Pareto Front Analysis Of The Objective Function In Model Predictive Control Based Power Management System Of A Plug-In Hybrid Electric Vehicle

2018 IEEE TRANSPORTATION AND ELECTRIFICATION CONFERENCE AND EXPO (ITEC)(2018)

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摘要
Model predictive control strategy (MPC) has been identified as an efficient path for reducing fuel consumption, greenhouse gasses (GHG) emission, or degradation of power-train components for electrified vehicles. MPC is an optimization-based control strategy that aims at finding the optimal control actions of a system by predicting its future behaviors. As the main contribution, this paper provides a Pareto-front analysis of the objective function taking into account the equivalent fuel consumption and the battery aging when the PHEV is in the charge sustaining (CS) mode. The results show that the MPC controller can decrease the battery capacity fade by 45% for only increasing the equivalent vehicle fuel consumption of 0.1% compared to an engine on-off thermostat control strategy.
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关键词
model predictive control,greenhouse gasses emission,power-train components,electrified vehicles,optimization-based control strategy,optimal control actions,Pareto-front analysis,objective function,MPC controller,power management system,vehicle fuel consumption,plug-in hybrid electric vehicle,battery aging,charge sustaining mode
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