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Model Predictive Control Based Energy Management Strategy for a Plug-In Hybrid Electric Vehicle

机译:基于模型预测控制基于插件混合动力电动车的能量管理策略

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In this paper, the model predictive control (MPC) method is researched for energy management problem of plug-In hybrid electric vehicle (PHEV). Multi-step Markov prediction method is selected for the prediction. Dynamic programming (DP) is chosen to solve the optimization problem within the prediction horizon. Through the comparison of MPC result with the results of dynamic programming strategy and a rule-based strategy, it is certified that the control effect of MPC strategy is much better than the ruled-based strategy and close to the global optimal control under DP strategy.
机译:本文研究了模型预测控制(MPC)方法对插入式混合动力电动车辆(PHEV)的能量管理问题。选择多步马尔可夫预测方法进行预测。选择动态编程(DP)来解决预测地平线内的优化问题。通过对MPC的比较结果与动态规划策略的结果和基于规则的策略,证明了MPC策略的控制效果远远优于基于裁决的策略,并在DP策略下接近全球最优控制。

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