Range Extension Autonomous Driving for Electric Vehicles Based on Optimization of Velocity Profile Considering Traffic Signal Information

Part of the Power Electronics and Power Systems book series (PEPS)


Electric vehicles (EVs) have been recognized as a practical solution to several environmental and energy conservation problems. The mileage per charge of EVs, however, is lower than the mileage of internal combustion engine vehicles (ICEVs). In this study, a range extension autonomous driving (READ) system that considers the traffic signal information is proposed. The proposed system optimizes the velocity profile of autonomous driving based on the precise loss models of vehicles. We conducted simulations and experiments that prove the effectiveness of the proposal in terms of mileage per charge.



This research was partly supported by the Industrial Technology Research Grant Program from New Energy and Industrial Technology Development Organization (NEDO) of Japan (number 05A48701d), Ministry of Education, Culture, Sports, Science and Technology grant (number 22246057 and 26249061), and the Core Research for Evolutional Science and Technology, Japan Science and Technology Agency (JST-CREST). The present study is a part of study being undertaken by the project team of JST-CREST named “Integrated Design of Local EMSs and their Aggregation Scenario Considering Energy Consumption Behaviors and Cooperative Use of Decentralized In-Vehicle Batteries.”


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Graduate School of Frontier SciencesUniversity of TokyoTokyoJapan

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