Project outline
Modern vacuum cleaners face increasing consumer demands for quieter operation while maintaining superior cleaning performance and energy efficiency. The suction motor (electric) is the dominant contributor to overall system noise, vibration and harshness (NVH), with current designs prioritizing performance and cost over acoustic comfort, resulting in noise levels exceeding 80 dB(A) during operation.
Electric motors present particularly challenging NVH issues including tonal components from rotor unbalance, electromagnetic excitation harmonics, slotting effect tones, and blade pass frequency noise from aerodynamic interactions. Despite significant advances in motor technology, existing approaches fail to capture the complex multi-physics interactions governing suction motor NVH behaviour across diverse operating conditions.
This PhD project directly addresses the critical need to place human sound perception at the heart of vacuum cleaner engineering by investigating the interdependencies between motor physics and perception. As well as understanding the sources of noise & quietening, this research systematically correlate objective acoustic measurements with human psychological responses through controlled psychoacoustic studies. By integrating advanced experimental methodologies with computational modeling, the project will establish perception-driven design criteria that optimize for human comfort rather than just sound power reduction, fundamentally shifting from physics-driven to human-centered acoustic engineering.
Project Partners
This project is hosted at the University of Southampton and supported by Vax Limited UK.
Further project information
This PhD project has two primary research objectives that together address both the technical and perceptual aspects of vacuum cleaner motor NVH optimization.
First, the project aims to experimentally isolate and quantify individual NVH contributors – electromagnetic forces, mechanical resonances, aerodynamic noise, and structural coupling effects – through advanced testing methodologies that establish protocols for accurately predicting real-world performance via correlation studies between laboratory measurements and in-situ product operation. This experimental work will be supported by numerical modelling approaches to correlate and validate experimental findings. The numerical models will serve as complementary tools to interpret experimental data, optimize test configurations, and extend findings across broader parameter ranges.
Second, the project aims to conduct psychoacoustic research to identify opportunities for improving perceived quietness through harmonic content optimization. This involves developing subjective evaluation protocols to correlate measured acoustic parameters with user comfort perception and establishing weighted sound quality metrics. The psychoacoustic research targets achieving superior user satisfaction even at comparable overall sound pressure levels by understanding how humans perceive and respond to different motor sound characteristics rather than simply focusing on traditional noise reduction metrics.
Along with being relevant to the industry partner the test methodologies & tools of this research have wider applications to other sectors such as automotive (electric vehicles), aviation etc.
This PhD project directly addresses the critical need to place human sound perception at the heart of vacuum cleaner engineering by investigating the interdependencies between motor physics and perception. As well as understanding the sources of noise & quietening, this research systematically correlate objective acoustic measurements with human psychological responses through controlled psychoacoustic studies. By integrating advanced experimental methodologies with computational modelling, the project will establish perception-driven design criteria that optimize for human comfort rather than just sound power reduction, fundamentally shifting from physics-driven to human-centred acoustic engineering.
Subject Areas
- Acoustics
- Tonal noise
- Noise control methods
- Psychoacoustics
- Electromagnetic force
- Fluid dynamics
Required qualifications/skills
Essential
- A first-class or upper second-class degree (or equivalent) in Acoustics, biology, ecology, bioacoustics, environmental science, or a related discipline.
- Skills in data analysis (e.g. R, Python, or MATLAB) and/or signal processing would be advantageous.
Student
Commencing in October 2026