摘要
为提高车辆紧急转向时的敏捷性和安全性,提出了一种以主动横向稳定杆系统为执行部件的基于转向意图的车辆敏捷性控制策略。对车辆转向时轮荷转移的侧倾动力学机理进行分析,开发了一种改进的驾驶员转向意图识别方法。根据转向意图和车辆侧倾动力学机理动态分配前后轴上左右车轮载荷,引入稳定性控制方法,进而提升车辆行驶过程中的敏捷性控制策略。搭建Simulink-CarSim整车模型进行仿真验证。仿真结果表明,相对于传统车辆,有主动稳定杆控制的车辆转向盘转角使用量减小约9%,质心侧倾角峰值减小约22%,同时横摆角速度提高4%,使用较小的转向盘转角实现紧急转向控制,提高横摆转向响应,提升车辆的敏捷性和稳定性。最后,搭建ECU在环试验台验证了仿真算法,可为后续的稳定杆样车开发提供参考。
In order to improve the agility and safety of emergency steering,a steering intention-based agility control strategy based on active lateral stabilizer bar system was proposed.The rolling dynamics mechanism of wheel load transfer during steering is analyzed and an improved driver steering intention recognition method is developed.According to the steering intention and the vehicle roll dynamics mechanism,the left and right wheel loads on the front and rear axles were dynamically distributed,and the stability control method was introduced to improve the agility control strategy during vehicle driving.Simulink-CarSim vehicle model was built for simulation and verification.The simulation results show that compared with traditional vehicles,the use of steering wheel angle decreases by about 9%,the peak angle of centroid side angle decreases by about 22%,and the yaw angle speed increases by 4%.Emergency steering control is achieved by using smaller steering wheel angle to improve the yaw steering response,and the agility and stability of the vehicle are enhanced.Finally,the simulation algorithm is verified on the ECU in-the-loop test bench and laid the foundation for the subsequent development of stabilizer rod prototypes.
作者
陈磊
王杨
董志圣
宋亚奇
CHEN Lei;WANG Yang;DONG Zhi-sheng;SONG Ya-qi(State Key Laboratory of Integrated Technology of Automotive Vibration and Noise and Safety Control,Changchun 130011,China;KH Automotive Technologies(Huzhou)Co.,Ltd.,Huzhou 313002,China)
出处
《吉林大学学报(工学版)》
EI
CAS
CSCD
北大核心
2023年第5期1257-1263,共7页
Journal of Jilin University:Engineering and Technology Edition
基金
汽车振动噪声与安全控制综合技术国家重点实验室开放基金项目(FAWSKL2020KFJJC2)。
关键词
车辆工程
敏捷性控制
驾驶员意图识别
仿真验证
vehicle engineering
agility control
driver intention identification
simulation verification