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The energy crisis and rising gas price in the 2000s led to a growing popularity of hybrid vehicles. Hyundai-Kia Motors has been challenging to develop the new efficient eco-technology since introducing the mild type compact hybrid electric vehicle for domestic fleet in 2004 to meet the needs of the increasing automotive-related environmental issues. Now Hyundai has recently debuted a full HEV for global market, Sonata Hybrid. This system is cost effective solution and developed with the main purpose of improving fuel consumption and providing fun to drive. Presenter Seok Joon Kim, Hyundai Motor Company

Development of the Nissan LEAF. Presenter Shigetoshi Tokuoka, Nissan Motor Co., Ltd.

Impact of driving patterns on fuel economy is significant in hybrid electric vehicles (HEVs). Driving patterns affect propulsion and braking power requirement of vehicles, and they play an essential role in HEV design and control optimization. Driving pattern conscious adaptive strategy can lead to further fuel economy improvement under real-world driving. This paper proposes a real-time driving pattern recognition algorithm for supervisory control under real-world conditions. The proposed algorithm uses reference real-world driving patterns parameterized from a set of representative driving cycles. The reference cycle set consists of five synthetic representative cycles following the real-world driving distance distribution in the US Midwestern region. Then, statistical approaches are used to develop pattern recognition algorithm. Driving patterns are characterized with four parameters evaluated from the driving cycle velocity profiles.