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One of the practical consequences of the development of low CO₂ emission cars is that many of the traditional NVH sound engineering processes no longer apply and must be revisited. Different and new sound sources, new constraints on vehicle body design (e.g., due to weight) and new sound perception characteristics make that the NVH knowledge built on generations of internal combustion-powered vehicles cannot be simply transferred to Hybrid and Electric Vehicles (HEV). Hence, the applicability of tools must be reviewed and extensions need to be developed where necessary. This paper focuses on sound synthesis tools as developed for ICE-powered vehicles. Because of the missing masking effect and the missing intake and exhaust noise of the Internal Combustion Engine (ICE) in electric vehicles, on one hand electric vehicles are quieter than traditional vehicles.

While CAE methods allow improving nominal product design using virtual prototypes, uncertainty and variability in properties and manufacturing processes lead to scatter in actual performances. Uncertainty must hence be incorporated in the CAE process to guarantee the robustness and reliability of the design. This paper presents an overview of uncertainty-based design in automotive and aerospace engineering. Fuzzy methods take uncertainty into account, whereas reliability analysis and a reliability-based design optimization framework can deal with variability. Key enabling technologies to alleviate the computational burden, such as workflow automation, substructuring and design of experiments, are discussed, and industrial applications are presented.

Acoustic performance of vehicle engines is a real challenge for powertrain design engineers. Quiet engines are required to reduce noise pollution and satisfy pass-by noise regulations, but also to improve the driving comfort. Simulation techniques such as the Boundary Element Method (BEM) have already been available for some time and allow predicting the vibro-acoustic response of engines. Although the accuracy of these simulation techniques has been proven, a challenge still remains in the required computation time. Given the large amount of speeds for a full engine run-up and the need to cover a large frequency range, computation times are significant, which limits the possibility to perform many design iterations to optimize the system. In 2001, Acoustic Transfer Vectors (ATV) [1] have been presented to adequately deal with multiple rpm. The ATV provide the acoustic response for unit surface velocities and are therefore independent from the engine's actual surface vibrations.

This paper discusses the requirement for CAE methods to properly take into account the variabilities and uncertainties that characterizes design input properties without leading to oversized structures. Optimizing the structural behaviour while taking into account expected variability and uncertainty in the structure and its model, requires the adoption of a reliability-based design optimization approach. This paper starts with an overview of the problem of simulation uncertainty. The key focus is then on the description of the most commonly used methods and enabling tools for reliability analysis and reliability based design optimization. The theory is illustrated by real automotive design problems.

A key element to bring research advances on intelligent materials to industrial use is that the product CAE models must support such solutions. This involves modeling capabilities for intelligent material systems, sensor and actuator components, control systems as well as their integration in system-level application designs. The final result will then be a multi-attribute optimization approach integrating noise and vibration performance with reliability, durability and cost aspects. As no single integrated solution will fulfill all requirements of the various material and control approaches, the focus of the research is on the use, combination and extension of existing codes and tools.

Vibro-acoustical optimization of vehicles is a complex task, due to the many interactions that exist between subcomponents and car body in a broad acoustical frequency range. The goal of this paper is to present a view on the different experimental methodologies for vibro-acoustical analysis, that approach the vehicle as a source, transfer and receiver system. This approach focuses on the use of transfer path and source identification techniques, both for structure-borne and air-borne contribution analysis, and on the use of modeling techniques as there are vibro-acoustical modal analysis, FRF based substructuring and experimental statistical energy analysis techniques. It is explained what the main focus is of each of the techniques, where they can be used in the vibro-acoustical optimization process and in which frequency ranges they are useful.

The subjective quality of sounds is a topic of increasing importance in the automotive industry. The first consideration is to describe the perceptual characteristics of this quality by means of jury tests or appropriate metrics. Once a NVH problem is determined in terms of an appropriate Sound Quality description, an in-depth analysis of the underlying physical phenomena must be made and engineering solutions newel to be proposed and validated This involves: • the detailed analysis of the signal structure in the time, frequency and order domain and identifying the signal Components Critical to the relevant sound quality dimension • the Correlation of the critical signal components to specific sources noise or vibration transmission paths and vibro-acoustic system characteristics. Ultimately this should lead to the prediction of the effect of feasible modifications in sound quality terms through the use of engineering models.

One of the scientific fields where, for already more than 20 years, system identification plays a crucial role is this of structural dynamics and vibro-acoustic system optimization. The experimental approach is based on the “Modal Analysis” concept. The present paper reviews the test procedure and system identification principles of this approach. The main focus though is on the real problems with which engineers, performing modal analysis on complex structures on a daily basis, are currently confronted. The added value of several new testing approaches (laser methods, smart transducers…) and identification algorithms (spatial domain, subspace, maximum likelihood,..) for solving these problems is shown. The discussed elements are illustrated with a number of industrial case studies.

Vehicles with electrified powertrains are being introduced at an increasing pace. On the level of interior sound, one is often inclined to assume that NVH problems in EV have disappeared together with the combustion engine. Three observations demonstrate that this is not the case. First of all, only the dominant engine sound disappears, not the noise from tire, wind or auxiliaries, which consequently become increasingly audible due to the removal of the broadband engine masking sound. Secondly, new noise sources like tonal sounds from the electro-mechanical drive systems emerge and often have, despite their low overall noise levels, a high annoyance rating. Thirdly, the fact that engine/exhaust sounds are often used to contribute to the “character” of the vehicle leads to an open question how to realize an appealing brand sound with EV. Hybrid vehicles are furthermore characterized by mode-switching effects, with impact on both continuity feeling and sound consistency problems.

15 years of NVH applications make Transfer Path Analysis (TPA) appear a commodity tool. But despite the fact that TPA is today successfully used in a large variety of applications in automotive and mechanical industries, its main bottleneck remains the huge measurement time to build the full TPA model. This paper presents a new TPA method that provides a good compromise between path accuracy and measurement time. The method is also referred to as OPAX. The key idea of OPAX is the use of simplified parametric load models with limited number of model parameters. The main advantage of this is that one should measure only a small amount of FRF data to identify the operational loads. This drastically reduces measurement time and efforts. In addition to this, the OPAX method does not require mount stiffness data and allows a simultaneous identification of structural and acoustic paths.

Despite the fact that Transfer Path Analysis (TPA) is a well known and widely used NVH tool it still has some hindrances, the most significant being the huge measurement time to build the full data model. For this reason the industry is constantly seeking for faster methods. The core concepts of a novel TPA approach have already been published in a paper at the ISMA 2008 Conference in Leuven, Belgium. The key idea of the method is the use of parametric models for the estimation of loads. These parameters are frequency independent as opposed to e.g. the classical inverse force identification method where the loads have to be calculated separately for each frequency step. This makes the method scalable, enabling the engineer to use a simpler model based on a small amount of measurement data for quick troubleshooting or simply increase accuracy by a few additional measurements and using a more complex model.