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dc.contributor.author | Zubkov E.V. | |
dc.date.accessioned | 2021-02-25T06:54:46Z | |
dc.date.available | 2021-02-25T06:54:46Z | |
dc.date.issued | 2020 | |
dc.identifier.uri | https://dspace.kpfu.ru/xmlui/handle/net/161477 | |
dc.description.abstract | © 2020 IEEE. The article discusses the construction of a neuro-fuzzy model of diesel fuel consumption in various modes of its operation. The structure of a neuro-fuzzy network trained according to the results of field tests is presented. To train the neural network, a hybrid method was used in the form of an error back propagation algorithm and a least squares method. In the process of training, the parameters of the neural-fuzzy network were selected that provide the maximum error of an individual measurement of 3.5375% with an average error of the model of 0.4429%. The neuro-fuzzy diesel model makes it possible to simulate various modes of its operation in accordance with the test cycle ETC EK UN No. 49. Using well-known optimization methods from the obtained model of fuel consumption under unsteady loads, it is possible to determine diesel parameters close to optimal when calibrating the electronic control unit. | |
dc.subject | diesel | |
dc.subject | fuel consumption | |
dc.subject | load | |
dc.subject | neural-fuzzy network | |
dc.subject | simulation | |
dc.subject | speed | |
dc.title | Neuro-Fuzzy Modeling of Diesel Fuel Consumption under Dynamic Loads | |
dc.type | Conference Paper | |
dc.collection | Публикации сотрудников КФУ | |
dc.relation.startpage | 390 | |
dc.source.id | SCOPUS-2020-SID85093957596 |