Observer-Based Torque Vector Control of a Four In-Wheel Motor-Driven Electric Vehicles Considering with Unbalanced Electric Magnetic Field
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- 形態
- 価格
- 一般価格(税込)：￥6,600 会員価格(税込)：￥5,280
- 文献・情報種別
- SAE Paper
No.2022-01-0915
- 掲載ページ
- 1-11(Total 11 p)
- 発行年月
- 2022年 3月
- 出版社
- SAE International
- 言語
- 英語
- イベント
- WCX SAE World Congress Experience 2022
書誌事項
| 著者（英） | 1) Jiansen Yang, 2) Zhenfeng Wang, 3) Xin Li, 4) Yugang Zhu, 5) Yanxin Nie, 6) HongLiang Li |
|---|---|
| 勤務先（英） | 1) CATARC (Tianjin) AERI Co., Ltd., 2) CATARC (Tianjin) AERI Co., Ltd., 3) CATARC (Tianjin) AERI Co., Ltd., 4) CATARC (Tianjin) AERI Co., Ltd., 5) CATARC (Tianjin) AERI Co., Ltd., 6) CATARC (Tianjin) AERI Co., Ltd. |
| 抄録（英） | The accuracy and range of chassis control for a four in-wheel motor (IWM)-driven electric vehicles (EVs), especially in observer-based EVs control for improving road handling and ride comfort, is a challenging task for the IWM-driven vehicle system. Due to the high fatality rate caused by inaccurate state-based control algorithm, how to precisely acquire movement state and chose the reasonable observer-based control algorithm for IWM-driven EVs become a hot topic in both academia and industry. Simultaneously, uncertainty is always existing, e.g., varying road excitation, variable system parameters or nonlinear structure. Meanwhile, the coupling effects between the non-ideal IWM actuator and vehicle are ignored under the assumption of an ideal actuator. To deal with the above mentioned, the paper presents an observer-based control approach, which combines Takagi-Sugeno (T-S) fuzzy observer and torque vector control algorithm, to further improve the chassis performance for IWM-driven EVs under the double lane change steering input. First, a nonlinear full-car model considering with the unbalanced electric magnetic force is established to describe vehicle lateral-vertical dynamics. Second, a fuzzy T-S observer is developed to estimate the state of slip angle and yaw rate in real time. The stability of the proposed observer is calculated using linear matrix inequalities (LMI). Then, a novel observer-based torque vector model predictive control (MPC) strategy is proposed to optimize the chassis performance of IWM-driven EVs. Finally, combing with a test rig platform, the proposed observer-based control algorithm is validated under the double lane change steering input. The research achievements develop a reasonable algorithm to apply to the improving chassis performance for a four IWM-driven EVs. 翻訳 |
