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Toward better drivability: Investigating user preferences for tip-in acceleration profiles in electric vehicles

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  • Seonghyeon Kim
  • Jaesik Yang

Abstract

Vehicle drivability, defined as the smooth operation and stability of a vehicle in response to driver inputs, significantly influences the performance of passenger cars. Among various driving conditions, tip-in acceleration is one of the most frequently encountered and crucial factors affecting drivability. This study investigates preferred longitudinal acceleration profiles for electric vehicles through subjective evaluations obtained from on-road tests. Five distinctive acceleration profiles were designed for tip-in conditions and evaluated by 15 highly experienced experts using the paired comparison method. Evaluations were conducted across three scenarios: light tip-in at 30 km/h, middle tip-in at 30 km/h, and middle tip-in at 60 km/h. Experimental results revealed distinct preferences based on driving conditions. For light tip-in at 30 km/h, drivers favored linear acceleration profiles with smaller jerk magnitudes and kurtosis. Conversely, for middle tip-in conditions at both 30 and 60 km/h, drivers preferred acceleration profiles exhibiting rapid initial acceleration followed by a smooth transition. However, at 60 km/h, a preference for higher jerk and steeper gradients was observed. Correlation analyses provided insights into the relationship between subjective preferences and dynamic characteristics of acceleration profiles. This study contributes practical guidance for designing optimal acceleration profiles aligned with driver preferences, thereby enhancing drivability and overall user experience in electric vehicles.

Suggested Citation

  • Seonghyeon Kim & Jaesik Yang, 2024. "Toward better drivability: Investigating user preferences for tip-in acceleration profiles in electric vehicles," PLOS ONE, Public Library of Science, vol. 19(12), pages 1-26, December.
    • Handle: RePEc:plo:pone00:0311504
    DOI: 10.1371/journal.pone.0311504
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    References listed on IDEAS

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    1. Firth, David, 2005. "Bradley-Terry Models in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 12(i01).
    2. Zhang, Bo & Zhang, Jiangyan & Shen, Tielong, 2022. "Optimal control design for comfortable-driving of hybrid electric vehicles in acceleration mode," Applied Energy, Elsevier, vol. 305(C).
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