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The development of an effective Acoustic Vehicle Alert System (AVAS) is not solely about adhering to safety regulations; it also involves crafting an auditory experience that aligns with the expectations of vulnerable road users. To achieve this, a deep understanding of the acoustic transfer function is essential, as it defines the relationship between the sound emitter (the speaker inside the vehicle) and the receiver (the vulnerable road user). Maintaining the constancy of this acoustic transfer function is paramount, as it ensures that the sound emitted by the vehicle aligns with the intended safety cues and brand identity that is defined by the car manufacturer. In this research paper, three distinct methodologies for calculating the acoustic transfer function are presented: the classical Boundary Element method, the H-Matrix BEM accelerated method, and the Ray tracing method.

Noise reduction is generally accomplished by applying appropriate noise control treatments at strategic locations. Noise control treatments consisting of poroelastic materials in layers are extensively used in noise control products. Sound propagation through poroelastic materials is governed by macroscopic material and geometric properties. Thus, a knowledge of material properties is important to improve the acoustical performance of the resulting noise control products. Since the direct measurement of these properties is cumbersome, these have been usually estimated indirectly from easily measurable acoustic performance metrics such as normal incidence sound transmission and/or absorption coefficient, measured using readily available impedance tube. The existing inverse characterization approaches fulfilled the estimation by curve fitting measured and predicted acoustic models.

Designing an effective AVAS system, not only to meet safety regulations, but also to create the expected perception for the vulnerable road user, relies on knowledge of the acoustic transfer function between the sound actuator and the receiver. It is preferable that the acoustic transfer function be as constant as possible to allow transferring the sound designed by the car OEM to ensure the safety of vulnerable road users while conveying the proper brand image. In this paper three different methodologies for the acoustic transfer function calculations are presented and compared in terms of accuracy and calculation time: classic Boundary Element method, H-Matrix BEM accelerated method and Ray tracing method. An example of binaural listening experience at different certification positions in the modeled simulated space is also presented.

Electric and Hybrid vehicles have standards for emitting enough noise to reduce danger and risk to pedestrians when operating at low speeds. Simulation can help to support development and deployment of these systems while avoiding a time-consuming, test-based approach to design these AVAS (Acoustic Vehicle Alerting System) warning systems. Traditionally, deterministic simulation methods such as Finite Element Method (FEM) and Boundary Element Method (BEM) are used at low frequencies and statistical, energy-based methods such as Statistical Energy Analysis (SEA) are used at high frequencies. The deterministic methods are accurate, but computationally inefficient, particularly when the frequency increases. SEA is computationally efficient but does not capture well the physics of exterior acoustic propagation. An alternative method commonly used in room acoustics, based on geometrical or ray acoustics, is “Ray Tracing” and can be used for sound field prediction.

With stricter pass-by norms, reducing engine noise radiation is becoming more important. Adding ribs to improve stiffness is one efficient approach to achieve this goal. This paper performs the optimization of ribs which are added on the surface of an inline six-cylinder engine block. The ribs are placed orthogonally. For the optimization, optimization variables are set up to update the dimensions of the ribs in each iteration. The limits of the size changes are defined by the optimization constraints. The overall sound power radiated from the engine block surface between 500Hz and 1450Hz is chosen as the optimization objective. In each iteration, the radiated sound power is obtained by numerical analysis of a fully coupled structural-acoustic model, while the FEM (finite element method) is adopted for calculating the structural response and BEM (boundary element method) is used to compute the noise radiation from the engine block surface.

Welding processes are complex in nature. They affect the mechanical properties of a weldment in and around the welding joint (in the heat affected zone: HAZ), causing deformation and inducing high level of residual stress and plastic strain which are detrimental to the weldment performance. After welding some materials soften while others harden in the heat affected zone, depending on the process heat input, the thickness of the material and its chemical composition. Traditionally, finite element (FE) performance analyses (crash, rupture, fatigue, static and dynamic tests) of weldments are performed without accounting for the effects of welding processes and as such the real performance of a weldment is not accurately predicted. On one hand, if base material properties are used to represent a weldment which hardens in the heat affected zone, the performance analysis results would be too conservative which would hinder/limit potential weight reduction strategies.

The truck cab is made of many structural members like hinge, A/B/C - pillar, rocker, roof rails, headliner, quarter panels, cross-members at the floor and other body panels. For an acoustic example, the source energy travels easily from one end to another end through pillars. To reduce these acoustic effects, the filler foams were added inside the pillars. The proper usage of filler design and filler material type produces the optimal sound response at the driver head space location. In this paper, an analytical method is used to evaluate the acoustic performance of the fillers as described above and the method also avoids the expensive full vehicle tests. The statistical energy analysis (SEA) model simulations and post-processing techniques were used to evaluate the results quickly with an acceptable level of accuracy.

Sound propagation through noise control treatment is governed by fluid, mechanical and geometric properties of the materials. The knowledge of material properties is important to improve the acoustical performance of the resulting noise control products. A method based on optimization together with genetic algorithm is used to estimate material properties of multi-layered treatments. Unlike previous inverse characterization approaches based on normal incidence performance metrics measured using standing wave impedance tubes, the current approach is based on random incidence performance metrics. Specially, the insertion loss ‘measured’ from two room transmission loss suite is utilized. To validate the applicability of the proposed method, numerically synthesized insertion loss computed from known material properties are used. In order to properly represent the ‘measured’ values, noise is added to the numerically synthesized insertion loss values.

Optimizing noise control treatments in the early design phase is crucial to meet new strict regulations for exterior vehicle noise. Contribution analysis of the different sources to the exterior acoustic performance plays an important role in prioritizing design changes. A method to predict Pass-by noise performance of a car, based on source-path-receiver approach, combining data coming from simulation and experimental campaigns, is presented along with its validation. With this method the effect of trim and sound package on exterior noise can be predicted and optimized.

A model of a tractor cab was built using Statistical Energy Analysis (SEA) best practices. In this paper, it is shown how this model was correlated using p/Q transfer functions measured in the lab with a volume velocity source. After correlation, the model was excited using acoustic loads measured during tractor operation. It was found that the data predicted by the model is in good agreement with the data measured inside the cabin during this test. It was concluded that SEA can be used as an engineering tool to predict the behavior under many different conditions and can be used to guide the development process.

Porous materials have been applied increasingly for absorbing noise energy and improving the acoustic performance. Different models have been proposed to predict the performance of these materials, and much progress has been achieved. However, most of the foregoing researches have been conducted on a single layer of porous material. In real application, porous materials are usually combined with other kinds of materials to compose a multilayered noise control treatment. This paper investigates the acoustic performance of such treatments with a combination of porous and non-porous media. Results from numerical simulation are compared to experimental measurements. Transfer matrix method is adopted to simulate the insertion loss and absorption associated with three samples of a noise control treatment product, which has two porous layers bonded by an impervious screen.

The demand for seating comfort is growing - in cars as well as trucks and other commercial vehicles. This is expected as the seat is the largest surface area of the vehicle that is in contact with the occupant. While it is predominantly luxury cars that have been equipped with climate controlled seats, there is now a clear trend toward this feature becoming available in mid-range and compact cars. The main purpose of climate controlled seats is to create an agreeable microclimate that keeps the driver comfortable. It also reduces the “stickiness” feeling which is reported by perspiring occupants on leather-covered seats. As part of the seat design process, a physical test is performed to record and evaluate the life cycle and the performance at ambient and extreme temperatures for the climate controlled seats as well as their components. The test calls for occupied and unoccupied seats at several ambient temperatures.

Finite element analysis (FEA) is commonly used in the automotive industry to predict low frequency NVH behavior (<150 Hz) of structures. Also, statistical energy analysis (SEA) framework is used to predict high frequency (>400 Hz) noise transmission from the source space to the receiver space. A comprehensive approach addressing the entire spectrum (>20 Hz) by taking into account structure-borne and air-borne paths is not commonplace. In the works leading up to this paper a hybrid methodology was employed to predict structure-borne and air-borne transfer functions up to 1000 Hz by combining FEA and SEA. The dash panel was represented by FE structural subsystems and the noise control treatments (NCTs) and the pass-throughs were characterized via testing to limit uncertainty in modeling. The rest of the structure and the fluid spaces were characterized as SEA subsystems.

In this paper a design methodology for automotive heat exchangers has been applied which brings robustness into the design process and helps to optimize the design goals: as to maintain an optimal coolant temperature and to limit the vehicle underhood air temperature within a tolerable limit. The most influential design factors for the heat exchangers which affect the goals have been identified with that process. The paper summarizes the optimization steps necessary to meet the optimal functional goals for the vehicle as mentioned above. Taguchi's [1] Design for Six Sigma (DFSS) methods have been employed to conduct this analysis in a robust way.

In this paper, thermal models are developed based on experimental test data, and the physics of thermal systems. If experimental data is available, the data can be fitted to mathematical models that represent the system response to changes in its input parameters. Therefore, empirical models which are based on test data are developed. The concept of time constant is presented and applied to development of transient models. Mathematical models for component temperature changes during transient vehicle driving conditions are also presented. Mathematical models for climate control system warm up and cool-down are also discussed. The results show the significance of adopting this concept in analysis of vehicle test data, and in development of analytical models. The developed models can be applied to simulate the system or component response to variety of changes in input parameters. As a result, significant testing and simulation time can be saved during the vehicle development process.

Taguchi method is a technology to prevent quality problems at early stages of product development and product design. Parameter design method is an important part in Taguchi method which selects the best control factor level combination for the optimization of the robustness of product function against noise factors. The air induction system (AIS) provides clean air to the engine for combustion. The noise radiated from the inlet of the AIS can be of significant importance in reducing vehicle interior noise and tuning the interior sound quality. The porous duct has been introduced into the AIS to reduce the snorkel noise. It helps with both the system layout and isolation by reducing transmitted vibration. A CAE simulation procedure has been developed and validated to predict the snorkel noise of the porous ducted AIS. In this paper, Taguchi's parameter design method was utilized to optimize a porous duct design in an AIS to achieve the best snorkel noise performance.

Accurate numerical prediction of an engine thermal map at a wide range of engine operating conditions can help tune engine performance parameters at an early development stage. This study documents the correlation of an engine thermal simulation using the conjugate heat transfer (CHT) methodology with thermocouple data from an engine operating in a dynamometer and a vehicle drive cell. Three different operating conditions are matched with the simulation data. Temperatures predicted by simulation at specific sections, both at the intake and the exhaust sides of the engine are compared with the measured temperatures in the same location on the operating engine.

Advanced high strength steels (AHSS) offer a good balance of strength, durability, crash energy absorption and formability. Applications of AHSS for lightweight designs of automotive structures are accelerating in recent years to meet the tough new CAFE standard for vehicle fuel economy by 2025. At the same time, the new generation pickup cargo box is to be designed for a dramatic increase in payload. Upgrading the box material from conventional mild steels to AHSS is necessary to meet the conflicting requirements of vehicle light weighting and higher payload. In this paper, typical AHSS grades such as DP590 and DP780 were applied to selected components of the pickup cargo box for weight reduction while meeting the design targets for fatigue, strength and local stiffness.

In recent trend, there is a huge demand for lightweight chassis frame, which improves fuel efficiency and reduces cost of the vehicle. Stiffness based optimization process is simple and straightforward while durability (life) based optimizations are relatively complex, time consuming due to a two-step (Stress then life) virtual engineering process and complicated loading history. However, durability performances are critical in chassis design, so a process of optimization with simplified approach has been developed. This study talks about the process of chassis frame weight optimization without affecting current durability performance where complex durability load cases are converted to equivalent static loadcases and life targets are cascaded down to simple stress target. Sheet metal gauges and lightening holes are the parameters for optimization studies. The optimization design space is constrained to chassis unique parts.

Interference assessments of a stepped-radius power-train component moving within a deformed stepped bore often arise during engine and transmission development activities. For example, when loads are applied to an engine block, the block distorts. This distortion may cause a cam or crankshaft to bind or wear prematurely in its journals as the part rotates within them. Within an automatic transmission valve body, care must be taken to ensure valve body distortion under oil pressure, assembly, and thermal load does not cause spool valves to stick as they translate within the valve body. In both examples, the mechanical scenario to be assessed involves a uniform or stepped radius cylindrical part maintaining a designated clearance through a correspondingly shaped but distorted bore. These distortions can occur in cross-sections (“out-of-round”) or along the bore (in an “s” or “banana” shaped distortions).