Thesis Work - Structure-borne noise assessment of automotive component

MSc Thesis proposal at Volvo Group

(60 ECTS credits, 40 weeks, One student) / (30 ECTS credits, 20 weeks, Two students)

Structure-borne noise assessment of automotive components using the blocked force approach

The commercial vehicle industry is shifting from ICE (Internal Combustion Engine) to EDU (Electric Driving Units) as a propulsion mean, resulting in lower noise emission in society and a quieter environment for the driver. However, without the noise masking effect from the ICE, requirements on using silent components like pumps, compressors and fans is getting tougher especially when it comes to structure-borne noise. Therefore, an appropriate structure-borne noise characterization method is required both for target settings towards suppliers and as input data for simulations.

The blocked force approach aims at describing the structure-borne characteristics of components without any influence of the measurement boundary conditions. In other words, a component tested on different test benches should give the same blocked force. Another advantage of the blocked force approach is that is has recently been formalized as an ISO standard, SS ISO 20270.

In this master’s thesis, we aim at reviewing some fundamental concepts of the blocked force approach. In a first part, after some literature study, FEM (Finite Element Modelling) will be used to verify the various blocked force determination methods. From this study, guidelines should be drawn for the matrix inversion problem, the effect of noise in the measurements, the measurement point location strategy and structure properties. In a second part, measurements will be performed on a truck component to validate the findings from part one.

Your profile:

• One or two Master’s student in mechanical, applied physics or electrical engineering, or from the “sound and vibration” program. For better synergy, students from different educational programs are very welcome
• Knowledge in Finite Element Methods and MATLAB or Python
• Good knowledge in linear algebra, signal processing
• Good hands-on capability and knowledge in measurement technique

The Master of Science Thesis work will be performed at Volvo Group Trucks Technology, (Gothenburg, Sweden)

Industry supervisors: Frédéric Wullens, Theresia Manns at Volvo GTT

University supervisors: TBD