A learning‐based hierarchical energy management control strategy for hybrid electric vehicles

In this work, a novel energy management control framework is developed for hybrid electric vehicles (HEVs) driving in car‐following scenarios. In order to enhance the energy efficiency while maintaining the driving safety, a hierarchical control approach consisting of an upper level speed tracking c...

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Bibliographic Details
Published in:IET control theory & applications Vol. 18; no. 18; pp. 2725 - 2741
Main Authors: Chen, Yanfang, Li, Xuefang
Format: Journal Article
Language:English
Published: Stevenage John Wiley & Sons, Inc 01.12.2024
Subjects:
Control algorithms
Control systems
Design
Electric vehicles
Energy consumption
Energy efficiency
Energy management
Hybrid electric vehicles
iterative learning model predictive control
Learning
Optimization
Powertrain
Predictive control
speed tracking
Tracking control
Vehicle safety
Velocity
ISSN:1751-8644, 1751-8652
Online Access:Get full text
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Summary:In this work, a novel energy management control framework is developed for hybrid electric vehicles (HEVs) driving in car‐following scenarios. In order to enhance the energy efficiency while maintaining the driving safety, a hierarchical control approach consisting of an upper level speed tracking control scheme and a lower level energy management control strategy is proposed. For the upper level tracking control system, an iterative learning model predictive control (ILMPC) scheme is developed to guarantee the tracking performance and the driving safety simultaneously. Additionally, a model predictive control (MPC) algorithm is adopted at the lower level to optimize the torque distribution in real‐time based on the driving cycles generated by the upper level control system. With the proposed hierarchical control framework, HEVs are able to improve the energy efficiency significantly by taking the advantages of the operational repeatability. The convergence of the proposed control strategy is analyzed rigorously, and its effectiveness is illustrated through numerical simulations. A hierarchical learning EMS is developed for hybrid electric vehicles (HEVs) in car‐following scenarios. A tube‐based iterative learning model predictive control scheme is proposed for speed tracking under uncertainties. The operation repetition is helpful to improve fuel efficiency of HEVs.
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ISSN:1751-8644
1751-8652
DOI:10.1049/cth2.12749