In WP 1 work has been performed in the field of noise sources in the context of vehicle pass-by to develop novel approaches for noise and vibration mitigation, warning sound devices and noise characterisation. Enhanced acoustic trim materials for engine bay abatement have been developed, outperforming standard foams. A method has been developed for minimising the noise generated by warning-sound sources, required to improve the safety for pedestrians. Machine Learning methods and big data approaches which are capable for long and short term prediction representing the dynamics of traffic by using summary statistics have been developed and demonstrated. A novel substructuring technique that allows for the efficient analysis of the contribution of the car floor panel to the overall vehicle's interior and pass-by noise was developed, leading to faster and more efficient vehicle design. Also a novel method for modal parameter estimation to automate this process has been developed and validated. Finally an estimation framework capable of reconstructing contact forces accounting for the complex interaction between tire and road has been developed. This method can be applied for better and quieter tire design.
WP2 has focused on both simulation and test based transfer path studies. Model Order Reduction techniques for the Boundary Element Method have been proposed, implemented and tested. They significantly extend the state of the art towards the direction of fast but sufficiently accurate acoustic analysis. An inverse Patch Transfer Function method has been developed to be used for blind identification of vibratory fields. Furthermore, the usability of indoor pass-by tests have been improved, by accounting for room effects. Subsequently, a new technique has been developed that allows the tire’s contribution to the total pass-by noise to be estimated from indoor measurements. Component-based transfer path analysis has been progressed substantially, enabling virtual engineering prediction capabilities.
In WP3 technologies related to pass-by noise receiver evaluation and perception have been investigated and developed. The use of low-quality models for jury testing has been investigated and applied. The indoor pass-by noise testing procedure has been extended involving a semi-circular microphone array, together with novel signal processing algorithms. An innovative and simplified tyre model has been developed allowing for tyre noise modelling and optimization. It has also been investigated whether objective evaluation of sound via brainwaves can contribute to the development of exterior warning sounds. promising results. Finally, a methodology to virtually simulate realistic pass-by noise tests has been explored for prediction of pass-by noise levels and sound quality evaluation.
WP 4 focused on the communication, dissemination and exploitation of the PBNv2 results. 2 technical and 2 industrial public workshops have been organized. 4 sessions at conferences have been organised, 38 conference papers have been presented and 9 journal papers were published, while others are still under review. All partners were highly involved in public engagement activities.
WP5 on management ran smoothly. Via GA meetings and SB meetings, organized twice a year, the project was followed-up closely.
WP6 on training also went well. Individual training programs were adjusted to the needs of the ESRs, while all foreseen network wide training courses took place. Specific attention was given to applied training.
