摘要
针对汽车悬架系统的时滞反馈控制问题,提出了一种时滞反馈控制参数的优化策略。首先,建立了时滞加速度反馈控制下1/4汽车悬架系统的力学和数学模型,利用理论推导得到了车身和车轮加速度幅值与路面激励频率之间的关系;其次根据特征值法分析了系统的稳定性,得到了反馈增益系数和时滞两参数平面上的系统稳定性分区图,并通过数值模拟验证了稳定性分析结果的正确性;最后,以最小的车身加速度幅值为优化目标,以反馈增益系数和时滞为优化参数,采用粒子群优化算法得到了不同路面激励频率下反馈增益系数和时滞的最优值。研究结果表明:相较于被动汽车悬架系统,最优时滞反馈控制下汽车悬架系统的隔振效果得到了明显的改善;在频率1 Hz^20 Hz内,车身的加速度幅值至少可降低19.60%。
Aiming at the problem of time delay feedback control of automobile suspension system,an optimization strategy of time-delayed feedback control parameters was proposed.Firstly,the mechanical and mathematical models of the 1/4 car suspension system under time-de-layed acceleration feedback control were established.The relationship between the body and wheel acceleration amplitude and the road sur-face excitation frequency was obtained by theoretical derivation.Then the stability of the system was analyzed according to the eigenvalue method,and the system stability partition map on the two-parameter plane with the feedback gain coefficient and time delay was obtained.The correctness of the stability analysis results was verified by numerical simulation.Finally,with the minimum body acceleration amplitude as the optimization objective,the particle swarm optimization algorithm was used to obtain the optimal values of feedback gain coefficient and time delay under different road excitation frequencies.The results indicate that the vibration isolation effect of the vehicle suspension system with the optimal time-delayed feedback control is significantly improved compared with the passive vehicle suspension system.Within the fre-quency range of 1 Hz^20 Hz,the acceleration amplitude of the body can be reduced by at least 19.60%.
作者
刘建均
孙艺瑕
李胜
LIU Jian-jun;SUN Yi-xia;LI Sheng(School of Mechanical and Automotive Engineering,Shanghai University of Engineering Science,Shanghai 201620,China)
出处
《机电工程》
CAS
北大核心
2020年第1期54-58,共5页
Journal of Mechanical & Electrical Engineering
基金
国家自然科学基金资助项目(11602135)
关键词
汽车悬架系统
隔振
时滞反馈控制
参数优化
粒子群优化算法
automobile suspension system
vibration isolation
time-delayed feedback control
parameter optimization
particle swarm opti-mization
