Personalized Steering Feel Control Based on Driving Style Recognition and Closed-Loop Motion Regulation
Year: 2025
Type: article
Abstract: Against the backdrop of the continuous expansion of the automotive industry, consumer demand is undergoing a profound shift from quantity to quality. Conventional steering systems, due to their lack of dynamic adaptation to driver styles, struggle to meet the diverse needs of different user groups. To address this challenge, this study proposes a personalized steering feel control strategy, which achieves precise control of target steering feel by integrating driving style identification and closed-loop control strategies. Subsequently, this study validates the effectiveness and robustness of the proposed control method using a driving simulator. The results demonstrate that the proposed control strategy delivers effective performance across multiple operating conditions, providing drivers with a comfortable and satisfying steering feel, thereby enhancing their driving experience.
Source: Sensors
DOI: 10.3390/s25247686
Authors: Hsin Guan, Yimeng Song, Pingping Lu, Chao Dai, Shenzhen Gao, Jun Zhan, Chunguang Duan, Yinsheng Liao, Binggen Zhao
Institutions: Jilin University, BYD (China)
Language: English
Subfield: Automotive Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,137
Awards: G166881281, G8409330207
OpenAlex ID: W4417466779
