Gearshift Overlap for Multistep Downshift of Automatic Transmissions Based on Iterative Learning Control

• Published in: IEEE/ASME transactions on mechatronics 2024-02, Vol.29 (1), p.224-236
• Main Authors: Dong, Peng, Li, Junqing, Guo, Wei, Wang, Shuhan, Xu, Xiangyang, Mao, Feihong, Liu, Yi
• Format: Article
• Language: English
• Subjects: Automated calibration; Automatic control; automatic transmission; Automatic transmissions; Calibration; Clutches; Dynamic response; Engines; Friction; Gears; gearshift overlap; Iterative learning control; iterative learning control (ILC); Learning; multistep downshift; Shafts; Torque; Vehicle dynamics
• ISSN: 1083-4435; 1941-014X
• DOI: 10.1109/TMECH.2023.3272980

In order to improve the dynamic response of vehicles to sudden acceleration or climbing requests of drivers, automatic transmissions generally perform multistep downshift to provide more wheel torque. The shift response is crucial for vehicle drivability. However, sequential downshift delays the wheel torque response. Existing downshift with more than two shifting elements (SE) obtains all clutches' control parameters from scratch and, consequently, requires a large calibration effort. To address this issue, this article overlaps two single well-calibrated clutch-to-clutch shifts instead of calibrating all clutches. A factor for determining the overlap degree of two single shifts is defined, and the influence of different overlap factors on shift jerk is evaluated. Iterative learning control (ILC) including its tuning guideline is devised to reduce the shift jerk. The gearshift overlap strategy and ILC are validated through simulations and vehicle tests of 8-4-3 power-on downshift, showing a significant shift time reduction without sacrificing comfort. This work fills the gap for control and automated calibration of gearshift with more than two SEs.