{"title":"对数分段拉普拉斯变换及其在电池诊断中的应用","authors":"N. Nagaoka, T. Ishii","doi":"10.1109/UPEC.2017.8232026","DOIUrl":null,"url":null,"abstract":"A Laplace transform with a logarithmic segmented sampling-method is proposed in this paper. The method gives a long observation time with a small number of samples in comparison with a conventional discrete Laplace transform (DLT) with an equally spaced sampling. The number of samples is decreased without the reduction in the analysis range. The proposed method is applied to an estimation of a battery internal impedance and its results are compared with those obtained by the conventional method. The computational time of the proposed method is reduced to 2.38 %. The maximum difference between the theoretical and calculated battery impedances is less than 2 %. The algorithm decreasing the number of samples is realized without reducing the sensitivity for a battery diagnosis system. The proposed method realizes a diagnosis system at a low cost because the computational load for the battery diagnosis is greatly reduced.","PeriodicalId":272049,"journal":{"name":"2017 52nd International Universities Power Engineering Conference (UPEC)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"A logarithmic segmented Laplace transform and its application to a battery diagnosis\",\"authors\":\"N. Nagaoka, T. Ishii\",\"doi\":\"10.1109/UPEC.2017.8232026\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A Laplace transform with a logarithmic segmented sampling-method is proposed in this paper. The method gives a long observation time with a small number of samples in comparison with a conventional discrete Laplace transform (DLT) with an equally spaced sampling. The number of samples is decreased without the reduction in the analysis range. The proposed method is applied to an estimation of a battery internal impedance and its results are compared with those obtained by the conventional method. The computational time of the proposed method is reduced to 2.38 %. The maximum difference between the theoretical and calculated battery impedances is less than 2 %. The algorithm decreasing the number of samples is realized without reducing the sensitivity for a battery diagnosis system. The proposed method realizes a diagnosis system at a low cost because the computational load for the battery diagnosis is greatly reduced.\",\"PeriodicalId\":272049,\"journal\":{\"name\":\"2017 52nd International Universities Power Engineering Conference (UPEC)\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 52nd International Universities Power Engineering Conference (UPEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/UPEC.2017.8232026\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 52nd International Universities Power Engineering Conference (UPEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/UPEC.2017.8232026","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A logarithmic segmented Laplace transform and its application to a battery diagnosis
A Laplace transform with a logarithmic segmented sampling-method is proposed in this paper. The method gives a long observation time with a small number of samples in comparison with a conventional discrete Laplace transform (DLT) with an equally spaced sampling. The number of samples is decreased without the reduction in the analysis range. The proposed method is applied to an estimation of a battery internal impedance and its results are compared with those obtained by the conventional method. The computational time of the proposed method is reduced to 2.38 %. The maximum difference between the theoretical and calculated battery impedances is less than 2 %. The algorithm decreasing the number of samples is realized without reducing the sensitivity for a battery diagnosis system. The proposed method realizes a diagnosis system at a low cost because the computational load for the battery diagnosis is greatly reduced.