老旧小区移动充电车避障路径规划与跟踪控制

doi:10.16731/j.cnki.1671-3133.2025.08.005

现代制造工程 ›› 2025, Vol. 539 ›› Issue (8): 39-47.doi: 10.16731/j.cnki.1671-3133.2025.08.005

老旧小区移动充电车避障路径规划与跟踪控制

覃频频¹, 梁文彬¹, 李龙杰², 叶磊²

1 广西大学机械工程学院,南宁 530004;
2 柳州五菱汽车工业有限公司,柳州 545007

出版日期:2025-08-18 发布日期:2025-09-09
通讯作者: 叶磊,硕士,高级工程师,兼职硕士生导师,主要研究方向为线控底盘与控制系统。E-mail:kf_ddd@163.com。
作者简介:覃频频,博士,副教授,硕士生导师,主要研究方向为车辆动力学与系统安全。E-mail:qpinpin@gxu.edu.cn;
基金资助:
广西科技重大专项项目(桂科AA22068055,桂科AA23062001);中央引导地方科技发展资金项目(桂科ZY24212060)

Obstacle avoidance path planning and tracking control for mobile charging vehicles in old neighborhoods

QIN Pinpin¹, LIANG Wenbin¹, LI Longjie², YE Lei²

1 School of Mechanical Engineering,Guangxi University,Nanning 530004,China;
2 Liuzhou Wuling Automobile Industry Co.,Ltd.,Liuzhou 545007,China

Online:2025-08-18 Published:2025-09-09

摘要/Abstract

摘要： 针对移动充电车在老旧小区狭窄道路主动避障与跟踪控制存在的问题,提出了一种基于道路模型的避障路径规划与低速跟踪控制策略。首先,构建了小区道路模型,在考虑路径质量与道路风险势场的前提下,采用五次项路径规划算法实现最优避障路径规划。其次,设计了一种基于遗传非线性递减权值粒子群优化算法(Genetic Nonlinear Decreasing Weight Particle Swarm Optimization algorithm,GA-NLDWPSO)的线性二次型调节器(Linear Quadratic Regulator,LQR)横向和速度补偿PID纵向的控制器,实现对规划路径的跟踪。最后,搭建PreScan、CarSim和MATLAB/Simulink联合仿真平台,验证所提出方法的有效性。仿真结果表明,所提出的方法能够确保移动充电车在安全避障的前提下,针对其低速特点,实现速度控制的快速响应,稳定后最大纵向速度误差为0.059 km/h,最大横向误差有效降低,显著提高了跟踪精度和稳定性。

关键词: 移动充电车, 避障路径规划, 遗传非线性递减权值粒子群算法, 低速控制

Abstract: Aiming at the problem of active obstacle avoidance and tracking control of mobile charging vehicles on narrow roads in old neighborhoods,a road model based obstacle avoidance path planning and low-speed tracking control strategy was proposed. Firstly,a community road model was constructed,and a quintic term path planning algorithm was used to achieve optimal obstacle avoidance path planning,taking into account path quality and road risk potential fields.Secondly,a Linear Quadratic Regulator (LQR) lateral and speed compensation PID longitudinal controller optimized by Genetic Nonlinear Decreasing Weight Particle Swarm Optimization algorithm (GA-NLDWPSO) was designed to achieve tracking of the planned path.Finally,a joint simulation platform of PreScan,CarSim and MATLAB/Simulink was built to verify the effectiveness of the proposed method. The simulation results showed that the proposed method could ensure the safe obstacle avoidance for mobile charging vehicles and achieved rapid speed control based on its low-speed characteristics. In response,the maximum longitudinal velocity error after stabilization was 0.059 km/h,and the maximum lateral error was effectively reduced,significantly improving tracking accuracy and stability.

Key words: mobile charging vehicle, obstacle avoidance path planning, Genetic Nonlinear Decreasing Weight Particle Swarm Optimization algorithm (GA-NLDWPSO), low-speed control

中图分类号:

TP273

覃频频, 梁文彬, 李龙杰, 叶磊. 老旧小区移动充电车避障路径规划与跟踪控制[J]. 现代制造工程, 2025, 539(8): 39-47.

QIN Pinpin, LIANG Wenbin, LI Longjie, YE Lei. Obstacle avoidance path planning and tracking control for mobile charging vehicles in old neighborhoods[J]. Modern Manufacturing Engineering, 2025, 539(8): 39-47.

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老旧小区移动充电车避障路径规划与跟踪控制

Obstacle avoidance path planning and tracking control for mobile charging vehicles in old neighborhoods

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