Energy benchmark for energy-efficient path planning of the automated guided vehicle

Luoke Hu; Xiaoliang Zhao; Weipeng Liu; Wei Cai; Kangkang Xu; Zhongwei Zhang

doi:10.1016/j.scitotenv.2022.159613

Energy benchmark for energy-efficient path planning of the automated guided vehicle

Sci Total Environ. 2023 Jan 20;857(Pt 3):159613. doi: 10.1016/j.scitotenv.2022.159613. Epub 2022 Oct 20.

Authors

Luoke Hu¹, Xiaoliang Zhao², Weipeng Liu¹, Wei Cai³, Kangkang Xu⁴, Zhongwei Zhang⁵

Affiliations

¹ Department of Mechanical Engineering, School of Engineering, Zhejiang University City College, Hangzhou, 310015, China.
² School of Software Technology, College of Computer Science and Technology, Zhejiang University, Ningbo, 315048, China.
³ College of Engineering and Technology, Southwest University, Chongqing, 400715, China.
⁴ School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou, 510006, China. Electronic address: xukangkang@gdut.edu.cn.
⁵ School of Mechanical and Electrical Engineering, Henan University of Technology, Zhengzhou, 450001, China.

PMID: 36273562
DOI: 10.1016/j.scitotenv.2022.159613

Abstract

The automated guided vehicle (AGV) is a piece of promising advanced transport equipment that has been widely used in flexible manufacturing systems to increase productivity and automation. Previous studies about the AGV focused on improving the capacities of perception, navigation, and anti-collision as well as reducing the transport time, cost, and distance, but insufficient attention was paid to the energy consumption (EC) reduction of AGV. The energy benchmark is recognised as an effective analytical methodology and management tool that can improve energy efficiency. Nonetheless, research on the energy benchmark for the AGV is lacking. To finish a transport task, many AGV path plans are feasible, and we develop an energy benchmark to evaluate each path plan and select the energy-saving one. We also establish a dynamic rating system of energy efficiency which is consistent with the energy-saving potentials of the transport task. The case study shows that the transport EC is reduced by 10.98 %, validating the proposed energy benchmark methodology. In addition, the effects of AGV path plans on the EC of machine tools at the workstations are analysed. Lastly, we explore the relationship between the energy efficiency of AGV path plans and the locations of workstations.

Keywords: Automated guided vehicle; Energy benchmark; Energy efficiency; Path planning; Sustainable manufacturing.

MeSH terms

Benchmarking*