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Range Extension Autonomous Driving for Electric Vehicle Based on Optimal Vehicle Velocity Profile in Consideration of Cornering
Author(s) -
Ikezawa Yuta,
Fujimoto Hiroshi,
Kawano Daisuke,
Goto Yuichi,
Takeda Yusuke,
Sato Koji
Publication year - 2019
Publication title -
electrical engineering in japan
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.136
H-Index - 28
eISSN - 1520-6416
pISSN - 0424-7760
DOI - 10.1002/eej.23088
Subject(s) - automotive engineering , range (aeronautics) , driving range , engineering , electric vehicle , rotation (mathematics) , internal combustion engine , energy consumption , simulation , computer science , electrical engineering , aerospace engineering , physics , power (physics) , quantum mechanics , artificial intelligence
SUMMARY Electric vehicles (EVs) have been intensively studied in the last decade due to their environment‐friendly characteristics. However, the miles‐per‐charge of EVs is less than that of internal combustion engine vehicles. To improve the miles‐per‐charge, the authors’ group proposed a Range Extension Autonomous Driving (READ) system that minimizes consumption energy by optimizing the velocity profile. However, conventional systems can be applied to driving on only straight roads. Therefore, this study extends READ system to be applied to driving not only on straight roads but also on curved roads by modeling the vehicle rotation motion and the cornering resistance. The effectiveness of the proposed method is verified by simulations and experiments.