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燃油计量装置中有限转角力矩电机的集成物理建模与最优控制方法

Integrated Physical Modeling and Optimal Control Method of Limited-Angle Torque Motor in Fuel Metering Apparatus.

作者信息

Chen Qian, Sheng Hanlin, Jiang Shengbin

机构信息

College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.

Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110117, China.

出版信息

Micromachines (Basel). 2022 Jun 15;13(6):949. doi: 10.3390/mi13060949.

Abstract

Limited-angle torque motor (LATM) is a critical component to precisely drive the valve angle of an engine's fuel metering apparatus and accurately measure the fuel flow, and research on it is of great significance. Thus, the LATM of a certain kind is regarded as the research object in this paper. Firstly, a Simscape-based LATM integrated physical modeling method is proposed, which can better demonstrate the real operational characteristics of a motor, compared with the current mathematical model. Secondly, a Proportional-Integral-Derivative (PID) parameter self-tuning method based on a constriction factor particle swarm optimization (CPSO) algorithm is broached since it is difficult to tune due to a large number of multi-loop cascade PID control parameters. Simulation and experimental results showed that the control performance increases by 40% in the triple closed-loop PID control system with a stronger disturbance rejection, simpler design, and quickly responds when compared with the previous empirical tuning method. The triple closed-loop PID control system comprises an angle loop + angle velocity loop + current loop and technically supports the engineering application design of motors.

摘要

有限角度扭矩电机(LATM)是精确驱动发动机燃油计量装置的阀门角度并准确测量燃油流量的关键部件,对其进行研究具有重要意义。因此,本文以某一种有限角度扭矩电机为研究对象。首先,提出了一种基于Simscape的有限角度扭矩电机集成物理建模方法,与当前的数学模型相比,该方法能够更好地展示电机的实际运行特性。其次,鉴于大量多回路串级PID控制参数难以整定,提出了一种基于收缩因子粒子群优化(CPSO)算法的比例-积分-微分(PID)参数自整定方法。仿真和实验结果表明,与先前的经验整定方法相比,在具有更强抗干扰能力、设计更简单且响应迅速的三闭环PID控制系统中,控制性能提高了40%。该三闭环PID控制系统包括角度环+角速度环+电流环,从技术上支持了电机的工程应用设计。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e11/9227499/cf7e0571eb10/micromachines-13-00949-g001.jpg

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