廉胤东1　苟彬2　李超磊1　李泽明1　余锦伟3　曾俊海4

（1.南方电网供应链科技（广东）有限公司，广东 广州 510630  

2.广东电网有限责任公司电力科学研究院，广东 广州 510062  

3.中国电信股份有限公司广东研究院，广东 广州 510660

4.华南理工大学自动化科学与工程学院，广东 广州 510641）

摘要：针对电力仓储环境下多自动导引车（AGV）系统的任务效率较低、能耗较高的问题，提出一种基于启发式能耗优化的电力仓储分布式多AGV路径规划方法。首先，提出两轮差速驱动AGV运动模型，引入驱动电机参数；然后，通过分析AGV车载锂电池的放电特性，建立AGV能耗模型；接着，分析AGV的主要能耗环节与路径网络特性，提出增加有限路径网络资源利用率、减少AGV移动时间的节能策略，并在AGV运动规划过程中引入时间约束；最后，提出一种改进时间约束的启发式路径规划方法，将能耗转化为路径网络占用时间，以实现系统能耗最小。数值模拟实验数据表明，该方法提高了多AGV系统的任务效率，有效降低了系统能耗。

关键词：多AGV系统；路径规划；能耗优化；启发式搜索算法；电力仓储；分布式规划 

中图分类号：TP242.6           文献标志码：A          文章编号：1674-2605(2024)05-0006-08

DOI：10.3969/j.issn.1674-2605.2024.05.006                    开放获取

Distributed Multi-AGV Path Planning Method Based on Heuristic Energy Consumption Optimization for Power Storage 

LIAN Yindong1  GOU Bin2  LI Chaolei1  LI Zeming1  YU Jinwei3  ZENG Junhai4

(1.Southern Power Grid Supply Chain Technology (Guangdong) Co., Ltd., Guangzhou 510630, China  

2.Electric Power Research Institute of Guangdong Power Grid Co., Ltd., Guangzhou 510062, China

3.Guangdong Research Institute of China Telecom Corporation Limited, Guangzhou 510660, China

4.School of Automation Science and Engineering, South China University of Technology, 

Guangzhou 510641, China) 

Abstract: A distributed multi-AGV path planning method based on heuristic energy optimization for power storage is proposed to address the issues of low task efficiency and high energy consumption in multi-AGV systems in the power storage environment. Firstly, a two wheel differential drive AGV motion model is proposed, and the driving motor parameters are introduced; Then, by analyzing the discharge characteristics of AGV onboard lithium batteries, an AGV energy consumption model is established; Next, analyze the main energy consumption links and path network characteristics of AGV, propose energy-saving strategies to increase the utilization of limited path network resources and reduce AGV movement time, and introduce time constraints in the AGV motion planning process; Finally, a heuristic path planning method with improved time constraints is proposed, which converts energy consumption into the time occupied by the path network to achieve the minimum system energy consumption. Numerical simulation experimental data shows that this method improves the task efficiency of multi-AGV systems and effectively reduces system energy consumption.

Keywords: multi-AGV system; path planning; energy consumption optimization; heuristic search algorithm; power storage; distributed planning