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 |
|