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This paper deals with the characterization of the vibration frequency spectrum of the electric motor in the power train of a hybrid vehicle. This analysis is carried out using a vibration analyzer as a measurement instrument and Minitab software for processing the numerical data obtained. The numerical data collected in each experiment allow an accurate evaluation of the significant differences in power consumption, both in the charging and discharging phases. In order to meet the proposed objectives, we proceed with the characterization of the vibration spectrum of the electric motor of the hybrid vehicle powertrain under controlled conditions, which include both the charging and discharging phases, as well as the operation of the air conditioning system at its maximum capacity. The acquisition of this data is carried out using Dewesoft software. Subsequently, analysis of variance is used to process and filter the collected data. The null hypothesis was accepted, since the results exceeded the significance level set at 0.005, with a confidence interval of 99.5% for normal distribution and 99% for ANOVA analysis.

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Spectral Analysis of Powertrain Vibration in a Hybrid Vehicle Under Controlled Operating Conditions

  • 会议论文

  • 发表日期：

    2025年

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  • Raquel de los A. Salas Ibarra,
  • Alexander E. Torres Romero,
  • David H. Cárdenas Villacrés

摘要

This paper deals with the characterization of the vibration frequency spectrum of the electric motor in the power train of a hybrid vehicle. This analysis is carried out using a vibration analyzer as a measurement instrument and Minitab software for processing the numerical data obtained. The numerical data collected in each experiment allow an accurate evaluation of the significant differences in power consumption, both in the charging and discharging phases. In order to meet the proposed objectives, we proceed with the characterization of the vibration spectrum of the electric motor of the hybrid vehicle powertrain under controlled conditions, which include both the charging and discharging phases, as well as the operation of the air conditioning system at its maximum capacity. The acquisition of this data is carried out using Dewesoft software. Subsequently, analysis of variance is used to process and filter the collected data. The null hypothesis was accepted, since the results exceeded the significance level set at 0.005, with a confidence interval of 99.5% for normal distribution and 99% for ANOVA analysis.