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采用改进卡尔曼滤波器PID控制的液压可变气门运动轨迹 被引量:2

Moving trajectory of hydraulic variable valve using improved Kalman filter PID control
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摘要 为了降低气门运动轨迹跟踪误差,提高气门落座的稳定性,采用液压可变阀驱动系统,并对气门运动轨迹跟踪效果进行仿真验证。创建了配气机构液压可变阀驱动系统,并介绍其工作原理。根据牛顿第二定律和热力学定律,推导出活塞运动位移方程式、排气阶段废气的温度和压力变化方程式。利用旋转阀控制液压缸的进油和出油,从而得出液压流量表达式。引用传统PID控制器,采用粒子群算法和卡尔曼滤波器对PID控制器进行改进,给出了气门升程在线控制系统的优化流程。采用Matlab软件对气门升程、气门速度和气门加速度跟踪误差进行仿真,并且与传统PID控制跟踪误差进行对比。结果显示:采用传统PID控制系统,气门升程、气门速度和气门加速度跟踪误差较大;而采用改进PID控制系统,气门升程、气门速度和气门加速度跟踪误差较小。采用液压可变阀驱动系统,气门升程运动轨迹跟踪精度较高,从而提高了气门落座的稳定性。 In order to reduce the tracking error of valve trajectory and improve the stability of valve seating,a hydraulic variable valve drive system was adopted,and the tracking effect of valve trajectory was simulated and verified.The hydraulic variable valve drive system of valve train is established and its working principle is introduced.According to Newton’s second law and thermodynamic law,the displacement equation of piston motion,the temperature and pressure change equation of exhaust gas in exhaust stage are deduced.The rotary valve is used to control the oil intake and output of the hydraulic cylinder,and the expression of the hydraulic flow rate is obtained.The traditional PID controller is introduced,and the particle swarm optimization algorithm and Kalman filter are used to improve the PID controller.The optimization process of online valve lift control system is given.The tracking errors of valve lift,valve speed and valve acceleration are simulated with Matlab software,and compared with the tracking errors of traditional PID control.The results show that the tracking errors of valve lift,valve speed and valve acceleration are larger when using traditional PID control system,while the tracking errors of valve lift,valve speed and valve acceleration are smaller when using improved PID control system.With the hydraulic variable valve drive system,the tracking accuracy of valve lift trajectory is high,which improves the stability of valve seating.
作者 王刚 王晓东 王锐 WANG Gang;WANG Xiaodong;WANG Rui(Branch Courts of Engineer Technology,Changchun Vocational Institute of Technology,Changchun 130033,Jilin,China;College of Mechanical and Electronic Engineering,Changchun University of Technology,Changchun 130012,Jilin,China)
出处 《中国工程机械学报》 北大核心 2020年第5期406-411,共6页 Chinese Journal of Construction Machinery
基金 吉林省科技厅重点科技成果转化资助项目(20150307013GX)。
关键词 卡尔曼滤波器 粒子群算法 液压可变阀 气门升程 PID控制 Kalman filter particle swarm optimization hydraulic variable valve valve lift PID control
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