickness gears. By computing the lubricant distribution state at 0.1 s after the oil injection onset based on the stabilized flow field under no-oil-injection condition, discussions are conducted on the single-phase and two-phase flow fields within the gear casing at different cone angles and rotational speeds separately examining the flow states near the oil nozzle and the distribution patterns of lubricant at the meshing portions. The results indicate that, without oil injection, the pressure near the oil nozzle gradually increases with an increase in rotational speed and decreases with an increase in cone angle; at the initial oil injection moment, the lubricant volume fraction at the gear meshing portions gradually increases with an increase in rotational speed and rises with an increase in cone angle. Full article

During the planetary gearbox design process, the issue of light-weighting has been studied using various methods. To get better results from light-weighting, it is necessary for new methods to be considered to deal with this problem. This study proposes the multi-strategy optimized sparrow search algorithm (MSOSSA) that employs five strategies to improve the ability to generate high-quality initial solutions, convergence ability and speed, and the quality of the solution. In the application, the volume of the gearbox is reduced by 6.39%, and the difference in ratio from the previous application is no more than 1.5%. The light-weighting problem of the gearbox is effectively solved. Compared to the other two algorithms, the MSOSSA is six times more likely to produce a high-quality initial solution in a set of 30 runs. The speed of convergence and the ability to converge and generate global optima are the best of the three. Full article

In order to clarify the effect of mixed lubrication methods on the oil flow and power loss of the gearbox, this study adopts a high-precision moving particle semi-implicit (MPS) method to investigate the lubrication of the gearbox under the joint influence of splash lubrication and oil injection lubrication. The accuracy of the numerical method to calculate the churning torque was verified by the constructed test rig. The effects of rotational speed, immersion depth, injection volume rate, and oil injection angle were analyzed and evaluated for lubrication. The results show that better lubrication can be achieved with relatively small churning torques by using a hybrid lubrication method. This provides some references for engineering applications of gearboxes. Full article

To investigate the lubrication characteristics in high-speed train gearboxes, a two-stage herringbone gearbox with an idle gear was analyzed. The lubricant flow and distribution were shown using the moving particle semi-implicit (MPS) method. A liquid film flow model was brought in to enhance the non-slip wall boundary conditions, enabling MPS to predict the film flow characteristics. This study investigates the influence of gear rotating speed, lubricant volume, and temperature on lubricant flow, liquid film distribution, lubrication state in the meshing zone, and churning power loss. The results indicate that lubrication characteristics depend on the splashing effect of rotating gears and lubricant fluidity. Increasing gear rotating speed and lubricant temperature can improve liquid film distribution on the inner wall, increase lubricant volume, and thus enhance film thickness. The lubricant particles in the meshing zone correlate positively with the gear rotating speed and lubricant volume, correlate negatively with a temperature above 20 °C, and decrease notably at low temperatures. Churning power loss mainly comes from the output gear. As lubricant volume and gear rotating speed increase, churning torque and power loss increase. Above 20 °C, viscosity decreases, reducing power loss; low temperatures lessen lubricant fluidity, reducing churning power loss. Full article

Resource and energy efficiency are of high importance in gearbox applications. To reduce friction and wear, an external lubricant supply like dip or injection lubrication is used to lubricate tribosystems in machine elements. This leads to the need for large lubricant volumes and elaborate sealing requirements. One potential method of minimizing the amount of lubricant and simplifying sealing in gearboxes is the self-lubrication of tribosystems using oil-impregnation of porous materials. Although well established in low-loaded journal bearings, self-lubrication of rolling-sliding contacts in gears is poorly understood. This study presents the self-lubrication method using oil-impregnated porous sinter material variants. For this, the tribosystem of gear contacts is transferred to model contacts, which are analyzed for friction and temperature behavior using a twin-disk tribometer. High-resolution surface images are used to record the surface changes. The test results show a significant increase in self-lubrication functionality of tribosystems by oil-impregnated porous sinter material and a tribo-performance comparable to injection-lubricated tribosystems of a sinter material with additionally solid lubricant added to the sinter material powder before sintering. Furthermore, the analyses highlight a significant influence of the surface finish, and in particular the surface porosity, on the overall tribosystem behavior through significantly improved friction and wear behavior transferable to gear applications. Full article

This paper provides a novel application of the multi-criteria decision-making (MCDM) method to the multi-objective optimization problem (MOOP) of creating a two-stage helical gearbox (TSHG) with second-stage double gear sets (SDGSs). The aim of the study is to determine the optimum major design components for enhancing the gearbox efficiency while reducing the gearbox volume. In this work, three primary design parameters are chosen to accomplish this: the gear ratio of the first stage and the coefficients of the wheel face width (CWFW) of the first and second stages. Additionally, the study is conducted with two distinct objectives in mind: the lowest gearbox volume and the maximum gearbox efficiency. Moreover, phase 1 and phase 2, respectively, are the two stages of the MOOP. Phase 2 handles the MOOP to identify the ideal primary design factors as well as the single-objective optimization problem to minimize the difference between the variable levels. Additionally, the Multi-Attributive Ideal–Real Comparative Analysis (MAIRCA) approach is selected to deal with the MOOP. The results of the study are utilized to determine the ideal values for three crucial design parameters in order to create a TSHG with SDGSs. Full article

In order to address the Multi-Objective Optimization Problem (MOOP) in building a two-stage helical gearbox, this work presents a novel application of the Multi-Criterion Decision-Making (MCDM) method. The aim of the study is to determine the optimal primary design factors that will increase gearbox efficiency while decreasing gearbox volume. Three main design parameters were chosen for assessment in this work: the first stage’s gear ratio, and the first and second stages’ Coefficients of Wheel Face Width (CWFW). In addition, the MOOP is divided into two phases: phase 1 solves the single-objective optimization problem to reduce the gap between variable levels, and phase 2 solves the MOOP to determine the optimal primary design factors. Furthermore, the Entropy approach was picked to compute the weight criteria, and the MARCOS method was chosen as an MCDM method to handle the multi-objective optimization issue. The following are important characteristics of the study: Firstly, the MCDM method (MARCOS technique) was successfully applied to solve a MOOP for the first time. Secondly, this work has looked into power losses during idle motion to calculate the efficiency of a two-stage helical gearbox. The results of the study were used in the design of a two-stage helical gearbox in order to identify the optimal values for three important design parameters. Full article

Wind turbines (WT) are a clean renewable energy source that have gained popularity in recent years. Gearboxes are complex, expensive, and critical components of WT, which are subject to high maintenance costs and several stresses, including high loads and harsh environments, that can lead to failure with significant downtime and financial losses. This paper focuses on the development of a digital twin-based approach for the modelling and simulation of WT gearboxes with the aim to improve their design, diagnosis, operation, and maintenance by providing insights into their behavior under different operating conditions. Powerful commercial computer-aided design tools (CAD) and computer-aided engineering (CAE) software are embedded into a computationally efficient multi-objective optimization framework (modeFrontier) with the purpose of maximizing the power density, compactness, performance, and reliability of the WT gearbox. High-fidelity models are used to minimize the WT weight, volume, and maximum stresses and strains achieved without compromising its efficiency. The 3D CAD model of the WT gearbox is carried out using SolidWorks (version 2023 SP5.0), the Finite Element Analysis (FEA) is used to obtain the stresses and strains, fields are modelled using Ansys Workbench (version 2024R1), while the multibody kinematic and dynamic system is analyzed using Adams Machinery (version 2023.3, Hexagon). The method has been successfully applied to different case studies to find the optimal design and analyze the performance of the WT gearboxes. The simulation results can be used to determine safety factors, predict fatigue life, identify potential failure modes, and extend service life and reliability, thereby ensuring proper operation over its lifetime and reducing maintenance costs. Full article