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• W2567832009 abstract "This paper proposes a power management strategy for an hybrid electrical vehicle based on the Non-linear Model Predictive Control (NLMPC) that uses an equivalent consumption cost to control the state of charge of the battery. The predictive control is formulated as a repeated solution of a finite horizon minimum consumption problem which respects input and state constraints and vehicle dynamics also including the efficiency of the gear box. The reference speed and acceleration in the prediction step of NLMPC horizon is obtained by integrating forward the dynamic equations of the vehicle model with a fast semi-analytical method that does not use information about the past behaviour of the vehicle. The corresponding demanded torque is then optimally split between the two energy sources as solution of NLMPC and used in each instant for the definition of the power management strategy. The proposed NLMPC is tested on a simplified driver simulator of the hybrid vehicle and the on-line results are compared both with conventional Adaptive-Equivalent Consumption Minimisation Strategy (AECMS) strategies and with the global optimal strategy off-line computed that serves as benchmark." @default.
• W2567832009 created "2017-01-13" @default.
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• W2567832009 date "2016-10-01" @default.
• W2567832009 modified "2023-09-23" @default.
• W2567832009 title "On-Line power management optimization of a hybrid electric vehicle with Non linear MPC and battery re-charge equivalent cost" @default.
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• W2567832009 doi "https://doi.org/10.1109/iecon.2016.7793803" @default.
• W2567832009 hasPublicationYear "2016" @default.
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