Odor Assessment of Automobile Cabin Air With Field Asymmetric Ion Mobility Spectrometry and Photoionization Detection

Abstract

Odor quality in the cabin air of automobiles can be a significant factor in the decision to purchase a vehicle and the overall customer satisfaction with the vehicle over time. A current standard practice uses a human panel to rate the vehicle cabin odors on intensity, irritation, and pleasantness. However, human panels are expensive, time-consuming, and complicated to administer. To address this issue, we present a machine olfaction approach to assess odors inside automobiles. The approach uses a field asymmetric ion mobility spectrometer and a photoionization detector to measure volatile organic compounds, and a multivariate technique to map sensor data into human ratings. Validation on an experimental dataset of odors from ten different vehicles shows a correlation (0.67–0.84) between model predictions and ground truth from a trained human panel. These results support the feasibility of replacing human panel assessments by objective instrumental means for quality control tasks in the production process.