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Noise concerns regarding snowmobiles have increased in the recent past. Current standards, such as SAE J192 are used as guidelines for government agencies and manufacturers to regulate noise emissions for all manufactured snowmobiles. Unfortunately, the test standards available today produce results with variability that is much higher than desired. The most significant contributor to the variation in noise measurements is the test surface. The test surfaces can either be snow or grass and affects the measurement in two very distinct ways: sound propagation from the source to the receiver and the operational behavior of the snowmobile. Data is presented for a known sound pressure speaker source and different snowmobiles on various test days and test surfaces. Relationships are shown between the behavior of the sound propagation and track interaction to the ground with the pass-by noise measurements.

Air spring systems gain more and more popularity in the automotive industry and with the ever growing demand for comfort nowadays they are almost inevitable. Some significant advantages over conventional steel springs are appealing for commercial vehicles as well as for the modern passenger vehicles in the luxury class. Current production air spring systems exist in combination with hydraulic shock absorbers (integrated or resolved). An alternative is to use the medium air not only as a spring but also as a damper: a so-called air spring air damper. Air spring air dampers are force elements which could be a great step for the chassis technology due to their functionality (frequency selectivity, load levelling, load independent vibration behaviour, load dependent damping). Some of their design which avoid dynamic seals by the using of rubber bellows contribute to a better ride comfort.

Low interior noise levels in combination with a comfortable sound is an important task for passenger cars. Due to the reduction of many noise sources over the last decades, nowadays tire-road noise has become one of the dominant sources for the interior noise. Especially for manufactures of luxury cars, the reduction of tire-road noise is a big challenge and therefore a central part of NVH development. The knowledge of the noise transmission behavior based on the characteristics of the relevant sources is a fundamental of a modern NVH - development process. For tire-road noise the source characteristics can be described by wheel forces and radiated airborne noise. In combination with the related vehicle transfer functions it is possible to describe the noise transmission behavior in detail. A method for estimating wheel forces and radiated airborne noise is presented.

This paper describes the possibility to resolve aeroacoustic feedback with a commercial 2nd/3rd order finite volume CFD code [1]. After a first comparison to a NACA 0012 test case, tonal noise components of a realistic automotive side view mirror are validated with in-house wind tunnel measurements. A zonal RANS/LES approach is used to ensure a realistic flow around the exterior side mirror mounted on a Mercedes-Benz passenger car. The provided compressible large eddy simulations are using non-reflecting boundary conditions in combination with a sponge zone approach to reduce hydrodynamic fluctuations and are in great accordance to measurements. The possibility of localizing and investigating the underlying feedback mechanism enables the chance for a targeted design of different appropriate remedies, which are finally confirmed by means of experimental comparison.

With the reduction of engine and road noise, wind has become an important source of interior noise when cruising at highway speed. The challenges of weight reduction, performance improvement and reduced development time call for stronger support of the development process by numerical methods. Computational Fluid Dynamics (CFD) and finite element (FE) vibroacoustic computations have reached a level of maturity that makes it possible and meaningful to combine these methods for wind noise prediction. This paper presents a method used for coupling time domain CFD computations with a finite element vibroacoustic model of a vehicle for the prediction of low-frequency wind noise below 500 Hz. The procedure is based on time segmentation of the excitation load and transformation into the frequency domain for the vibroacoustic computations. It requires simple signal processing and preserves the random character as well as the spatial correlation of the excitation signal.

The object of the validation study presented in this paper is a generic vehicle, the so-called SAE body, developed by a consortium of German car manufacturers (Audi, Daimler, Porsche, Volkswagen). Many experiments have been performed by the abovementioned consortium on this object in the past to investigate its behavior when exposed to fluid flow. Some of these experiments were used to validate the simulation results discussed in the present paper. It is demonstrated that the simulation of the exterior flow is able to represent the transient hydrodynamic structures and at the same time both the generation of the acoustic sources and the propagation of the acoustic waves. Performing wave number filtering allows to identify the acoustic phenomena and separate them from the hydrodynamic effects. In a next step, the noise transferred to the interior of the cabin through the glass panel was calculated, using a Statistical Energy Analysis approach.

Aero-vibro-acoustic prediction of interior noise associated with exterior flow requires accurate predictions of both fluctuating surface pressures across the exterior of a vehicle and efficient models of the vibro-acoustic transmission of these surface pressures to the interior of a vehicle. The simulation strategy used in this paper combines both CFD and vibro-acoustic methods. An accurate excitation field (which accounts for both hydrodynamic and acoustic pressure fluctuations) is calculated with a hybrid CAA approach based on an incompressible unsteady flow field with an additional acoustic wave equation. To obtain the interior noise level at the driver's ears a vibro-acoustic model is used to calculate the response of the structure and interior cavities. The aero-vibro-acoustic simulation strategy is demonstrated for a Mercedes-Benz S-class and the predictions are compared to experimental wind tunnel measurements.

The driving comfort is an important factor for buying decisions. For the interior noise of battery electric vehicles (BEV) high frequency tonal orders are characteristic. They can for example be caused by the gearbox or the electric drive and strongly influence the perception and rating of the interior noise by the customer. In this contribution methods for measuring, analyzing and predicting the excitation by the dynamic torque of the electric drive are presented. The dynamic torque of the electric drive up to 3.5 kHz is measured on a component test bench with the help of high frequency, high precision torque transducer. The analysis of the results for the order of interest shows a good correlation with the acoustic measurements inside the corresponding vehicle. In addition an experimental and numerical modal analysis of the rotor of the electric drive are performed.

Thermally sprayed engine bores require surface preparation prior to coating to ensure adequate adhesion. Mechanical roughening methods produce repeatable surfaces with high adhesion strength and are attractive for high volume production. The currently available mechanical roughening methods are finish boring based processes which require diameter-specific tooling and significant clearance at the bottom of the bore for tool overtravel and retraction. This paper describes a new mechanical roughening method based on circular interpolation. This method uses two tools: a peripheral milling tool, which cuts a series of concentric grooves in the bore wall through interpolation, and a second rotary tool which deforms the grooves to produce an undercut. This method produces equivalent or higher bond strength than current surface preparation methods, and does not require diameter-specific tooling or bottom clearance for tool retraction.

Prediction of flow induced noise in the interior of a passenger car requires accurate representations of both fluctuating surface pressures across the exterior of the vehicle and efficient models of the vibro-acoustic transmission of these surface pressures to the driver’s ear. In this paper, aeroacoustic and vibro-acoustic methods are combined in order to perform an aero-vibro-acoustic analysis of a Mercedes-Benz A-class. The exterior aero-acoustic method consists of a time domain incompressible Detached Eddy Simulation (DES) and an acoustic wave equation. The method is extended in this paper to account for convection effects when modelling the exterior sound propagation. The interior vibro-acoustic model consists of a frequency domain Finite Element (FE) model of the side glass combined with a generalized Statistical Energy Analysis (SEA) model of the interior cabin.

This paper makes a contribution toward a more efficient chassis durability process for the development of passenger cars, in which the simulation of relevant load data is a time-consuming part. This is especially due to the full vehicle model complexity which is usually determined by the demands of rough road simulations. However, for the load calculation on a racetrack, time saving model approaches that are more simplified might be sufficient. Our investigation comprises two levels of vehicle model complexity: one with all chassis parts modeled in a multibody system environment and one characteristic curve based model in an internal simulation environment. Both approaches consider an original chassis control system as a Software-in-the-Loop model. By the evaluation of real-world experiments the main influence factors in terms of durability are demonstrated. With the help of those highly sensitive durability criteria the measurement and simulation results are then compared.

In this paper, a systems engineering approach is explored to evaluate the effect of design parameters that contribute to the performance of the embedded Automatic Speech Recognition (ASR) engine in a vehicle. This includes vehicle designs that influence the presence of environmental and HVAC noise, microphone placement strategy, seat position, and cabin material and geometry. Interactions can be analyzed between these factors and dominant influencers identified. Relationships can then be established between ASR engine performance and attribute performance metrics that quantify the link between the two. This helps aid proper target setting and hardware selection to meet the customer satisfaction goals for both teams.

This paper describes two case studies in which multiple microphone processing (beamforming) and microphone location were evaluated to determine their impact on improving embedded automatic speech recognition (ASR) in a vehicle hands-free environment. While each of these case studies was performed using slightly different evaluation set-ups, some specific and general conclusions can be drawn to help guide engineers in selecting the proper microphone location and configuration in a vehicle for the improvement of ASR. There were some outcomes that were common to both dual microphone solutions. When considering both solutions, neither was equally effective across all background noise sources. Both systems appear to be far more effective for noise conditions in which higher frequency energy is present, such as that due to high levels of wind noise and/or HVAC (heating, ventilation and air conditioning) blower noise.

This paper describes a method to validate in-vehicle speech recognition by combining synthetically mixed speech and noise samples with batch speech recognition. Vehicle cabin noises are prerecorded along with the impulse response from the driver's mouth location to the cabin microphone location. These signals are combined with a catalog of speech utterances to generate a noisy speech corpus. Several factors were examined to measure their relative importance on speech recognition robustness. These include road surface and vehicle speed, climate control blower noise, and driver's seat position. A summary of the main effects from these experiments are provided with the most significant factors coming from climate control noise. Additionally, a Signal to Noise Ratio (SNR) experiment was conducted highlighting the inverse relationship with speech recognition performance.

Nowadays, the vehicle design is highly ruled by the increasing customer demands and expectations. In addition to ride comfort and vehicle handling, the Noise, Vibration and Harshness (NVH) behavior of the powertrain is also a critical factor that has a big impact on the customer experience. To evaluate the powertrain NVH characteristics, the NVH error states should be studied. A typical NVH event could be decoupled into 3 parts: source, path, and receiver. Take-off shudder, which evaluates the NVH severity level during vehicle take-off, is one of the most important NVH error states. The main sources of Front Wheel Drive (FWD) take-off shudder are the plunging Constant Velocity Joints (CVJ) on the left and right half shafts. This is because a plunging CVJ generates a third order plunging force with half shaft Revolution Per Minute (RPM), which is along the slip of the plunging CVJ.

At various milestones during a vehicle’s development program, different CAE models are created to assess NVH error states of concern. Moreover, these CAE models may be developed in different commercial CAE software packages, each one with its own unique advantages and strengths. Fortunately, due to the wide spread acceptance that the Functional Mock-up Interface (FMI) standard gained in the CAE community over the past few years, many commercial CAE software now support cosimulation in one form or the other. Cosimulation allows performing multi-domain/multi-resolution simulations of the vehicle, thereby combining the advantages of various modeling techniques and software. In this paper, we explore cosimulation of full 3D vehicle model developed in MSC ADAMS with 1D driveline model developed in LMS AMESim. The target application of this work is investigation of vehicle NVH error states associated with both hybridized and non-hybridized powertrains.

This paper investigates an optimal design of a diesel engine and after-treatment systems for a series hybrid electric forklift application. A holistic modeling approach is developed in GT-Suite® to establish a model-based hardware definition for a diesel engine and an after-treatment system to accurately predict engine performance and emissions. The used engine model is validated with the experimental data. The engine design parameters including compression ratio, boost level, air-fuel ratio (AFR), injection timing, and injection pressure are optimized at a single operating point for the series hybrid electric vehicle, together with the performance of the after-treatment components. The engine and after-treatment models are then coupled with a series hybrid electric powertrain to evaluate the performance of the forklift in the standard VDI 2198 drive cycle.

The Composite Hybrid Automotive Suspension System Innovative Structures (CHASSIS) is a project to develop structural commercial vehicle suspension components in high volume utilising hybrid materials and joining techniques to offer a viable lightweight production alternative to steel. Three components are in scope for the project:- Front Subframe Front Lower Control Arm (FLCA) Rear Deadbeam Axle

Fatigue analysis incorporating explicit finite element simulation was conducted on a forged magnesium wheel model where a rotating bend moment was applied to the hub to simulate rotary fatigue testing. Based on wheel fatigue design criteria and a developed fatigue post-processor, the safety factor of fatigue failure was calculated for each finite element. Fatigue failure was verified through experimental testing. Design modifications were proposed by increasing the spoke thickness. Further numerical and experimental testing indicated that the modified design passed the rotary fatigue test.

Fuel cells convert a fuel together with oxygen in a highly efficient electrochemical reaction to electricity and water. Automotive fuel cell systems mainly use compressed onboard stored hydrogen as fuel. Oxygen from ambient air is fed to the cathode of the fuel cell stack by an air supply subsystem. For its current and next generation air supply subsystem NuCellSys has employed screw type compressor technology, which in the automotive area initially was developed for supercharged internal combustion (IC) engines. As NVH expectations to fuel cell vehicles differ very much from IC-engine driven vehicles, specific efforts have to be taken to address the intense noise and vibration profile of the screw compressor. This paper describes different counter measures which have been implemented into the NuCellSys next generation air supply subsystem.