Search Results (143)

The increasing performance requirements of electric vehicle powertrains demand lightweight, efficient, and low-noise transmission systems. High-speed electric drive unit concepts offer significant potential for reducing motor size and mass by shifting torque generation to higher rotational speeds. However, this approach places increased demands on gearbox power density, efficiency, and noise, vibration, and harshness (NVH) performance. This work investigates the NVH behaviour of a compact, high-speed automotive gearbox with a focus on planetary gear stages. Although planetary stages offer high compactness, their complex kinematics can lead to pronounced NVH challenges. In particular, sequentially phased gear meshing results in characteristic sideband components whose orders can be predicted analytically, while their amplitudes remain difficult to estimate reliably during the design phase, necessitating experimental validation. Several NVH-oriented design measures, including high-contact-ratio gearing and low-NVH microgeometry, are applied to a two-stage gearbox comprising a planetary and a cylindrical gear stage. Peak-to-peak transmission error is used as a primary NVH design metric. The planetary stage is analysed in detail to assess the influence of sequential phasing on sideband components in the dynamic response and resulting vibration behaviour. The NVH-oriented gearbox is tested on a bench, with housing accelerations used to analyse planetary sidebands, providing insights into the NVH potential of compact, high-speed gearboxes and the role of sequential phasing in the vibration response. Full article

Forced spray on transmission gears performs the triple functions of lubrication, heat dissipation, and tooth surface cleaning under high-speed and heavy-duty conditions, serving as a key technical means to prevent scuffing, pitting, or even tooth breakage failure and ensure highly reliable operation of the transmission system. This study conducted numerical simulations using CFD to investigate the lubrication performance of high-speed spur gear pairs with respect to nozzle parameters including jet velocity, nozzle position, included angle, length, and number of nozzles. The results show that the medium jet velocity of 40–60 m/s achieves an optimal balance between penetration depth and spray dispersion. The results indicate that a medium jet velocity of 40–60 m/s optimally balances penetration depth and spray dispersion. Dual-nozzle oil injection significantly improves spatial uniformity and establishes a stable circular recirculation structure, increasing the oil volume fraction in the meshing zone by approximately 40% compared to the single-nozzle configuration, and reducing the area of dry patches by over 60%. A nozzle inclination angle of 60–90° combined with a length of 30 mm yields the best combination of oil delivery and coverage. Furthermore, upgrading from a 2 + 1 to a 3 + 1 nozzle layout enhances oil film continuity and suppresses abrupt negative-pressure fluctuations during meshing, thereby stabilizing the hydrodynamic lubrication effect. These findings provide quantitative guidance for optimizing nozzle geometry and layout in high-speed gearbox lubrication systems, contributing to improved reliability and reduced energy loss. Full article

For high-speed electric multiple units, derailment may lead to severe vehicle instability and safety hazards, making it essential to understand post-derailment dynamic behavior and protective mechanisms. To elucidate the dynamic evolution characteristics and anti-derailment mechanisms of high-speed electric multiple units under derailment conditions, a multibody vehicle–track derailment dynamics model was established for both motor and trailer cars, incorporating nonlinear multi-point contact interactions among wheelsets, gearboxes, traction motors, brake discs, rails, fasteners, and slab tracks. Static geometric clearance verification and dynamic simulations were combined to evaluate the anti-derailment performance of different vehicle configurations and the effectiveness of a carbody–bogie anti-yaw stopper. The results show that underframe components are the first structures to interact with the track after derailment and play a critical role in the evolution of vehicle attitude. Compared with the gearbox and traction motor of a motor car, the brake disc of a trailer car provides more effective lateral restraint and energy dissipation due to its lower installation position and more favorable load-transfer path. The anti-yaw stopper significantly suppresses the relative yaw motion between the carbody and bogie, reducing the peak yaw angle by approximately 30–70% and improving post-derailment stability. Furthermore, a time-sequential and complementary protection mechanism is identified between underframe structures and an anti-yaw stopper. These findings provide guidance for the design and evaluation of derailment protection systems for high-speed vehicles. Full article

Permanent Magnet Direct Current (PMDC) motors are widely used in applications requiring precise speed control due to their efficiency and high torque-to-inertia ratio. This work proposes a feedforward speed control strategy for PMDC motors based on model inversion, complemented by a disturbance rejection feedback term. A gray-box model is developed using only four concentrated parameters, avoiding the overdetermination problem of classical seven-parameter identification. These parameters are identified experimentally from step-response data using a nonlinear optimization approach. The proposed control law is validated on two commercially available PMDC motors with distinctly different dynamics: a fast-response motor (FC130SA) and a slower motor with a gearbox (GM25-370). Experimental results show that the proposed feedforward controller with disturbance rejection achieves lower or comparable Integral Squared Error (ISE) than optimally tuned PID/PI controllers, while significantly reducing overshoot (up to 66% in the fast motor) and maintaining lower or comparable Control Input Area (CIA), a metric commonly used in the literature to provide an indirect indication of control effort. Unlike classical controllers, the proposed method requires no per-reference gain tuning. These results show compelling evidence that inversion-based control with disturbance rejection is a viable, energy-efficient alternative to PID control for PMDC motor speed regulation. Full article

This paper investigates the gear whine problem in a high-speed heavy-load reducer. A rigid-flexible coupled multibody dynamic model of the reducer is established using Romax. Transmission error, unit load, tooth root stress, and contact stress are used as optimization objectives. A comprehensive gear micro-modification method including lead crowning, lead slope, involute crowning, and involute slope is proposed, and a genetic algorithm is employed for optimization. The peak-to-peak transmission error [TE(p-p)] decreased from 0.27 μm to 0.19 μm for the first-stage gear pair and from 2.67 μm to 0.96 μm for the second-stage gear pair, corresponding to reductions of 29.63% and 64.04%, respectively. The maximum contact stresses decreased from 507 MPa to 488 MPa (3.75%) and from 627 MPa to 618 MPa (1.44%) for the first- and second-stage gear pairs, respectively. The radiated noise of the gearbox was reduced by about 10 dB on average. The proposed method provides a reference for the microgeometry design of high-speed heavy-load reducers. Full article

Electric-vehicle gearboxes operate at high rotational speeds and under low acoustic masking, making tonal excitation and unit-to-unit variability important design concerns. Contemporary loaded tooth contact, multibody, finite-element, and vibroacoustic models can represent the nominal excitation–transfer–response–radiation chain in considerable detail, but their inputs often remain disconnected from the manufactured and assembled gearbox. This review develops a structured framework for identifying which physical parameters, numerical representations, and validation evidence are required before a model can credibly represent a nominal design, a tolerance space, an as-built unit, or a production population. Parameters are classified jointly based on the physical origin and noise, vibration, and harshness (NVH) function and are mapped to contact, system-dynamic, structural, acoustic, and hybrid data-driven models. Four simulation-readiness levels are defined: nominal, tolerance-based, measurement-based, and variability-aware. Explicit transition gates, validation quantities, and permitted claims are assigned to each level. A stage-specific validation matrix distinguishes contact-level, interface-force, structural-response, and acoustic evidence. Literature-grounded quantitative examples demonstrate validated elastic multibody modeling and manufacturing-data-based gear-whine prediction while clarifying the limits of the available evidence. The framework provides a traceable basis for model planning, measurement selection, uncertainty analysis, and readiness-aware reporting of electric-vehicle gearbox NVH simulations. Full article

The accessory gearbox of an aero-engine operates under high-speed and heavy-load conditions, where insufficient lubrication may lead to oil-film failure, increased frictional losses, and reduced transmission reliability. Therefore, understanding oil-jet injection and tooth surface oil-film spreading characteristics is essential for improving lubrication performance. In this study, a three-dimensional geometric model incorporating the meshing region and oil nozzles was established based on a typical accessory gear pair. The model employs the VOF multiphase flow approach and the standard k-ε turbulence model, coupled with dynamic mesh techniques to accurately capture the transient interactions between gear rotation and oil–air two-phase flow. Numerical simulations reveal the dynamic evolution of oil injection, impingement on the tooth surface, oil-film spreading, and transport into the meshing zone, while the effects of injection velocity and nozzle length on lubrication performance are quantitatively analyzed. Results indicate that an injection velocity of 45–55 m/s yields optimal oil-film coverage and uniformity, and a nozzle length of h = 30 mm minimizes jet energy decay and airflow interference, achieving uniform oil filling in the meshing zone. The optimal lubrication performance for accessory gears is obtained at an injection velocity of 45–55 m/s and a nozzle length of 30 mm. This study provides a reference for the design optimization of accessory gear lubrication systems. Full article

Agricultural machinery operates under complex field conditions involving uneven terrain, crop flow impacts, variable speed and load, dust, moisture, and multi-source structural excitation. These factors make vibration-based fault diagnosis more challenging than that of conventional rotating machinery because weak fault features are often masked by non-stationary background vibration and operating condition disturbances. This review provides a structured synthesis of vibration-based fault diagnosis for agricultural machinery, focusing on tractors, combine harvesters, harvesting machinery, and key components such as bearings, gearboxes, transmission systems, headers, threshing drums, cleaning sieves, vibrating screens, chassis, frames, and cab systems. The review first analyzes vibration sources, fault mechanisms, and signal degradation under field conditions. It then summarizes vibration sensors, data acquisition, preprocessing, time–frequency analysis, feature representation, machine learning, deep learning, transfer learning, and multi-source information fusion. Applications are reviewed from component-level diagnosis to whole-machine monitoring. Key challenges include field data scarcity, variable conditions, sensor reliability, data leakage, model generalization, edge deployment, standardization, and long-term validation. Future research should emphasise high-quality field datasets, physics-informed and explainable models, robust cross-condition diagnosis, multimodal sensing, edge intelligence, digital twins, and predictive maintenance. This review highlights the need to connect vibration mechanisms, diagnostic models, and engineering deployment requirements for reliable agricultural machinery health monitoring. Rather than treating sensors, components, algorithms, and deployment issues as separate topics, this review organizes the literature around field-specific vibration disturbances, validation evidence, deployable diagnostic requirements, and future implementation priorities. Full article

High-speed electric machines enhance power density and eliminate the need for a gearbox in waste heat recovery microturbine systems. However, existing designs often suffer from high manufacturing costs and complex cooling requirements. This study presents the development, experimental validation, and comparative analysis of three high-speed machine designs. First, a lower-speed induction machine prototype, constructed using standardized components, was tested at an operating speed of 13,000 rpm. This prototype enabled experimental validation of the numerical model used for loss calculations. Experimental results showed total losses of 7.89 kW, closely matching the simulated value of 7.75 kW at an output power of 93.1 kW, i.e., an efficiency of 92.19%. Building on these findings, two smaller machine prototypes were developed: one featuring an induction squirrel-cage rotor and the other employing a surface-mounted permanent magnet rotor topology. Both machines were designed and evaluated using finite element analysis and conjugate heat transfer simulations. Their performance was analyzed under both sinusoidal and pulse-width-modulated voltage supply conditions. At an operating speed of 14,000 rpm, the permanent magnet machine outperformed the induction machine, achieving 63.2 kW of mechanical power and an efficiency of 96.21%, while operating at lower temperatures. In comparison, the induction machine delivered 52.4 kW of mechanical power with an efficiency of 94.64%. The primary novelty and contribution of this work lie in the implementation of a two-pole machine architecture capable of achieving an output power of 100 kW at operating speeds between 20,000 and 25,000 rpm. Compared with similar solutions reported in the literature, the proposed machines feature a simplified bearing arrangement and a more straightforward liquid-cooling system. These characteristics have the potential to reduce manufacturing costs and simplify maintenance during operation. Full article

Reliable condition monitoring of wind turbine gearboxes is critical to reducing unplanned downtime and maintenance costs in wind farms. However, this task presents significant challenges due to the non-stationary nature of vibration signals, in which fault-relevant features are sparsely and unevenly distributed across the time–frequency map. Although time–frequency analysis has been widely adopted to represent nonlinear and non-stationary vibration signals, existing deep learning methods typically process the full spectrogram directly, without distinguishing redundant or uninformative regions. This leads to high input dimensionality and exposes the model to substantial spectral noise. Consequently, it increases computational burden and potentially reduces the diagnostic reliability. To address this issue, this paper proposes a two-stage hybrid framework based on complementary selection mechanisms operating on two distinct feature spaces. In the first stage, eXtreme Gradient Boosting (XGBoost) importance scores are used to identify and permanently prune uninformative time–frequency features from the input spectrogram, reducing the input map size by 25%. In the second stage, a Squeeze-and-Excitation (SE) block, inserted after the deepest residual layer, performs soft channel-wise recalibration of the abstract feature maps produced by the residual convolutional neural network (ResCNN), thereby amplifying discriminative representations prior to classification. The proposed method was evaluated in an eight-class variable-speed fault classification task using the MCC5-THU benchmark, where data were collected from a 2.2 kW motor-driven gearbox test rig. The proposed method achieves a mean accuracy of 97.81% ± 0.33% under 5-fold stratified cross-validation (CV), while reducing classifier training time by approximately 23% compared to a baseline model trained on the full spectrogram. These results demonstrate that explicit input-level spectrogram pruning, combined with model-level channel attention, yields a robust and computationally efficient diagnostic framework for wind turbine gearbox condition monitoring. Full article

Accurate gear fault diagnosis under variable operating conditions remains challenging because vibration signals are affected by noise, speed-load variations, and condition-dependent feature shifts. To address these issues, this study proposes a gear fault diagnosis framework that integrates multidomain vibration feature fusion with a back-propagation neural network optimized by the sparrow search algorithm (SSA-BP). Vibration signals collected from a planetary gearbox fault-implantation platform were used to identify seven health states, including normal condition, sun gear pitting, sun gear fracture, sun gear wear, planetary gear pitting, planetary gear fracture, and planetary gear wear. For each signal segment, a 20-dimensional feature vector was constructed by combining nine time-domain features, three frequency-domain features, and eight wavelet packet energy features. SSA was employed to optimize the initial weights and biases of a double-hidden-layer BP neural network before supervised training. Experimental results show that the proposed feature fusion scheme achieved a classification accuracy of 98.30%, outperforming single-domain and pairwise feature combinations. In overall fault classification, SSA-BP obtained 98.26% accuracy, 98.26% macro-recall, 98.27% macro-precision, and 98.26% macro-F1. Moreover, SSA-BP reduced the convergence iterations from 826 to 312 compared with traditional BP and maintained 95.18% accuracy under high-speed and high-load conditions with scarce training samples. These results demonstrate that the proposed SSA-BP model provides improved convergence efficiency, diagnostic accuracy, and cross-condition robustness for intelligent gearbox condition monitoring. Full article

Wind turbine gearbox failures lead to substantial downtime and high maintenance costs. Although condition-monitoring systems are widely used, traditional life-extension methods that simply reduce power output often decrease revenue. Current research frequently treats life optimization and power generation independently, and as such lacks a quantitative link between control strategies and remaining useful life. To address this gap, this paper proposes a novel life-extension strategy that optimizes power generation by dynamically adjusting rotor speed and pitch angle. A transfer learning–long short-term memory model enhanced by multi-source information fusion is developed to predict remaining useful life accurately under conditions with limited fault data. Utilizing real operational data from 2 MW wind turbines in Northeast China, the study quantitatively analyzes the impact of variable-speed and pitch control. The results demonstrate that while both strategies extend life, variable-speed control offers superior effectiveness in improving remaining useful life. Furthermore, maximum power generation is achieved not at full capacity, but when the output is reduced to approximately 70% of the nominal power. At this optimal point, the proposed strategy increases power generation by up to 7.3%. This establishes a dynamic balance between operational safety and economic efficiency, overcoming the limitations of conventional methods. Full article

To investigate the contact mechanical performance of helicopter main gearbox rotor shaft bearings under a complex load spectrum, this study focuses on the contact stress and load-carrying characteristics of bearings operating under high-speed and heavy-load conditions. Based on the rotor shaft system of a helicopter main gearbox and Hertzian contact theory, quasi-static analyses were performed on four tapered roller bearings and one cylindrical roller bearing mounted on the shaft system conducted in Romax. The results indicate that the maximum contact stresses of the bearings do not exhibit sustained high-stress states under most operating conditions. The peak-stress conditions account for only extremely small time proportions in limited cases, namely 0.003429% and 0.025%. The contact stresses on both the inner and outer raceways exhibit a non-uniform distribution along the roller length, with local peak values appearing near the highly loaded roller-raceway contact regions. This suggests that during the design process of the helicopter main gearbox rotor shaft, special attention should be given to this region. The present results provide a theoretical basis for subsequent life-index verification and offer an effective analytical method for the design and validation of such critical components. Full article

Wind turbine (WT) drivetrains are exposed to high dynamic loads, especially caused by grid and converter faults. Those loads increase the frictional energy in the contact zone of the gearbox bearings and gear wheels and, thus, theoretically, the probability of failure of the gearbox before the WTs reach their service lifetime. To increase the robustness against grid and converter faults, gearboxes can be designed to include these as special load cases. The critical parts of gearboxes regarding the influence of grid and converter faults are the components of the fast-rotating gearbox side. This paper introduces an optimization procedure for the high-speed shaft (HSS) components of a WT gearbox, considering several electrical faults as special load cases. The basis for data collection in this work is a validated multi-body simulation (MBS) model of a WT drivetrain. Initially, a test plan is formulated using Latin hypercube sampling (LHS). Based on the simulation results generated with the detailed MBS model according to the defined test plan, computationally efficient surrogate models are derived that link the design parameters with the objectives of the optimization. The surrogate models are employed to optimize the microgeometry of the gearbox. The process is done for several electrical faults. With the optimization, the risk of damage to the gear wheels can be reduced by 28% with a reduced or equal risk of damage to the HSS bearing, depending on the load case. It is also shown via comparison that the optimal design for one critical fault simultaneously leads to a sufficient improvement for other electrical faults (max. 4% reduction in improvement of objectives). Thus, it is sufficient to do the optimization regarding electrical faults only for one critical fault, reducing the necessary computational effort significantly. Full article

Windage power losses (WPLs) can take a noticeable toll on the efficiency of high-speed gear transmissions, especially in helical gears, where complex 3D airflow patterns increase aerodynamic drag. In this work, we measured the WPL of a helical gear using a combination of analytical models, experiments, and CFD simulations. A custom test rig recorded windage losses at four speeds—2000, 3000, 4000, and 5000 rpm—producing values between 1.33 W and 21.67 W. We then compared these results with predictions from commonly used analytical methods (Dawson, Lord, ISO/TR 13593, ANSI/AGMA 6011-I03). These models showed discrepancies of about 25–35%, largely because they were not developed with helical gear geometries in mind. To complement this, CFD simulations carried out in SolidWorks Flow Simulation closely matched the experimental data, with an average deviation of just 4.99%. The combined results highlight the dominant mechanisms contributing to windage losses, assess the accuracy and limitations of each method, and identify the operating regimes where discrepancies are most pronounced. The findings offer a validated framework for predicting windage losses in industrial helical gears and support the development of more efficient gearbox designs. Full article