dc.contributor.author | Zhang, Y | |
dc.contributor.author | Guo, C | |
dc.contributor.author | Li, G | |
dc.contributor.author | Liu, Y | |
dc.contributor.author | Chen, Z | |
dc.date.accessioned | 2020-04-15T09:17:02Z | |
dc.date.available | 2020-04-15T09:17:02Z | |
dc.date.issued | 2020-04-01 | |
dc.identifier.citation | Zhang, Yuanjian et al. "Cooperative Control Strategy For Plug-In Hybrid Electric Vehicles Based On A Hierarchical Framework With Fast Calculation". Journal Of Cleaner Production, vol 251, 2020, p. 119627. Elsevier BV, doi:10.1016/j.jclepro.2019.119627. Accessed 15 Apr 2020. | en_US |
dc.identifier.issn | 0959-6526 | |
dc.identifier.other | ARTN 119627 | |
dc.identifier.other | ARTN 119627 | |
dc.identifier.uri | https://qmro.qmul.ac.uk/xmlui/handle/123456789/63582 | |
dc.description.abstract | Developing optimal control strategies with capability of real-time implementation for plug-in hybrid electric vehicles (PHEVs) has drawn explosive attention. In this study, a novel hierarchical control framework is proposed for PHEVs to achieve the instantaneous vehicle-environment cooperative control. The mobile edge computation units (MECUs) and the on-board vehicle control units (VCUs) are included as the distributed controllers, which enable vehicle-environment cooperative control and reduce the computation intensity on the vehicle by transferring partial work from VCUs to MECUs. On this basis, a novel cooperative control strategy is designed to successively achieve the energy management planned by the iterative dynamic programming (IDP) in MECUs and the energy utilization management achieved by the model predictive control (MPC) algorithm in the VCU. The performance of raised control strategy is validated by simulation analysis, highlighting that the cooperative control strategy can achieve superior performance in real-time application that is close to the global optimization results solved offline. | en_US |
dc.publisher | Elsevier | en_US |
dc.relation.ispartof | JOURNAL OF CLEANER PRODUCTION | |
dc.subject | Cooperative control strategy | en_US |
dc.subject | Hierarchical framework | en_US |
dc.subject | Iterative dynamic programming (IDP) | en_US |
dc.subject | Model predictive control (MPC) | en_US |
dc.subject | Plug-in hybrid electric vehicles (PHEVs) | en_US |
dc.title | Cooperative control strategy for plug-in hybrid electric vehicles based on a hierarchical framework with fast calculation | en_US |
dc.type | Article | en_US |
dc.rights.holder | © 2019 Elsevier Ltd. | |
dc.identifier.doi | 10.1016/j.jclepro.2019.119627 | |
pubs.author-url | http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000510823700037&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=612ae0d773dcbdba3046f6df545e9f6a | en_US |
pubs.notes | Not known | en_US |
pubs.publication-status | Published | en_US |
pubs.volume | 251 | 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 |