Lateral safety enhancement in a full dynamic vehicle model based on series active variable-geometry suspension
Publish Year: 1400
نوع سند: مقاله ژورنالی
زبان: English
View: 221
This Paper With 14 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_JCAM-52-1_010
تاریخ نمایه سازی: 21 اردیبهشت 1400
Abstract:
Today, the importance of providing safety and stability while paying attention to the ride comfort and providing road holding is of paramount importance. This issue has become more important due to the many accidents related to vehicle rollover. In this article, an attempt has been made to reduce the risk of rollover prevention of the vehicle while paying attention to the needs of the occupant and the road. In this research, an attempt has been made to reduce the overall acceleration of the GT vehicle by using a series of active variable geometry suspensions and by using a variety of control strategies such as Fuzzy PID, LQR, Sliding mode. In previous works, PID and Skyhook controllers have been used. However, in this study, the choice of the controllers is based on attention to accuracy and optimization while pay attention to control aims. This study was performed in conditions of severe asymmetric roughness and cornering maneuvers. The examination of the results shows an improvement of more than ۲۰% for the goal of vehicle stability while providing other suspension goals. This performance improvement occurs with the effect of suspending variable geometry along with the use of a suitable controller. It should also be noted that the improvement achieved by consuming energy is far less than other suspensions, which is the strength of the research.
Keywords:
Authors
Amin Najafi
School of Automotive Engineering, Iran University of Science and Technology
Masoud Masih-Tehrani
School of Automotive Engineering, Iran University of Science and Technology
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :