Andreis Stupans, Pāvels Maksimkins, Armands Senfelds, L. Ribickis
{"title":"Industrial robot energy consumption analysis for gravity-induced opposing force minimization","authors":"Andreis Stupans, Pāvels Maksimkins, Armands Senfelds, L. Ribickis","doi":"10.1109/energycon53164.2022.9830240","DOIUrl":null,"url":null,"abstract":"The paper describes the process of mapping industrial robot energy consumption. It is assumed that using an obtained energy map, an optimal robot workspace area can be found where the robot consumes less energy because opposing force of gravity is reduced. The study focuses on experimental approach rather than computer modelling to decrease complexity and time consumption of energy mapping. The robot’s consumed power measurements are taken in its multiple static positions with brakes released. The array of robot positions forms a vertical plane - one slice of the robot’s workspace. All the measured power data is combined into the 2D map that shows how much power the robot consumes in different areas of its workspace. Obtained data shows a correlation between energy consumption and robot position in its workspace.","PeriodicalId":106388,"journal":{"name":"2022 IEEE 7th International Energy Conference (ENERGYCON)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 7th International Energy Conference (ENERGYCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/energycon53164.2022.9830240","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The paper describes the process of mapping industrial robot energy consumption. It is assumed that using an obtained energy map, an optimal robot workspace area can be found where the robot consumes less energy because opposing force of gravity is reduced. The study focuses on experimental approach rather than computer modelling to decrease complexity and time consumption of energy mapping. The robot’s consumed power measurements are taken in its multiple static positions with brakes released. The array of robot positions forms a vertical plane - one slice of the robot’s workspace. All the measured power data is combined into the 2D map that shows how much power the robot consumes in different areas of its workspace. Obtained data shows a correlation between energy consumption and robot position in its workspace.