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The increasing trend toward electric and hybrid-electric vehicles (HEVs) has created unique challenges for NVH development and refinement. Traditionally, characterization of in-vehicle powertrain noise and vibration has been assessed through standard operating conditions such as fixed gear engine speed sweeps at varied loads. Given the multiple modes of operation which typically exist for HEVs, characterization and source-path analysis of these vehicles can be more complicated than conventional vehicles. In-vehicle NVH assessment of an HEV powertrain requires testing under multiple operating conditions for identification and characterization of the various issues which may be experienced by the driver. Generally, it is necessary to assess issues related to IC engine operation and electric motor operation (running simultaneously with and independent of the IC engine), under both motoring and regeneration conditions.

This work presents an application of airborne source path contribution analysis with emphasis on prediction of wideband sounds inside a cabin from measurements made around a stand-alone engine. The heart of the method is a time domain source path receiver technique wherein the engine surface is modeled as a number of source points. Nearfield microphone measurements and transfer functions are used to quantify the source strengths at these points. This acoustic engine model is then used in combination with source-to-receiver transfer functions to calculate sound levels at other positions, such as at the driver's ear position. When combining all the data, the in-cabin engine sound can be synthesized even before the engine is physically installed into the vehicle. The method has been validated using a powertrain structure artificially excited by several shakers playing band-limited noise so as to produce a complicated vibration pattern on the surface.

Active noise control (ANC) technique with the filtered-x least mean square (FXLMS) algorithm has proven its efficiency and drawn increasingly interests in vehicle noise control applications. However, many vehicle interior and/or exterior noises are exhibiting non-Gaussian type with impulsive characteristic, such as diesel knocking noise, injector ticking, impulsive crank-train noise, gear rattle, and road bumps, etc. Therefore, the conventional FXLMS algorithm that is based on the assumption of deterministic and/or Gaussian signal may not be appropriate for tackling this type of impulsive noise. In this paper, an ANC system configured with modified FXLMS (MFXLMS) algorithm by adding thresholds on reference and error signal paths is proposed for impulsive noise control. To demonstrate the effectiveness of the proposed algorithm, an experimental study is conducted in the laboratory.

An enhanced, frequency domain filtered-x least mean square (LMS) algorithm is proposed as the basis for an active control system for treating powertrain noise. There are primarily three advantages of this approach: (i) saving of computing time especially for long controller’s filter length; (ii) more accurate estimation of the gradient due to the sample averaging of the whole data block; and (iii) capacity for rapid convergence when the adaptation parameter is correctly adjusted for each frequency bin. Unlike traditional active noise control techniques for suppressing response, the proposed frequency domain FXLMS algorithm is targeted at tuning vehicle interior response in order to achieve a desirable sound quality. The proposed control algorithm is studied numerically by applying the analysis to treat vehicle interior noise represented by either measured or predicted cavity acoustic transfer functions.

Past studies have shown that NVH CAE tire model quality is not adequate to correctly capture a mid-frequency range (100-300 Hz). A new methodology has been developed to estimate tire forces that are independent of dynamic characteristics of vehicle suspension and rig test fixture. The forces are called tire blocked forces and defined as a force generated by a tire/wheel system whose boundary condition is constrained. The tire blocked force is estimated by removing the dynamic effect of the tire force measurement fixture. The blocked forces can be applied to CAE models to predict vehicle road NVH responses. This new method can also be used as a target setting tool. Tire suppliers can check the blocked tire forces from the rig testing data against a force target before they submit tires to automotive manufacturers for evaluations on a prototype vehicle.

The exhaust system is one of the major P/T systems for sound quality tuning. The many varieties in exhaust pipe routing and the flexibility in muffler design make it possible to design an exhaust system to deliver tailpipe sound for specific sound quality requirements. It is essential that the tailpipe sound be balanced with other P/T sound to yield the overall sound targets. The primary contribution of an exhaust system is the firing and sub-firing orders. The typical tailpipe sound target contains banded targets for “good” orders as well as “do-not-exceed” targets for the rest. Every order target needs to be met in order to yield the right tailpipe sound. In most cases, the pipe routing and the muffler volumes of mufflers are dictated by package constraints, however, the internal design of muffler with a given volume can create quite different tailpipe sounds.

A method to create a CAE load by utilizing the vibration motions at structure attachments has been developed. This method employs the concept of enforced motion as the constraints of boundary conditions to create an equivalent input force/moment matrix for a sub-structure with multi-point attachments. The main assumption is that motions at the attachments of the sub-structure should be the same as the known motions of the main structure under the generated input load. The key concept of the developed methodology is the calculation of the input dynamic compliance matrix for sub-structure attachment locations. This method is developed to create a system level input load to be used for squeak and rattle CAE analysis on a component or sub-system. It can also be used for minor component design change evaluation using only the component CAE model, yet as if it is assembled in the vehicle.

Panel acoustic contribution analysis (PACA) is an advanced engineering tool to improve the NVH quality of vehicles. Using PACA areas of vehicle body panels are categorized according to their contribution to the total sound. Positive contribution areas increase the sound level as vibration amplitude increases, negative contribution areas decrease the sound level as vibration amplitude increases, and neutral areas have no significant effect on the sound level. This knowledge is important to guide vehicle NVH refinement. This paper presents the technical approach of PACA and the results of an experiment used to validate the PACA techniques. Vehicle application results to improve NVH quality and reduce weight are also included.