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Summary & Details

Energy Management Based on Driving Pattern Classification Using Clustering Methods

クラスタリング手法による走行パターン分類を用いたエネルギーマネジメントの検討

Delivery: Available on this site

Format: PDF

Price: Non-members (tax incl.)：￥1,100 Members (tax incl.)：￥880

Publication code: 20266013

Paper/Info type: Proceedings (Autumn)

No.95-26

Pages: 1-4(Total 4 p)

Date of publication: Oct 2026

Publisher: JSAE

Language: Japanese

Event: 2026 JSAE Annual Congress (Autumn)

Detailed Information

Author(J)	1) 石橋雄登, 2) 林和樹, 3) 廣渡庸介, 4) 小塚信
Author(E)	1) Yuto Ishibashi, 2) Kazuki Hayashi, 3) Yosuke Hirowatari, 4) Makoto Kozuka
Affiliation(J)	1) 日産自動車, 2) 日産自動車, 3) 日産自動車, 4) 日産自動車
Affiliation(E)	1) Nissan Motor, 2) Nissan Motor, 3) Nissan Motor, 4) Nissan Motor
Abstract(J)	現行シリーズHEVのエネルギーマネジメントは複数の走行パターンを考慮した包括的な制御パラメータ設定となっている．これを走行パターンごとに最適化できれば燃費向上の余地がある．そこで，過去走行データから作成したクラスタにより走行パターンを分類し，それに応じた制御を適用することで，提案制御の有効性を確認した． Translation
Abstract(E)	Current energy management strategies for series HEVs rely on a comprehensive set of control parameters that take multiple driving patterns into account, leaving room for fuel-economy improvement through pattern-specific optimization. In this study, driving patterns are classified by clustering historical driving data, and pattern-optimized control is applied. The effectiveness of the proposed control is validated.

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