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논문 기본 정보

자료유형
학술대회자료
저자정보
Yeppeun Lee (Korea Automotive Technology Institute) Seyoung Jang (Korea Automotive Technology Institute) Youngseok Lee (Korea Automotive Technology Institute)
저널정보
대한인간공학회 대한인간공학회 학술대회논문집 2022 대한인간공학회 추계학술대회 및 국제심포지엄
발행연도
2022.10
수록면
177 - 180 (4page)

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초록· 키워드

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Objective: The aim of this study is to present an index that can quantify thermal comfort for the development of various heating systems that help the efficient energy management of electric vehicles. Background: To quantify thermal comfort, thermophysiological models and thermopsychological models have been proposed, and data-based PMV(Predicted mean vote) and PPD(Predicted percent dissatisfied) have also been used. However, this is not enough to meet the growing demand for personalization. Method: Based on the BMI, height, and weight of men and women in their 20s and 30s who are healthy physically and mentally, 30 people who belong to 25%~75% as of 2015 Size Korea were selected. The heating system was evaluated in an electric vehicle soaking at minus 7 degrees Celsius.; (1) Thermal sensation (9 scale) and thermal comfort (9 scale) were collected 12 times every 5 minutes by Berkley scale. (2) After the survey, subjects were asked to close their eyes and remain in a stable state for 30 seconds so that the background EEG could be measured. (3) In order to confirm the stable and relaxed state of the subject, the relative alpha power was selected as a state indicator, and it was extracted with a 50% overlap of 2 seconds segment. The ratio with the relative alpha wave collected in a stable state was used as the final analysis index. Results: As a result of analysis based on the experimental results at minus 7 degrees and 20 degrees Celsius, the relative alpha wave confirmed a significant positive correlation with thermal comfort and r = .385 (p < 0.01). Conclusion: In an environment that rapidly changes from a relatively cold temperature to a comfortable temperature, the relative alpha power can be presented as a quantifying index for thermal comfort. Application: An EEG-based evaluation method is proposed as a thermal comfort quantification index for evaluating various heating systems of electric vehicles.

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ABSTRACT
1. Introduction
2. Method
3. Results
4. Conclusion
References

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