拡張カルマンフィルターと統合端末のスライディングモード制御に基づく分散駆動電気自動車の階層的な横向安定制御戦略
Junzhu Wang1, Youqun Zhao1, Wei Gao1,2
1College of Energy and Power, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
PloS one
|February 12, 2026
まとめ
この研究は,状態推定のための拡張カルマンフィルタリング (EKF) と,ダイレクト・ヤウ・モーメント・コントロール (DYC) のための統合端末滑動モード制御 (ITSMC) を使用して,電気自動車の階層的な制御戦略を紹介しています. これにより,車両の安定性と安全性が向上します.
科学分野:
- 自動車工学 自動車工学
- コントロールシステム コントロールシステム
- ロボット工学 ロボット工学 ロボット工学
背景:
- 横方向の安定性は,特に分散駆動システムを備えた電気自動車では,車両の安全性にとって極めて重要です.
- 既存の制御戦略は,状態推定の不確実性や実際のトルク分布に苦戦することが多い.
研究 の 目的:
- 分散駆動電気自動車の横向的な安定性を高めるための階層的な制御戦略を提案する.
- 状態の見積もり,強固なヤウモントの生成,および実際のトルク実現の組み合わせた課題に対処するために.
主な方法:
- 拡張カルマンフィルター (EKF) を使用して,車両状態のリアルタイム推定 (横滑り角度,ヤウレート) を行います.
- インテグラル・ターミナル・スライディング・モード・コントロール (ITSMC) を使用したダイレクト・ヤウ・モメント・コントロール (DYC) システムの設計.
- 4つの車輪内モーターの最適制御ベースのトルク配分戦略の実施.
主要な成果:
- EKFは,状態の推定において高い精度を示した.
- ITSMC-DYC コントローラーは,横方向の安定性,軌道の追跡,運転の安全性を大幅に改善しました.
- ハードウェア・イン・ザ・ループ (HIL) テストは,現実的なシナリオで戦略の有効性を検証しました.
結論:
- 提案された階層的な制御戦略は,分散駆動電気自動車の横向的な安定性を効果的に高めます.
- 統合的アプローチは,既存の方法の限界を克服し,実用的な適用性を提供します.
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