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Improvement of Energy Management Control Strategy of Fuel Cell Hybrid Electric Vehicles Based on Artificial Intelligence Techniques

机译:基于人工智能技术的燃料电池混合电动汽车能量管理控制策略的提高

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摘要

In this paper, we present a new approach for the optimization of energy management of the hybridization of three sources battery/Fuel Cell/Photovoltaic (B/FC/PV) vehicles configurations in order to reduce hydrogen consumption. An advanced control optimization strategy is proposed using an artificial intelligence (AI) algorithm carried out in a Matlab/Simulink environment. The power control of the fuel cell is obtained by regulating the powers of the two other sources as well as the state of charge (SOC) of the battery with hybridization via a parameter P_H (parameter of hybridization). The regulation of the power of both battery and the solar PV system is achieved to the regulation of the DC bus voltage according to the reference current of the fuel cell during the optimization of the output value via a parameter P_O (parameter of optimization). The activation outputs of the three sources are generated by the AI algorithm developed while including the dynamics and the profile/condition of the road as well as the demand of the vehicle. An optimization is proposed via the introduction of two parameters P_H and P_O, during phases of high energy demands. The results show that the proposed strategy will provide a new approach for the advanced energy management system for hybrid vehicles.
机译:在本文中,我们提出了一种优化三源电池/燃料电池/光伏(B/FC/PV)车辆配置的能量管理的新方法,以减少氢消耗。在Matlab/Simulink环境下,利用人工智能算法,提出了一种先进的控制优化策略。燃料电池的功率控制通过参数P_H(杂化参数)调节其他两个电源的功率以及电池的荷电状态(SOC)来实现。在通过参数P_O(优化参数)优化输出值的过程中,根据燃料电池的参考电流调节直流母线电压,从而实现对电池和太阳能光伏系统功率的调节。三个源的激活输出由开发的AI算法生成,同时包括道路的动态和轮廓/状况以及车辆的需求。在高能量需求阶段,通过引入两个参数P_H和P_O,提出了一种优化方法。结果表明,该策略为混合动力汽车的先进能量管理系统提供了一条新的途径。

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