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The eco-driving effect of electric vehicles compared to conventional gasoline vehicles

1 Toyota Transportation Research Institute, 3-17, Motoshiro-cho, Toyota, Aichi, 471-0024 Japan
2 National Institute for Environmental Studies, 16-2, Onogawa, Tsukuba, Ibaraki 305-8506 Japan
3 Tsukuba University, 1-1-1, Tennoudai, Tsukuba, Ibaraki, 305-8573 Japan

Topical Section: Electric and Hybrid Vehicles

Eco-driving is attractive to the public, not only users of internal-combustion-engine vehicles (ICEVs) including hybrid electric vehicles (HEVs) but also users of electric vehicles (EVs) have interest in eco-driving. In this context, a quantitative evaluation of eco-driving effect of EVs was conducted using a chassis dynamometer (C/D) with an “eco-driving test mode.” This mode comprised four speed patterns selected from fifty-two real-world driving datasets collected during an eco-driving test-ride event. The four patterns had the same travel distance (5.2 km), but showed varying eco-driving achievement levels. Three ICEVs, one HEV and two EVs were tested using a C/D. Good linear relationships were found between the eco-driving achievement level and electric or fuel consumption rate of all vehicles. The reduction of CO2 emissions was also estimated. The CO2-reduction rates of the four conventional (including hybrid) vehicles were 10.9%–12.6%, while those of two types of EVs were 11.7%–18.4%. These results indicate that the eco-driving tips for conventional vehicles are effective to not only ICEVs and HEVs but also EVs. Furthermore, EVs have a higher potential of eco-driving effect than ICEVs and HEVs if EVs could maintain high energy conversion efficiency at low load range. This study is intended to support the importance of the dissemination of tools like the intelligent speed adaptation (ISA) to obey the regulation speed in real time. In the future, also in the development and dissemination of automated driving systems, the viewpoint of achieving the traveling purpose with less kinetic energy would be important.
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Copyright Info: © 2016, Hideki Kato, et al., licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution Licese (http://creativecommons.org/licenses/by/4.0)

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