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The need for improved axle NVH integration has increased significantly in recent years with industry trends toward full-time and automatic four wheel drive (4wd) systems. Along with seamless 4wd operation, quiet performance has become a universal expectation. Axle gear-mesh noise can be transmitted to the vehicle passenger compartment through airborne paths (not discussed in this paper) and structure-borne paths (the focus of this paper.) A variety of mounting configurations are used in an attempt to provide improved axle isolation and reduce structure-borne transmission of gear-mesh noise. The configuration discussed in this paper is a 4-point vertical mount design for an Independent Front Drive Axle (IFDA). A significant benefit of this configuration is improved isolation in the range of drive torques where axle-related NVH issues typically exist.

This paper presents the principles of robustness design of axle system dynamics to reduce vehicle system related axle gear whine. Through examining the physics of the axle gear noise, the influence of the system dynamics are identified as two parts, i.e., the dynamics mesh force generated at the gear meshing per unit gear mesh motion variation; and the force transmissibility from mesh to the axle housing, and then further to the bracket attachments. The noise sensitive design parameters are identified and discussed. Component design requirements are proposed to minimize the system resonances in the typical gear mesh frequency range. The use of FEA models for system understanding and further design tuning is illustrated.

An application of variation simulation for predicting vehicle interior driveline vibration is presented. The model, based on a “Monte Carlo”-style approach, predicts the noise, vibration and harshness (NVH) response of the vehicle driveline based on distributions of imbalance and runout derived from manufacturing production variation (the forcing function) and the vehicle's sensitivity to the forcing function. The model is used to illustrate the change in vehicle interior vibration that results when changes are made to production variation for runout and imbalance of driveline components, and how those same changes result in different responses based on vehicle sensitivity.

The installation of various liners into the propeller shaft tube is a traditional driveline NVH treatment to attenuate driveline vibration. The most commonly used liners include rolled paper, C-cut cardboard, corrugated cardboard, etc. These traditional liner treatments are expected to provide damping to the driveline system to reduce the vibration levels. However their added level of damping and effectiveness to the driveline system are limited, particularly when dealing with driveline gear mesh vibration and noise. This paper presents a novel type of liner treatment - tunable liners. The liner is designed such that it functions as a tuned dynamic vibration absorber. Through proper design of the liner, it can be tuned for bending and torsion modes at the same time. The liner design parameters and their impact on the frequency tuning are analyzed and studied through both physical testing and FEA analysis.

Today's emerging 4-wheel-drive and all-wheel-drive vehicle architectures have presented new challenges to engineers in achieving low driveline system noise. In the meantime there's also a constant pressure from increasingly stringent noise level requirements. A driveline system's NVH (noise, vibration and harshness) performance is controlled by various noise sources and mechanisms. The common noise issues include the axle gear whine, driveline imbalance/run-out, 2nd order kinematics, engine torque fluctuation, engine idle shake etc. Unfortunately various design alternatives may improve some NVH performance attributes while degrading others. It is important to balance the requirements for these noise sources to achieve an optimized driveline system NVH. However, very little literature is found on this topic. In this paper, discussions on methodologies in balancing these different driveline NVH requirements are presented.

This paper presents a study of axle system NVH (noise, vibration and harshness) performance using DFSS (Design for Six Sigma) methods with the focus on the system robustness to typical product variations (tolerances / manufacturing based). Instead of using finite element as the simulation tool, a lumped parameter system dynamics model developed in Matlab/Simulink is used in the study, which provides an efficient way in conducting large size analytical DOE (Design of Experiment) and stochastic studies. The model's capability to predict both nominal and variance performance is validated with vehicle test data using statistical hypothesis test methods. Major driveline system variables that contribute to axle gear noise are identified and their variation distributions in production are obtained through sampling techniques.

This paper focuses on a P3 HEV drivetrain for a performance vehicle with a 2-speed gear shift system. The drivetrain NVH performance varies at different gear and different loading conditions, therefore creates a new level of challenges in optimizing the system. This paper presents the methodologies in optimizing the system NVH, including noise sources from both gearbox and eMotor. CAE modeling methods are discussed and illustrated for their usage in optimizing both structural and acoustic responses. Reasonable correlations to test data are achieved and presented.

Alternative powertrains, in particular electric and plug-in hybrids, create a wide range of unique and challenging NVH (noise, vibration & harshness) issues in today's automotive industry. Among the emerging engineering challenges from these powertrains, their acoustic performances become more complicated, partially due to reduced ambient masking noise level and light weight structure. In addition, the move away from conventional displacement engines to electrical drive units (EDU) has created a new array of NVH concerns and dynamics, which are relatively unknown as compared to the aforementioned traditional setups. In this paper, an NVH optimization study will be presented, focusing on four distinct factors in electric drive unit gear mesh source generation and radiation: EDU housing and bearing dynamics, gear geometry, EDU shafting torsional dynamics, and EDU housing structure. The study involves intensive FEA modeling/analyses jointly with physical validation tests.

The American Axle & Manufacturing Inc. driveline dynamometer provides immense value for experimental validation of product NVH performances. It has been intensively used to evaluate product design robustness in terms of build variations, mileage accumulation, and temperature sensitivity. The current driveline dynamometer input motor system has multiple torsional modes which create strong coupling with test part gear mesh dynamics. Mechanical Engineering seniors at Lawrence Technological University designed, fabricated, and validated a mechanism to decouple the driveline dynamics from the driveline dynamometer dynamics. The student-designed decoupler mechanism is presented with experimental validation of effectiveness in decoupling driveline dynamometer dynamics from the driveline under test.

With the trend of electric drive unit gradually replacing ICE powertrain, in additional to gear noise, the motor noise has become a new major NVH challenge. These tonal noises are easier to be detected in the pure electric vehicle that has no masking effect of ICE powertrain. Therefore, how to accurately predict and reduce the motor noise is a key to solve the problem. The accuracy of calculated motor stator modes determines the accuracy of motor noise prediction. This paper presents a simulation method based on the finite element model and defined orthotropic material properties of the stator. The material property parameters of the stator core and hairpin windings are reverse-engineered through iterative correlations to test data. High accuracy FEA model is achieved that can determine the stator mode shapes and frequencies of this hairpin motor accurately, which provides a reliable and effective approach for the motor noise prediction and optimization studies.