低速行驶电动行李牵引车辆电机控制算法设计  

A Design of Motor Control Algorithm for Low-speed Electric Luggage Traction Vehicles

作　　者：赵国珍[1] ZHAO Guozhen(Anhui Communications Vocational&Technical College,Hefei,Anhui 230051)

机构地区：[1]安徽交通职业技术学院,安徽合肥230051

出　　处：《绵阳师范学院学报》2024年第8期52-59,共8页Journal of Mianyang Teachers＇ College

基　　金：安徽省教育厅高职院校职业教育提质培优行动计划项目(2021 TZPY 60);安徽省教育厅高等学校省级质量工程项目(2022cyxy009)。

摘　　要：在车辆低速行驶过程中,主要应用传统PI(比例-积分)策略实现车辆电机控制,控制参数不随环境扰动调整,使得控制处理产生的超调量较大.提出一种面向低速行驶的车辆电机控制算法,分析车辆电机的内部结构,并构建电机运行数学模型.应用粒子群算法进行迭代学习,得到电机参数辨识和跟踪结果,并找到参数跟踪波动曲线中的突变点.结合模糊控制策略和PI控制策略,搭建具有自整定能力的双闭环模糊PI控制器.利用包含步长调节机制的天牛须算法,进一步优化双闭环模糊PI控制器参数,通过控制突变点,实现低速行驶车辆电机高效控制.实验结果表明:所研究方法应用后,车辆电机各项控制参数产生的超调量都小于10%,可以保障车辆电机高效控制.During the low-speed driving process of vehicles,traditionally,PI(proportional integral)strategy is mainly used to achieve vehicle motor control,with control parameters not adjusted with environmental distur-bances,resulting in a large overshoot generated by control processing.Therefore,a vehicle motor control algorithm for low-speed driving is proposed.The internal structure of the vehicle motor was analyzed and a mathematical model for motor operation was constructed.Particle swarm optimization algorithm was applied for iterative learning to obtain motor parameter identification and track results and mutation points in the parameter tracking fluctuation curve.A dual closed-loop fuzzy PI controller with self-tuning capability was built by combining fuzzy control strat-egy and PI control strategy.Using the search algorithm of beetle antennae with a step size adjustment mechanism,we further optimized the parameters of the dual closed-loop fuzzy PI controller,and achieved efficient control of the motor of low-speed vehicles by controlling the mutation point.The experiment results showed that after the applica-tion of the studied algorithm,the overshoot generated by various control parameters of the vehicle motor was less than 10%,which could ensure efficient control of the vehicle motor.

关 键 词：低速行驶 车辆电机 矢量控制 状态变量 模糊控制器 参数优化 

分 类 号：TP206[自动化与计算机技术—检测技术与自动化装置]