Whine Noise Research Articles

Research on gear whine evaluation method based on transmission error sensitivity

Abstract The issue of noise control for electric vehicles has gradually become prominent, and gear whine noise, as a key factor, is crucial for improving the overall performance and quality of vehicles. This paper discusses the transmission error, a key parameter leading to gear whine, and analyzes the influence of load and gear micro modification on the distribution of transmission error, to achieve comparison and optimization of different axle plans. In addition, by statistical analysis of the distribution of manufacturing errors, it is concluded that they accord with a normal distribution. Then, the weighted transmission error is obtained considering error probability distribution, which provides a new approach for evaluating the sensitivity of gear whine noise to manufacturing errors, in order to solve the issue of noise consistency in large-scale production.

Rear Axle Whine Reduction by Gear Contact Patch Optimization

In-cab whine is a highly annoying phenomena in all the category of vehicles. The in-cab noise of passenger vehicle with Rear Wheel Drive ( RWD) considered for this study consist of axle whine noise. The whine noise is heard at multiple speeds during Wide Open Throttle (WOT) as well as coasting. To resolve the issue of whine noise, series of measurement are carried out to identify the source and transfer path of the whine. The noise measurement revealed that rear axle pinion mesh order is responsible for in-cab whine. It is confirmed through measurement that the whine is structure borne. The order based operational deflections shapes of rear axle show excessive vibration on differential nose in affected speed zones. It is thus learnt that whine is due to poor contact pattern of pinion and crown wheel of the rear axle. The three resonances in operation range amplify this mesh order resulting in whine. It is decided to work on noise source i.e. gear rather than transfer path. The hypoid gear design is optimized through Tooth Contact Analysis (TCA). The lapping and heat treatment processes of gear manufacturing are modified. The contact pattern of optimized gear is identified on gear tester machine. Significant improvement is observed in contact pattern. The in-cab noise measurement is carried out with optimized hypoid gear and it is found that the whine is completely eliminated.
 Keywords: Rear axle, Whine reduction, Gear contact, Patch optimization, Rear Wheel Drive, Whine Source, Vibration on Transfer Paths, Noise Generation, Hypoid Gear, Heat Treatment

A model-based approach for gear train whine noise reduction by mesh phasing modification

Heavily loaded gear trains are known to produce a characteristic whine noise and vibration signature, which radiates through the bearings producing an undesired noise emission affecting the NVH behavior of the overall machine. This phenomenon is generated by the variable mesh stiffness and the static transmission error of the gear pairs in mesh within the gear train, but its magnitude strongly depends on how the meshing processes combine between each others. In this context, the present work proposes an analytical methodology to predict amplitude and direction of the variable loads applied on the bearings of idle gears, assuming quasi-static conditions. The dissertation demonstrates that the multiple mesh forces produce a variable load on idle gear bearings describing an ellipse whose shape depends on various geometrical parameters of the system. Numerical examples are shown to assess the potentials of the method and highlight how gear train spatial layout and phasing between different meshings may be used during gearbox design projects to limit the emitted noise of the gear train.

Development of a Prediction Model for the Gear Whine Noise of Transmission Using Machine Learning

Development of a Prediction Model for the Gear Whine Noise of Transmission Using Machine Learning

Feasibility of Using a Mobile Device to Identify the Axle Whine Noise in a Vehicle

This article investigates the feasibility of using the built-in microphones of mobile devices to diagnose axle whine noise in a vehicle. Three sound pressure measuring sensors or devices are selected. The first one is a high-end condenser microphone, which is calibrated during the measurements; this data is taken as a reference for the other devices. Then two different types of mobile devices are selected and relative calibrations are carried out. Measurements are first performed inside a hemi-anechoic room; artificially generated sinusoidal and random sound signals are played through a calibrated sound source and data is acquired with all devices. This setup is placed inside a vehicle cabin (for a non-running engine) and measurements are repeated. The onboard entertainment system of the vehicle is used as well in addition to the calibrated sound source. Measurements reveal that one of the mobile devices has superior performance when compared to the other one though calibration improves the performance of the latter. Finally, measurements are performed inside the vehicle cabin while the vehicle is being driven along a certain path to assess the diagnostic performance. The axle whine noise problem in two vehicles is successfully detected by employing an empirical mode decomposition process.

Reduction Technologies of Rear Differential Gear Whine Noise by Controlling Vibration Characteristics of Leaf Suspension

Reduction Technologies of Rear Differential Gear Whine Noise by Controlling Vibration Characteristics of Leaf Suspension

The role of gear layout and meshing phase for whine noise reduction in ordinary geartrains

Whine noise is one of major concern within geared system dynamics. The time-varying bearing forces are transmitted to the gearbox case, which coupled with the whole system assembly provokes an undesired noise emission. The paper proposes an analytical formulation able to forecast the main overall direction and magnitude of bearing reaction forces on idler gear when the geartrain works under quasi-static condition. Moreover, a parametric study is conducted by evaluating the influence of geartrain layout, the meshing phase shift and the amplitudes of meshing forces. Finally, numerical experiments are performed in order to evaluate discrepancies and similarities when the inertial effects become relevant.

An efficient analytical approach to assess root cause of nonlinear electric vehicle gear whine

Noise, vibration, and harshness (NVH) issues pose considerable challenges for electric vehicle powertrain engineers. Gear vibrations generate an intrusive gear whine noise, with significant impact on the sound quality of electric powertrains. Dynamic transmission error (DTE) is the most quantitative indicator for gear NVH. Backlash, time variable meshing stiffness and damping contribute to DTE. Hence, a better understanding of these excitation sources is essential. A gear tribodynamics model is developed using potential energy method to estimate time variable meshing stiffness (TVMS). A fully analytical time-efficient model is proposed for lubricated contact stiffness based on transitions in the regimes of lubrication. The model accounts for the combined effects of surface elasticity and lubricant stiffness. Film thickness and damping coefficients are transiently updated at each instant during meshing cycle. The predictions from this model are compared with measured results from the literature and predicted results from Hertz contact model. The lubricated contact model successfully shows the contribution of the lubricant stiffness to TVMS and its variations with elasticity and viscosity parameters during meshing cycle. Gear harmonic and super-harmonic resonances are accurately estimated in terms of amplitude, frequencies and stiffness softening nonlinearities. Time history responses and phase-displacement diagrams show good agreement with the gear dynamics response at the main harmonic and second super-harmonic frequencies. The proposed model has a reasonable accuracy, significantly better than those from Hertzian contact models, and is considerably time efficient in comparison to numerical EHL solvers.

The Role of Gear Layout and Meshing Phase for Whine Noise Reduction in Ordinary Geartrains

The Role of Gear Layout and Meshing Phase for Whine Noise Reduction in Ordinary Geartrains

Simulation based Approach to Study the Effect of Hypoid Gear Manufacturing Variability on In-Cabin Noise

<div class="section abstract"><div class="htmlview paragraph">With increase in demand for quieter product and reduction in masking noise, axle whine management plays a crucial role in the early product development process. Whine is tonal in nature and humans are more sensitive to tonal memory, hence this makes user to experience a very unpleasant ride which in turn results in bad product credibility. Dynamic mesh force excitation is the cause of the axle whine noise. Critical factors in consideration are gear micro geometry variability, misalignments, temperature of operation and resulting bearing pre-load, operating loads, and structural resonances that carry the excitation to the occupant’s ear. The variability associated with gear micro-geometry plays crucial role during optimization in the quest for robust gear design. This work attempts to study the influence of manufacturing variability on transmission error and dynamic mesh force with the aim of helping design engineers understand and consider manufacturing variability during target setting and gear design.</div></div>

Optimization of gear macro-geometry for reducing gear whine noise in agricultural tractor transmission

Agricultural tractors generate various noise sources, such as the engine, transmission, and hydraulic systems. In particular, tractors generate considerable transmission gear whine noises during operation, and such noises need to be reduced for the driver’s comfort. The gear whine noise level is related to peak-to-peak static transmission errors (PPSTEs), and the PPSTE can be minimized through the gear macro-geometry optimization method. Here, we optimized the gear macro-geometry of a 75-kW agricultural tractor transmission through a genetic algorithm (non-dominated sorting genetic algorithm III; NSGA-III) to minimize PPSTEs. The two gear pairs were optimized to maintain the gear mesh efficiency at similar levels and to minimize the PPSTE to less than 25 % of the existing gear specifications. To determine the improvement in noise, the noise levels were evaluated and compared using a 3-axis dynamometer tester. The overall noise level in the transmission operating range was found to reduce by 3.1 dBA, and all the noise levels of the gear harmonic components were reduced effectively.

Analysis of Vibration and Noise for the Powertrain System of Electric Vehicles under Speed-Varying Operating Conditions

Whine noise from the electric powertrain system of electric vehicles, including electromagnetic noise and gear-meshing noise, significantly affects vehicle comfort and has been getting growing concern. In order to identify and avoid whine problems as early as possible in the powertrain development process, this paper presents a vibration and noise simulation methodology for the electric powertrain system of vehicles under speed-varying operating conditions. The electromagnetic forces on the stator teeth of the motor and the bearing forces on the gearbox for several constant-speed operating conditions are obtained first by electromagnetic field simulation and multi-body dynamic simulation, respectively. Order forces for the speed-varying operating condition are generated by interpolation between the obtained forces, before they are applied on the mechanical model whose natural modes have been calibrated in advance by tested modes. The whine noise radiated from the powertrain is then obtained based on acoustic boundary element analysis. The simulated bearing forces indicate that the overlooking of the motor torque ripple does not result in significant loss in simulation accuracy of electromagnetic noise. The simulation results and tested data show good consistency, with the relative frequency deviation of local peaks being less than 8% and the error of the average sound pressure level (SPL) being mostly below 10 dB (A).

Robust Development of Electric Powertrain NVH for Compact Electric SUV

<div class="section abstract"><div class="htmlview paragraph">Electric vehicles (EV’s) present new challenges to achieving the required noise, vibration & harshness performance (NVH) compared with conventional vehicles. Specifically, high-frequency noise and unexpected noise phenomenon, previously masked by the internal combustion engine can cause annoyance in an EV. Electric motor (E-motor) whine noise caused by electromagnetic excitation during E-motor operation is caused by torque ripple and radial excitation. Under high speed and high load operating conditions, the overall sound level may be low, however high frequency whine noise can impair the vehicle level NVH performance. An example of a previously masked unexpected noise phenomenon is a droning noise that can be caused by manufacturing quality variation of the spline coupling between the rotor shaft of the E-motor and the input shaft of the reducer. It is dominated by multiple higher orders of the E-motor rotation frequency.</div><div class="htmlview paragraph">In this study, the high speed and high load condition whine noise problem was reproduced through electromagnetic and structural analysis. The countermeasures (E-motor geometry refinements to reduce the excitations and mechanical system transfer path modifications to reduce the vibration response) were defined and the effects investigated. Mechanical system modification to improve NVH performance without increasing the mass is challenging. However, E-motor air-gap geometry optimization, such as slot opening modulation and rotor notch modifications achieved significant noise reduction without critical trade-off of other performance.</div><div class="htmlview paragraph">This paper also describes the basic improvement plan proposed through the simulation of the droning noise behavior. The main two manufacturing errors (pitch error in the spline coupling and the alignment error between the rotor and the gearbox shafts) that are responsible for the unexpected droning noise were identified. Using simulation it was shown that the droning noise can be reduced through improved quality control and tolerance design optimization of factors such as axis self-alignment and spline gear tooth quality.</div></div>

Evaluation and modeling of automotive transmission whine noise quality based on MFCC and CNN

The sound quality of automotive transmission noise strongly influences passengers’ psychological and physiological perceptions. To predict the sound quality of automotive transmission noise, a uniform deceleration noise test with two automotive transmissions has been conducted in a semi-anechoic room. All recorded transmission noise signals have been divided into 5 s segments and subsequently evaluated subjectively through the rating scales test by a jury. In addition, a novel prediction method, namely, Mel-Frequency Cepstral Coefficients-based convolutional neural networks (MFCC-CNN), which substitute the softmax classification layer for the linear transform prediction layer at the output of the general CNN’s structure and take MFCC feature map as input, has been proposed to predict the transmission sound quality. MFCC's distinguishing performance on sound quality has been validated. The parameter selection of the MFCC-CNN model has been compared and studied using a grid search. In addition, three conventional machine-learning-based methods have been introduced to enable a comparison of the performance with the newly developed MFCC-CNN. The results show the following: (1) In different transmission gears, MFCC features can distinguish different sound quality noises. (2) The accuracy of the proposed MFCC-CNN sound quality prediction approach are better than those of the 3 other referenced methods. (3) The correlation coefficient of prediction value from MFCC-CNN is more than 0.95 and the mean absolute error of prediction value from MFCC-CNN is less than 0.55, which fully meets the need of engineering. Finally, the newly proposed MFCC-CNN approach may be extended to address other vehicle noises in the future.

Classifying, Predicting, and Reducing Strategies of the Mesh Excitations of Gear Whine Noise: A Survey

Gear whine noise has attracted increasing attention from researchers in both the academe and the industry over the past two decades. The wide range of research topics demonstrates that there is a huge technical challenge in understanding the source-path-receiver mechanisms deeply and predicting the gear whine noise precisely. Thoroughly understanding the sources of gear whine noise is the first step to solving this issue. In this paper, the authors summarize a certain number of published articles regarding the sources of gear whine noise. The excitations of gear whine noise are classified into three groups: transmission error along the line of action direction, frictional excitations along the off-line of action direction, and shuttling excitation along the axial direction. The mechanisms, characteristics, predicting approaches, measuring methods, and decreasing strategies for these excitations are summarized. Current research characteristics and future research recommendations are presented at the end.

Study on the Reduction of Gear Whine Noise in Diesel Engine Gear Train

Study on the Reduction of Gear Whine Noise in Diesel Engine Gear Train

Robust optimisation of dynamic and NVH characteristics for compound power-split hybrid transmission

In this paper, vibro-acoustic characteristics of a power-split hybrid transmission including a compound planetary gear set are investigated by numerical procedure and refined system dynamics modelling. For validation of the numerical predictions, bench tests are performed for dynamic and acoustic responses of the hybrid transmission, contribution rates of acoustic radiation power induced due to the planetary gears, support bearings, transmission shafts and the gearbox housing are estimated. In improving the noise, vibration and harshness (NVH) performance of the transmission during hybrid vehicle acceleration, traction torques of the motors against the planetary gear parametric resonance are formulated and an optimal control strategy is proposed. By real road NVH test results acquired on board of the midsize hybrid car, it is demonstrated that a significant reduction of the planetary gear whine noise is achieved. As a result, numerical approaches applied to establish relationships between torques of the two traction motors and parametric excitations of the compound planetary gear train are experimentally validated.

Parameter Study and Improvement of Gearbox Whine Noise in Electric Vehicle

Gearbox whine noise can seriously reduce the interior sound quality in an electric passenger car. In this work, a six-degree-of-freedom (6-DOF) dynamic model of a helical gear system was constructed and the mechanism for generation of whine noise was analyzed. The root cause of the problem was found through noise, vibration and harshness (NVH) testing of the gearbox and the vehicle. A rigid-elastic coupling dynamics model of the reducer assembly was then developed. The accuracy of the model was then validated via modal testing. The structure-borne noise of the reducer under full acceleration conditions was predicted using the acoustic structure coupling model and the rigid-elastic coupling model of the reducer. Gear parameters including the pressure angle, the helix angle and the contact ratio were studied to determine their effects on the whine noise. Gear tooth microgeometry modification parameters were then optimized to reduce the transmission error of the first pair of meshing gears. Finally, the whine noise from the gearbox was eliminated.

Structurally Integrated Piezoelectric Actuators for Reducing Rear Axle Gear Whine Noise

The gear whine phenomenon in vehicles is a well‐known acoustic issue which often needs a development of individual measures. Especially in rear‐wheel and four‐wheel drive vehicles, the acoustical optimization of the rear axle leads to the major goal conflict: improvement of the vibrational isolation of the rear axle versus excellent driving dynamics of the vehicle. A promising solution for this issue is described in this paper. The key objective is to reduce the noise contributions of the rear axle using an active vibration control system (AVC) based on piezoelectric actuators on the transfer path from the axle into the vehicle. In the first part of the paper, the development process of the AVC system is described. In the second part of the paper, a rear axle test bench is presented which is used to validate the simulation results. A multi component control algorithm has been implemented in order to get an optimum reduction of relevant forces at the mounting points to the vehicle using one or more actuators. In preparation for a series launch of the AVC system, an assembly concept for applying the piezoelectric actuators to the rear sub frame in a series production process is presented.

흡음재특성에 따른 전기자동차 화인 음질 평가법

흡음재특성에 따른 전기자동차 화인 음질 평가법