Abstract
State of charge (SOC) management is necessary for electric vehicle (EV) driving safety and comfort. However, the SOC estimated by a human driver may differ from the actual SOC, inducing negative emotions and false charging behaviors. Currently, a model for explaining or estimating driver perceptions and emotions regarding SOC is lacking. Therefore, this paper proposes a Bayesian framework that explains and estimates human SOC perception and related emotions and experimentally verifies the model predictions. The results suggest that the deviations between actual SOC variations and driver expectations are necessary to determine the emotional experiences of drivers caused by managing SOC noise.
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Acknowledgements
This work was conducted in collaboration with Toyota Motor Corporation. The theoretical part of this study was supported by KAKEN No. 21H03528. We thank Mr. Hironori Miki and Mr. Kenji Tsuchiya of Toyota Motor Co. Ltd. for their cooperation. We also thank Prof. Tamotsu Murakami and the members of the Design Engineering Lab for supporting this project.
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Yanagisawa, H., Miyamoto, M. & Arima, S. Modelling of State of Charge Recognition: Use of a Bayesian Approach to Formulate Hidden State Perceptions and Emotions. Int. J. ITS Res. 20, 612–622 (2022). https://doi.org/10.1007/s13177-022-00313-5
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DOI: https://doi.org/10.1007/s13177-022-00313-5