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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.

Wind noise is a major contributor to vehicle noise and a very common consumer complaint for overall vehicle quality [1]. The reduction of wind noise is becoming even more important as powertrain noise is reduced or eliminated (by conversion to hybrid and electric vehicles) and as the importance of quiet interior environment for hands-free device use and voice activation systems becomes more pronounced. In contrast to other noise sources such as tires, engine, intake, exhaust or other component noise whose acoustic loads may be measured in a direct and standardized way with the proper equipment, wind noise is very difficult to predict because the acoustic part of wind noise is a small component of overall fluctuating pressures. It is very challenging to either directly measure or to simulate the acoustic component of fluctuating exterior pressures using CFD (Computational Fluid Dynamics) without a great deal of specialized experience in this area.

Predicting Vehicle Pass-by noise using simulation enables efficient development of adequate countermeasures to meet legislative targets while reducing development time and the number of physical trial-and-error prototypes and tests. It has already been shown that deterministic simulation methods such as the Boundary Element Method (BEM), which may also include directivity of sources, can support the trim package optimization process for Pass-by noise, especially for low to mid frequencies. At higher frequencies, the Ray Tracing technique, can represent an efficient alternate providing options to trade off speed versus accuracy compared to wave-based technique such as FE/BEM. This paper presents a Ray Tracing approach with high order diffraction effect. Moreover, source directivity and sound package effect are accounted for.

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.

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.

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.

Tire/Road noise is a dominant contribution to a vehicle interior noise and requires significant engineering resources during vehicle development. A process has been developed to support automotive OEMs with road noise engineering during vehicle design and development which has test as its basis but takes advantage of simulation to virtually accelerate road noise improvement. The process uses airborne noise sources measured on a single tire installed on a test stand. The measured sources are then combined with vehicle level transfer functions calculated using a Statistical Energy Analysis (SEA) model to predict the sound at the driver ears. The process can be applied from the early stages of a vehicle development program and allows the evaluation of vehicle road noise performance as perceived by the driver long before the first prototype is available. This process is also extensible to other types of sources and loads impacting vehicle interior acoustics.

To meet vehicle interior noise targets and expectations, components including those related to electric vehicles (EVs) can effectively be treated at the source with an encapsulation approach, preventing acoustic and vibration sources from propagating through multiple paths into the vehicle interior. Encapsulation can be especially useful when dealing with tonal noise sources in EVs which are common for electrical components. These treatments involve materials that block noise and vibration at its source but add weight and cost to vehicles – optimization and ensuring the material used is minimized but efficient in reducing noise everywhere where it is applied is critically important. Testing is important to confirm source levels and verify performance of some proposed configurations, but ideal encapsulation treatments are complex and cannot be efficiently achieved by trial-and-error testing.