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• W2944297230 endingPage "3137" @default.
• W2944297230 startingPage "3126" @default.
• W2944297230 abstract "The electric turbocharger (ET) is a promising solution for engine downsizing. It provides great potential for vehicle fuel efficiency improvement. The ET makes engines run as hybrid systems so critical challenges are raised in energy management and control. This paper proposes a real-time energy management strategy based on updating and tracking of the optimal exhaust pressure setpoint. Starting from the engine characterization, the impacts of the ET on engine response and exhaust emissions are analyzed. A multivariable explicit model predictive controller is designed to regulate the key variables in the engine air system, whereas the optimal setpoints of those variables are generated by a high-level controller. The two-level controller works in a highly efficient way to fulfill the optimal energy management. This strategy has been validated in physical simulations and experimental testing. Excellent tracking performance and sustainable energy management demonstrate the effectiveness of the proposed method." @default.
• W2944297230 created "2019-05-16" @default.
• W2944297230 creator A5027569449 @default.
• W2944297230 creator A5068533876 @default.
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• W2944297230 date "2020-04-01" @default.
• W2944297230 modified "2023-10-05" @default.
• W2944297230 title "Real-Time Energy Management of the Electric Turbocharger Based on Explicit Model Predictive Control" @default.
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• W2944297230 doi "https://doi.org/10.1109/tie.2019.2910033" @default.
• W2944297230 hasPublicationYear "2020" @default.
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