主动悬架
悬挂(拓扑)
刚度
隔离器
隔振
振动
簧载质量
加速度
控制理论(社会学)
工程类
流离失所(心理学)
振动控制
汽车工程
结构工程
计算机科学
控制(管理)
执行机构
声学
物理
数学
心理学
电子工程
心理治疗师
纯数学
人工智能
阻尼器
电气工程
同伦
经典力学
作者
Chunyu Wei,Xiangyun Pang
标识
DOI:10.1177/09544070251327898
摘要
People have high requirements for the comfort of vehicle riding, so active suspension control has always been a research hotspot. However, due to the difficulty in obtaining speed signals, the implementation of active suspension control is extremely difficult. In this paper, a novel active control method for vehicle suspension is proposed, which is based on the mechanical characteristics of a large-scale zero-stiffness isolator. The active control force obtained by the new method is only proportional to the relative displacement between the tire and the vehicle body, which is easily achievable in practical applications. Firstly, a physical model of a novel large-scale zero-stiffness vibration isolator is developed, and its segmented force characteristics are derived. Subsequently, the force characteristics between the tire and the vehicle body are integrated with the segmented force characteristics of the isolator to generate the active control force for the 2-degree-of-freedom (2-DOF) quarter vehicle active suspension model. Then, an analysis was conducted to demonstrate that the proposed active control method can maintain stability of the vehicle suspension system. Then, there representative road surfaces are selected for numerical simulation testing, and the results demonstrate the efficacy of the active control method in significantly enhancing suspension performance. In comparison to passive suspension, the vertical acceleration RMS values of the vehicle body are reduced by 76.2%, 77.8%, and 43.2% under the bump road, sine undulating road, and C-level road, respectively. Finally, to be closer to the actual situation, a new testing verification method is proposed. A multi-body dynamics model considering the existence of random nonlinear disturbances in the vehicle body is built and it is used to test the effectiveness of the control algorithm.
科研通智能强力驱动
Strongly Powered by AbleSci AI