Parallel Hybrid Electric Vehicle Modelling and Model Predictive Control

This paper presents the modelling and calculations for a hybrid electric vehicle (HEV) in parallel configuration, including a main electrical driving motor (EM), an internal combustion engine (ICE), and a starter/generator motor. The modelling equations of the HEV include vehicle acceleration and je...

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Autores principales:	Trieu Minh Vu, Reza Moezzi, Jindrich Cyrus, Jaroslav Hlava, Michal Petru
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	model predictive control parallel hybrid electric vehicle hard constraints softened constraints fast clutch engagement drivability and comfortability Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/3bab6e75da42429dbdcfffc4bb6826c0
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id	oai:doaj.org-article:3bab6e75da42429dbdcfffc4bb6826c0
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spelling	oai:doaj.org-article:3bab6e75da42429dbdcfffc4bb6826c02021-11-25T16:34:54ZParallel Hybrid Electric Vehicle Modelling and Model Predictive Control10.3390/app1122106682076-3417https://doaj.org/article/3bab6e75da42429dbdcfffc4bb6826c02021-11-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/22/10668https://doaj.org/toc/2076-3417This paper presents the modelling and calculations for a hybrid electric vehicle (HEV) in parallel configuration, including a main electrical driving motor (EM), an internal combustion engine (ICE), and a starter/generator motor. The modelling equations of the HEV include vehicle acceleration and jerk, so that simulations can investigate the vehicle drivability and comfortability with different control parameters. A model predictive control (MPC) scheme with softened constraints for this HEV is developed. The new MPC with softened constraints shows its superiority over the MPC with hard constraints as it provides a faster setpoint tracking and smoother clutch engagement. The conversion of some hard constraints into softened constraints can improve the MPC stability and robustness. The MPC with softened constraints can maintain the system stability, while the MPC with hard constraints becomes unstable if some input constraints lead to the violation of output constraints.Trieu Minh VuReza MoezziJindrich CyrusJaroslav HlavaMichal PetruMDPI AGarticlemodel predictive controlparallel hybrid electric vehiclehard constraintssoftened constraintsfast clutch engagementdrivability and comfortabilityTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 10668, p 10668 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	model predictive control parallel hybrid electric vehicle hard constraints softened constraints fast clutch engagement drivability and comfortability Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	model predictive control parallel hybrid electric vehicle hard constraints softened constraints fast clutch engagement drivability and comfortability Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Trieu Minh Vu Reza Moezzi Jindrich Cyrus Jaroslav Hlava Michal Petru Parallel Hybrid Electric Vehicle Modelling and Model Predictive Control
description	This paper presents the modelling and calculations for a hybrid electric vehicle (HEV) in parallel configuration, including a main electrical driving motor (EM), an internal combustion engine (ICE), and a starter/generator motor. The modelling equations of the HEV include vehicle acceleration and jerk, so that simulations can investigate the vehicle drivability and comfortability with different control parameters. A model predictive control (MPC) scheme with softened constraints for this HEV is developed. The new MPC with softened constraints shows its superiority over the MPC with hard constraints as it provides a faster setpoint tracking and smoother clutch engagement. The conversion of some hard constraints into softened constraints can improve the MPC stability and robustness. The MPC with softened constraints can maintain the system stability, while the MPC with hard constraints becomes unstable if some input constraints lead to the violation of output constraints.
format	article
author	Trieu Minh Vu Reza Moezzi Jindrich Cyrus Jaroslav Hlava Michal Petru
author_facet	Trieu Minh Vu Reza Moezzi Jindrich Cyrus Jaroslav Hlava Michal Petru
author_sort	Trieu Minh Vu
title	Parallel Hybrid Electric Vehicle Modelling and Model Predictive Control
title_short	Parallel Hybrid Electric Vehicle Modelling and Model Predictive Control
title_full	Parallel Hybrid Electric Vehicle Modelling and Model Predictive Control
title_fullStr	Parallel Hybrid Electric Vehicle Modelling and Model Predictive Control
title_full_unstemmed	Parallel Hybrid Electric Vehicle Modelling and Model Predictive Control
title_sort	parallel hybrid electric vehicle modelling and model predictive control
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/3bab6e75da42429dbdcfffc4bb6826c0
work_keys_str_mv	AT trieuminhvu parallelhybridelectricvehiclemodellingandmodelpredictivecontrol AT rezamoezzi parallelhybridelectricvehiclemodellingandmodelpredictivecontrol AT jindrichcyrus parallelhybridelectricvehiclemodellingandmodelpredictivecontrol AT jaroslavhlava parallelhybridelectricvehiclemodellingandmodelpredictivecontrol AT michalpetru parallelhybridelectricvehiclemodellingandmodelpredictivecontrol
_version_	1718413070987952128

Parallel Hybrid Electric Vehicle Modelling and Model Predictive Control

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