Multiple target sound quality balance for hybrid electric powertrain noise. (15th January 2018)

• Record Type: Journal Article
• Authors: Mosquera-Sánchez, J.A.; Sarrazin, M.; Janssens, K.; de Oliveira, L.P.R.; Desmet, W.
• Is Part Of: Mechanical systems and signal processing. Volume 99(2017)
• Page Start: 478
• Page End: 503
• Publication Date: 2018-01-15
• Subjects: Hybrid electric vehicle -- Multichannel active sound quality control -- Multi-objective sound quality optimization -- Periodic disturbance -- Sound quality; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2017.06.034
• Languages: English
• ISSNs: 0888-3270

Abstract

Graphical abstract: Highlights: A method to design and implement sound quality targets is proposed. Optimization of sound quality is carried out in a multi-objective fashion. Sensitivity analyses identify relevant tones in periodic disturbances. Optimal sound quality targets for each listener in a cavity have been implemented. Success percentages above 90% verify the effectiveness of the proposed framework. Abstract: The integration of the electric motor to the powertrain in hybrid electric vehicles (HEVs) presents acoustic stimuli that elicit new perceptions. The large number of spectral components, as well as the wider bandwidth of this sort of noises, pose new challenges to current noise, vibration and harshness (NVH) approaches. This paper presents a framework for enhancing the sound quality (SQ) of the hybrid electric powertrain noise perceived inside the passenger compartment. Compared with current active sound quality control (ASQC) schemes, where the SQ improvement is just an effect of the control actions, the proposed technique features an optimization stage, which enables the NVH specialist to actively implement the amplitude balance of the tones that better fits into the auditory expectations. Since Loudness, Roughness, Sharpness and Tonality are the most relevant SQ metrics for interior HEV noise, they are used as performance metrics in the concurrent optimization analysis, which, eventually, drives the control design method. Thus, multichannel active sound profiling systems that feature cross-channel compensation schemes are guided by the multi-objective optimization stage, by means of optimal sets of amplitude gain factors that can be implemented at each single sensor location, while minimizing cross-channel effects that can either degrade the original SQ condition, or even hinder the implementation of independent SQ targets. The proposed framework is verified experimentally, with realistic stationary hybrid electric powertrain noise, showing SQ enhancement for multiple locations within a scaled vehicle mock-up. The results show total success rates in excess of 90%, which indicate that the proposed method is promising, not only for the improvement of the SQ of HEV noise, but also for a variety of periodic disturbances with similar features.