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Article: Integrated Motion and Powertrain Predictive Control of Intelligent Fuel Cell/Battery Hybrid Vehicles

TitleIntegrated Motion and Powertrain Predictive Control of Intelligent Fuel Cell/Battery Hybrid Vehicles
Authors
KeywordsFuel cell/battery hybrid vehicles
Hierarchical control
Integrated motion and powertrain control
Nonlinear model predictive control
Successive linearizations
Issue Date2020
PublisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=9424
Citation
IEEE Transactions on Industrial Informatics, 2020, v. 16 n. 5, p. 3397-3406 How to Cite?
AbstractThis article considers intelligent fuel cell/battery hybrid vehicles (FCHVs) that can make autonomous decisions at both the vehicle and powertrain levels. Since the vehicle and powertrain level dynamics are inherently integrated, we propose an integrated motion and powertrain model predictive control approach for intelligent FCHVs by jointly optimizing the vehicle acceleration and fuel cell current. The control goals are to achieve vehicle mobility, minimal hydrogen consumption, and battery state-of-charge maintenance within system constraints. The main challenge in an integrated control is that the electric motor can operate in both propelling and generating modes coupling with vehicle and powertrain states. This hybrid operation is handled by the mixed logical dynamical modeling resulting in a mixed integer nonlinear control problem. To relieve the possible heavy computational burden, two simplification approaches are proposed: hierarchical control and successive linearizations. Two standard driving cycles and a typical vehicle cruising scenario are employed to test the effectiveness of the proposed modeling and control algorithms. Simulation results show that the hierarchical linear control is more suitable for real-time applications with comparable control performance with that of the integrated control. However, additional constraints must be carefully designed to compensate for the ignored coupling dynamics and constraints.
Persistent Identifierhttp://hdl.handle.net/10722/286495
ISSN
2019 Impact Factor: 9.112
2015 SCImago Journal Rankings: 2.973
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorZheng, H-
dc.contributor.authorWu, J-
dc.contributor.authorWu, W-
dc.contributor.authorWang, Y-
dc.date.accessioned2020-08-31T07:04:40Z-
dc.date.available2020-08-31T07:04:40Z-
dc.date.issued2020-
dc.identifier.citationIEEE Transactions on Industrial Informatics, 2020, v. 16 n. 5, p. 3397-3406-
dc.identifier.issn1551-3203-
dc.identifier.urihttp://hdl.handle.net/10722/286495-
dc.description.abstractThis article considers intelligent fuel cell/battery hybrid vehicles (FCHVs) that can make autonomous decisions at both the vehicle and powertrain levels. Since the vehicle and powertrain level dynamics are inherently integrated, we propose an integrated motion and powertrain model predictive control approach for intelligent FCHVs by jointly optimizing the vehicle acceleration and fuel cell current. The control goals are to achieve vehicle mobility, minimal hydrogen consumption, and battery state-of-charge maintenance within system constraints. The main challenge in an integrated control is that the electric motor can operate in both propelling and generating modes coupling with vehicle and powertrain states. This hybrid operation is handled by the mixed logical dynamical modeling resulting in a mixed integer nonlinear control problem. To relieve the possible heavy computational burden, two simplification approaches are proposed: hierarchical control and successive linearizations. Two standard driving cycles and a typical vehicle cruising scenario are employed to test the effectiveness of the proposed modeling and control algorithms. Simulation results show that the hierarchical linear control is more suitable for real-time applications with comparable control performance with that of the integrated control. However, additional constraints must be carefully designed to compensate for the ignored coupling dynamics and constraints.-
dc.languageeng-
dc.publisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=9424-
dc.relation.ispartofIEEE Transactions on Industrial Informatics-
dc.subjectFuel cell/battery hybrid vehicles-
dc.subjectHierarchical control-
dc.subjectIntegrated motion and powertrain control-
dc.subjectNonlinear model predictive control-
dc.subjectSuccessive linearizations-
dc.titleIntegrated Motion and Powertrain Predictive Control of Intelligent Fuel Cell/Battery Hybrid Vehicles-
dc.typeArticle-
dc.identifier.emailWang, Y: amywang@hku.hk-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/TII.2019.2956209-
dc.identifier.scopuseid_2-s2.0-85079769440-
dc.identifier.hkuros313326-
dc.identifier.volume16-
dc.identifier.issue5-
dc.identifier.spage3397-
dc.identifier.epage3406-
dc.identifier.isiWOS:000519588700049-
dc.publisher.placeUnited States-

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