dc.contributor.author | Wu, Y | en_US |
dc.contributor.author | Zhang, Y | en_US |
dc.contributor.author | Li, G | en_US |
dc.contributor.author | Shen, J | en_US |
dc.contributor.author | Chen, Z | en_US |
dc.contributor.author | Liu, Y | en_US |
dc.date.accessioned | 2020-08-20T09:12:20Z | |
dc.date.available | 2020-07-10 | en_US |
dc.date.issued | 2020-10-01 | en_US |
dc.identifier.issn | 0360-5442 | en_US |
dc.identifier.other | ARTN 118366 | en_US |
dc.identifier.other | ARTN 118366 | en_US |
dc.identifier.uri | https://qmro.qmul.ac.uk/xmlui/handle/123456789/66461 | |
dc.relation.ispartof | ENERGY | en_US |
dc.rights | https://doi.org/10.1016/j.energy.2020.118366 | |
dc.subject | Plug-in hybrid electric vehicles | en_US |
dc.subject | Model predictive control | en_US |
dc.subject | Dynamic programming | en_US |
dc.subject | Neural network | en_US |
dc.subject | Pontryagin's minimum principle | en_US |
dc.title | A predictive energy management strategy for multi-mode plug-in hybrid electric vehicles based on multi neural networks | en_US |
dc.type | Article | |
dc.rights.holder | © 2020 Elsevier Ltd. | |
dc.identifier.doi | 10.1016/j.energy.2020.118366 | en_US |
pubs.author-url | http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000564661300007&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=612ae0d773dcbdba3046f6df545e9f6a | en_US |
pubs.notes | Not known | en_US |
pubs.publication-status | Published | en_US |
pubs.volume | 208 | en_US |
rioxxterms.funder | Default funder | en_US |
rioxxterms.identifier.project | Default project | en_US |
qmul.funder | Hierarchical Optimal Energy management of Electric Vehicles::Horizon 2020 | en_US |
qmul.funder | Hierarchical Optimal Energy management of Electric Vehicles::Horizon 2020 | en_US |