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Optimization of Hybrid Electric Cars by Neuro-Fuzzy Networks

机译:基于神经模糊网络的混合动力汽车优化

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摘要

In this paper, the problem of the optimization of energetic flows in hybrid electric vehicles is faced. We consider a hybrid electric vehicle equipped with batteries, a thermal engine (or fuel cells), ultracapacitors and an electric engine. The energetic flows are optimized by using a control strategy based on the prediction of short-term and medium-term vehicle states (energy consumption, vehicle load, current route, traffic flow, etc.). The prediction will be performed by a neuro-fuzzy control unit, where the predictive model exploits the robustness of fuzzy logic in managing the said uncertainties and the neural approach as a data driven tool for non-linear control modeling.
机译:本文提出了混合动力汽车能量流优化的问题。我们考虑一种混合动力电动汽车,其配备有电池,热引擎(或燃料电池),超级电容器和电动引擎。通过使用基于短期和中期车辆状态(能耗,车辆负载,当前路线,交通流量等)的预测的控制策略来优化能量流。该预测将由神经模糊控制单元执行,其中该预测模型利用模糊逻辑在管理所述不确定性方面的鲁棒性以及将神经方法用作非线性控制建模的数据驱动工具。

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