Sound quality driven active control of periodic disturbance for hybrid vehicles

• Autor(a) principal: Sanchez, Jaime Alberto Mosquera
• Data de Publicação: 2017
• Tipo de documento: Tese
• Idioma: eng
• Título da fonte: Biblioteca Digital de Teses e Dissertações da USP
• Texto Completo: https://www.teses.usp.br/teses/disponiveis/18/18149/tde-10062020-170830/
• topic: controle ativo multicanal de qualidade sonora; distúrbio periódico; hybrid electric vehicle; multi-objective sound quality optimization; multichannel active sound quality control; otimização multi-objetivo de qualidade sonora; periodic disturbance; qualidade sonora; sound quality; veículo elétrico híbrido

Hybrid and electric vehicles (HEVs) arise as a response of the automotive industry to the quest of implementing clean and sustainable propulsion, face to the potential scarcity of fossil fuels. The integration of the electric motor to the powertrain in this sort of vehicles presents acoustic stimuli that elicit new perceptions. The large number of spectral components, as well as the bandwidth of the hybrid electric powertrain noise, pose new challenges to current noise, vibration and harshness approaches. None of the state-of-the-art techniques is able to simultaneously tackle low-, mid- and high-frequency issues, and probably just a handful of them take the auditory perception as a fundamental design criteria. This research proposes a framework for enhancing the sound quality (SQ) of the hybrid electric powertrain noise that is perceived inside the passenger compartment. The proposed method relies on the extensive use of active noise equalizer systems, which are capable of modifying the SQ of harmonic disturbances by means of profiling their magnitude and relative-phase functions. An extension of single-channel active noise equalizers to multichannel environments has been developed and the challenges related to cross-channel interferences tackled, which allows simultaneous active sound profiling for a number of listeners. In addition, as Loudness, Roughness, Sharpness and Tonality are the most relevant SQ metrics for HEVs noise, they have been used as performance metrics in the concurrent optimization analysis that drives the control design method. The proposed method is verified experimentally with realistic hybrid electric powertrain noise, by attaining SQ improvement for either single or multiple locations within a scaled vehicle mock-up. The results show success rates in excess of 90%, which indicate the proposed method is promising, not only for HEVs noise, but also for a variety of periodic disturbances with similar features.