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Brake squeal has been a persistent quality issue for automobile OEMs and brake system suppliers. The ability to model and measure brake squeal dynamics is of utmost importance in brake squeal reduction efforts. However, due to the complex nature of brake squeal and the wide frequency range in which it occurs, it is difficult to accurately correlate and update analytical models to experimental results. This paper introduces a systematic and rigorous correlation and updating process that yields FE models, which can accurately reproduce high-frequency brake squeal dynamics.

Without the masking effect of a combustion engine, noise from the road is much more prominent in electric vehicles (EV) and has become the dominant source of noise for drivers and passengers. Road noise however is a complex problem. Unlike engine noise, which comes from a single, well-defined source, road noise finds its origins in the road-to-tire contact. This means that there are typically 4 sources (assuming a 4-wheel vehicle) which are influenced by the roughness and profile of the road as well as the compliance of the tires. From an engineering point of view it’s easy to appreciate the added complexity compared to engine noise. In addition to the engineering complexity, there is also a supplier-OEM relationship that comes into play. Most OEMs do not manufacture their own tires and may even have multiple tire suppliers for the same vehicle. This brings on another set of complications.

Improving fuel efficiency often affects NVH performance. Modifying a vehicle’s design in the latter stages of development to improve NVH performance is often costly. Therefore, to optimize the cost performance, a Multi-Attribute Balancing (MAB) approach should be employed in the early design phases. This paper proposes a solution based on a unified 1D system simulation model across different vehicle performance areas. In the scope of this paper the following attributes are studied: Fuel economy, Booming, Idle, Engine start and Drivability. The challenges to be solved by 1D simulation are the vehicle performance predictions, taking into account the computation time and accuracy. Early phase studies require a large number of scenarios to evaluate multiple possible parameter combinations employing a multi-attribute approach with a systematic tool to ease setup and evaluation according to the determined performance metrics.