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Automotive companies are studying to add extra value in their vehicles by enhancing powertrain sound quality. The objective is to create a brand sound that is unique and preferred by their customers since quietness is not always the most desired characteristic, especially for high-performance products. This paper describes the process of developing a brand powertrain sound for a high-performance vehicle using the DFSS methodology. Initially the customer's preferred sound was identified and analyzed. This was achieved by subjective evaluations through voice-of-customer clinics using vehicles of similar specifications. Objective data were acquired during several driving conditions. In order for the design process to be effective, it is very important to understand the relationship between subjective results and physical quantities of sound. Several sound quality metrics were calculated during the data analysis process.

Powertrain noise is a significant factor in determination of the overall vehicle refinement expected by today's discriminating automotive customer. Development of a powertrain to meet these expectations requires a thorough understanding of the contributing noise sources. Specifically, combustion noise greatly impacts the perception of sound levels and quality. The relevance of combustion noise development has increased with the advent of newer efficiency-driven technologies such as direct injection or homogeneous charge compression ignition. This paper discusses the application of a CSL (Combustion Sound Level) analysis-a method for the identification and optimization of combustion noise. Using CSL, it is possible to separate mechanical and combustion noise sources.

It is commonly accepted that refined “powertrain sound quality” is essential to the development of a vehicle which will be well received by today's discriminating automotive customer. However, though there are several metrics which correlate well with a subjective impression of powertrain level inputs, what is ultimately important is the sound quality at driver's ear. Vehicle level powertrain sound quality is influenced by the powertrain noise and vibration (source) as well as the vehicle airborne and structureborne transfer functions (path). In development as well as benchmarking activities, it can be difficult to separate the influence of source and path on overall vehicle sound quality.

Increased customer expectation for NVH refinement creates a significant challenge for the integration of Diesel powertrains into passenger vehicles that might have been initially developed for gasoline engine applications. A significant factor in the refinement of Diesel powertrain sound quality is calibration optimization for NVH, which is often constrained by performance, emissions and fuel economy requirements. Vehicle level enablers add cost and weight to the vehicle and are generally bounded by vehicle architecture, particularly when dealing with a carry-over vehicle platform, as is often the case for many vehicle programs. These constraints are compounded by the need to make program critical sound package content decisions well before the availability of prototype vehicles with the right powertrain. In this paper, a case study on NVH development for integration of a light duty Diesel powertrain is presented.

The definition of vehicle and powertrain level targets is one of the first tasks toward establishing where a vehicle will reside with respect to the current or future state of industry. Though development of sound quality metrics is ongoing to better correlate objective data with subjective assessments, target setting at the vehicle level is relatively straightforward. However, realization of these targets depends on effective cascading to system and component levels. Often, component level targets are derived based on experience from earlier development programs, or based on selected characteristics observed during component level benchmarking. An approach is presented here to complement current strategies for component level target definition. This approach involves a systematic concept for definition of component NVH targets based on desired vehicle level performance and a consequent target break down.

Relative to Combustion Engine vehicles, electric powertrains are a blank canvas for sound. There are an increasing number of applications where sound is added to enhance the driving experience and increase pedestrian safety. In Hybrid vehicles, the combustion engine sound is not always present and must properly blend in with any additional sound added to the vehicle. Vehicle manufacturers have an opportunity to reinforce their brand identity through the addition of the perfect, target sound. Each brand, market segment, and powertrain require unique sounds. In addition, shuttle or ride sharing applications highlight the need for added sound during other scenarios to reinforce the brand sound. Traditional sound quality measurements and preference testing are very limited in defining the perfect sound due to the subjective nature of sound design.

The definition of vehicle and powertrain level NVH targets is one of the first tasks toward establishing where a vehicle's NVH behavior will reside with respect to the current or future state of industry. Realization of vehicle level NVH targets relies on a combination of competitive powertrain (source) and vehicle (path) NVH performance. Assessment of vehicle NVH sensitivity is well understood, and can be accomplished through determination of customer interface NVH response to measured excitations at the source input locations. However, development of appropriate powertrain source targets can be more difficult, particularly related to sound quality. This paper discusses various approaches for definition of powertrain targets for sound quality, with a specific focus on impulsive noise.

Environmental noises such as wind, road, powertrain, and HVAC noise are important aspects to consider when implementing a hands-free terminal for mobile phone calling from within a car. Traditionally, these environmental noises have been exclusively considered for driver comfort; however, with the introduction of the hands-free terminals (HFT) and increasing consumer demand relative to mobile phone call quality, a broader implication of high background noise levels should be considered. HFT algorithm development and implementation can and does provide a high level of background noise suppression to mitigate these concerns, but this is often done at the expense of computational power and cumulative delay during a phone call. The more advantageous solution would be to address the problem from a source and path perspective with emphasis on reduction of noise in the frequency bands which most influence call quality performance.

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.

It is a common practice to conduct NVH fingerprinting and benchmarking assessments at the powertrain level, to understand source level noise and vibration. To assess the NVH influence of engine, e-motor, and transmission, sub-system testing is often conducted in addition to full powertrain testing. These powertrain or sub-system investigations provide valuable information regarding the status of “source” level excitations relative to targets and / or competitive powertrains. In the case of transmissions and e-machines, it is particularly important to understand source level tonal content and how this will be perceived at the vehicle level. However, variation in component design results in differences in order content, which complicates the process of objectively comparing multiple products. Multiple methods are presented here for characterizing tonal content of transmission and e-machines, based on assessments conducted in a component hemi-anechoic dynamometer test cell.