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Hybrid Vehicle’s Real World Fuel Economy Development by Machine Learning of Behavior Pattern
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- Jinno Kunihiko
- トヨタ自動車(株)
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- Inui Kiwamu
- トヨタ自動車(株)
Bibliographic Information
- Other Title
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- 行動パターン学習によるハイブリッド車の燃費向上技術
- コウドウ パターン ガクシュウ ニ ヨル ハイブリッドシャ ノ ネンピ コウジョウ ギジュツ
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Description
Thermal management technology to improve fuel economy is required for Hybrid vehicle during warm-up in winter. A predictive thermal management control method was developed in this study. Based on predicted long term parking location by vehicle usage, this study developed a method to manage simultaneous vehicle warm-up and battery charging. Tested winter fuel economy was improved and long term parking locations could be predicted with high accuracy with this control.
Journal
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- Transactions of Society of Automotive Engineers of Japan
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Transactions of Society of Automotive Engineers of Japan 49 (2), 307-310, 2018
Society of Automotive Engineers of Japan
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Details 詳細情報について
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- CRID
- 1390282679589843584
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- NII Article ID
- 130006565503
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- NII Book ID
- AA1260263X
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- ISSN
- 24339652
- 18830811
- 02878321
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- NDL BIB ID
- 028916595
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL Search
- CiNii Articles
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- Abstract License Flag
- Disallowed