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An Energy Management System Using Trip Information and Fuzzy Logic for a Plug-In Hybrid Electric Vehicle

机译:一种基于行程信息和模糊逻辑的插电式混合动力汽车能源管理系统

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The growing interest in reducing fuel consumption and gas emissions provides an incentive for the automotive industry to innovate in the field of hybrid and plug-in hybrid electric vehicles. The two embedded power sources in these vehicles require an intelligent controller in order to make the best decision on the power distribution. Actually these controllers, often called energy management systems (EMS), are very important and greatly influence the achievable fuel economy. Many authors have studied the possibility of fuzzy based systems as they have proved to be robust, reliable and simple. However, they demonstrate a lack of optimality because their design is focused on the vehicle characteristics rather than the driving conditions. This paper proposes an approach that uses a fuzzy system fed with driving condition information in order to increase the controller effectiveness in every situation. The efficiency of the proposed controller is demonstrated through simulations.
机译:对减少燃料消耗和气体排放的兴趣日益浓厚,这为汽车工业在混合动力和插电式混合动力电动汽车领域的创新提供了动力。这些车辆中的两个嵌入式电源需要一个智能控制器,以便对功率分配做出最佳决策。实际上,通常称为能量管理系统(EMS)的这些控制器非常重要,并且极大地影响了可实现的燃油经济性。许多作者已经研究了基于模糊的系统的可行性,因为它们已被证明是健壮,可靠和简单的。但是,由于其设计重点在于车辆的特性而不是驾驶条件,因此它们表现出缺乏最佳性。本文提出了一种方法,该方法使用带有驾驶条件信息的模糊系统,以提高每种情况下的控制器效率。通过仿真证明了所提出控制器的效率。

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