{"title":"Limitations of the conventional phase advance method for constant power operation of the brushless DC motor","authors":"J. Lawler, J. Bailey, J. McKeever, J. Pinto","doi":"10.1109/SECON.2002.995581","DOIUrl":"https://doi.org/10.1109/SECON.2002.995581","url":null,"abstract":"The brushless DC motor (BDCM) has high-power density and efficiency relative to other motor types. These properties make the BDCM well suited for applications in electric vehicles provided a method can be developed for driving the motor over the 4 to 6:1 constant power speed range (CPSR) required by such applications. The present state of the art for constant power operation of the BDCM is conventional phase advance (CPA). In this paper, we identify key limitations of CPA. It is shown that the CPA has effective control over the developed power but that the current magnitude is relatively insensitive to power output and is inversely proportional to motor inductance. If the motor inductance is low, then the RMS current at rated power and high speed may be several times larger than the current rating. The inductance required to maintain RMS current within rating is derived analytically and is found to be largely relative to that of BDCM designs using high-strength rare earth magnets. Thus, the CPA requires a BDCM with a large equivalent inductance.","PeriodicalId":228265,"journal":{"name":"Proceedings IEEE SoutheastCon 2002 (Cat. No.02CH37283)","volume":"167 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115280143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Advancing technology in wireless communications","authors":"D. Dunn, D.R. Brown, T.H. Avery","doi":"10.1109/SECON.2002.995642","DOIUrl":"https://doi.org/10.1109/SECON.2002.995642","url":null,"abstract":"This paper presents information on the recent advances of practical wireless networks for voice, data, image and video services in areas as small as an office and as large as the entire planet. This paper also addresses the potential economic and sociological impacts of mobile communications. We also discuss the next generation of cellular telephones, computer networks and pagers being developed to meet the demands of increased quality and capacity of a growing telecommunication market.","PeriodicalId":228265,"journal":{"name":"Proceedings IEEE SoutheastCon 2002 (Cat. No.02CH37283)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116856424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Multiple path planning for a group of mobile robots in a 3D environment using genetic algorithms","authors":"S. Zein-Sabatto, R. Ramakrishnan","doi":"10.1109/SECON.2002.995620","DOIUrl":"https://doi.org/10.1109/SECON.2002.995620","url":null,"abstract":"We present the development, simulation and testing of a new approach using genetic algorithms for planning optimum paths for a group of mobile robots to be moved from arbitrary starting positions to final a number of targets in a known multi-obstacle 3D environment. The factors considered for fording optimum paths for the group of mobile robots are the size and location of obstacles in the environment and the topographical elevations of the environment. First, a digital picture of the environment is transformed into a grid map by a graphic simulator. The obstacles are mapped according to their location, shape and size. The ground elevations are represented using a color-coding scheme. The resulting grid map of the environment contains information about initial positions of the robots, target positions, obstacle locations and ground elevation. Hence, the location and size of obstacles and altitudes of the elevation of the environment are presented in the map. The genetic algorithm modules takes information about the environment from the grid map and search for optimum paths to move a group of mobile robots to the specified targets.","PeriodicalId":228265,"journal":{"name":"Proceedings IEEE SoutheastCon 2002 (Cat. No.02CH37283)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130427150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}