Adaptive shift scheduling strategy introducing neural network in automatic transmission |
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| Institution: | 1. Kyoto Transmission Designing, Transmission & Final Drive Engineering Department, Office of Passenger Car Development & Engineering, Mitsubishi Motors Corporation, 1, Tatsumi-cho, Uzumasa Ukyo-ku, Kyoto, 616 Japan;2. Okazaki Transmission Testing, Transmission & Final Drive Engineering Department, Office of Passenger Car Development & Engineering, Mitsubishi Motors Corporation, 1, Nakashinkiri, Hashime-cho, Okazaki, Aichi 444 Japan;1. Adjunct Clinical Professor of Surgery, Stanford University, Stanford, California;2. Department of Surgery, Marin Health Medical Center (Formerly Marin General Hospital), Greenbrae, California;3. Chair, Department of Surgery, Medical Director for Trauma Services, Marin Health Medical Center, Greenbrae, California;4. Trauma Services, Marin Health Medical Center, Greenbrae, California;5. 528 Hospital Center, Ft. Bliss, Texas;6. Department of Neurosurgery, University of California, San Francisco, California;1. Engineering Research Center of Advanced Driving Energy-saving Technology, Ministry of Education, Chengdu, 610031, People’s Republic of China;2. School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, 610031, People’s Republic of China |
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| Abstract: | Conventional automatic transmissions, which have fixed shift patterns, sometimes show inconvenient shifting patterns, especially in uphill and downhill driving. In order to improve the driveability for these road conditions, Mitsubishi developed an adaptive shift logic called “Fuzzy shift” in 1992. Since then, further evolutional shift scheduling strategies has been developed to cover more extensive road conditions. This paper introduces neural network, learning and continuous variable shift patterns control incorporating this strategy. |
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