DMP-SMP Parallel Computation Strategies for FE-BEM-PEM Transmission Loss Simulation in Automotive Dash Panels

Kamel Amichi･Massimiliano Calloni (Keysight Technologies)

Transmission Loss is a key metric for automotive components such as dash panels. While curved panel acoustics are well studied, panels with acoustic treatments receive less attention. Classical FEM and SEA methods are limited by cost and assumptions, and TMM applies mainly to homogenized geometries. Deterministic simulations combining FEM for structure, poroelastic modeling for treatments, and BEM for sound propagation offer greater accuracy. To extend frequency range and enable SEA integration, computation time must be reduced. This paper introduces a DMP-SMP parallel approach for FE-BEM-PEM workflows on trimmed dash panels and compares bare structures using an accelerated H-Matrix BEM solver.

Influence of Electric Compressor Operating Parameters on NVH Performance

Itsukyo Yamayoshi (Valeo Japan)･Saad Bennouna (Valeo)

Driven by worldwide environmental regulations, the automotive industry is accelerating Electric Vehicle (EV) development. This shift has elevated the importance of the thermal management system, at the core of which lies the Electric Drive Compressor (EDC). As the EDC is a dominant noise source, NVH targets are typically evaluated and validated during vehicle development, but typically for a set of specific test conditions. This study investigates the influence of the operating parameters on the NVH characteristics across a selection of commercially available units to explore a possibility in the system side NVH control measures.

The study for improvement of NV performance by contribution analysis of interior noise and optimization of acoustic package for next-generation BEV

Atsuki Saito･Naotsugu Tajima･Kosuke Ueda･Shoma Taniguchi (HOWA)･Makoto Kon･Kenji Yasuda･Keita Suzuki･Yutaka Yamaguchi (Suzuki Motor)

For next-generation BEV development, a Hybrid Statistical Energy Analysis (HSEA) model was built to conduct contribution analysis of interior noise sources. Based on the result, an optimized vehicle package was designed to enhance NV performance without increasing mass. The validity of this optimization was verified by testing actual vehicle.

Comparison of Conventional Prediction Methods and Sound Ray Tracing in Automobile Interior Acoustic Space

Shogo Takeuchi･Kastuhiko Kuroda (Nagasaki Institute of Applied Science)

With the spread of electric vehicles, it has become necessary to address high-frequency noise generated by inverters. Since FEM is generally impractical for acoustic analysis in higher frequency ranges, analytical SEA has traditionally been employed as an alternative approach. However, SEA is not suitable for upstream design due to the time-consuming of its model construction. Therefore, sound ray tracing which has been developed primarily in the architectural acoustics field was applied, and aims to propose a guideline for efficiently balancing the trade-off between computational cost and analysis accuracy in upstream design.

Development of a Method for Predicting Door Closing Sound Sensory Scores in the Design Phase Using CAE and AI

Tomohiro Hori･Koji Morimoto･Kai Fujii･Kana Sugimoto (Daihatsu Motor)･Dirk von Werne (Siemens Digital Industries Software)･Kohta Sugiura (Siemens)･Yasushi Kido･Genki Matsuno (Skydisc)

Doors are among the most frequently operated components by users, and the closing sound, in particular, is a critical factor influencing the overall impression of a vehicle. However, evaluation of this sound has traditionally relied on physical testing, making it difficult to consider and optimize during the design phase. To address this issue, we have developed a method to estimate sensory scores by inputting spectrograms of door closing sounds obtained through CAE analysis into AI. This approach enables evaluation and optimization of door closing sounds during the design phase, contributing to improved design efficiency and product quality.