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Intelligent Energy Management Based on the Driving Cycle Sensitivity Identification Using SVM

机译:基于SVM的驾驶周期灵敏度识别智能能量管理

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Hybrid Electric Vehicles (HEV) offer the ability to significantly reduce fuel consumptions and emission. Management of energy is one of essential elements in the implementation of hybrid electric vehicles. Engine and motor should satisfy the driver's demand in different driving environment. This paper defines a driving cycle sensitivity parameter, which is used to create different driving cycles to substitute a kind of the on-road driving conditions. The parameters of control strategy are optimized by genetic agency on these different cycles. In this paper support vector machine (SVM) is used to identify the driving cycle sensitivity parameter. And an intelligent energy management is crated, which could change the parameters in control strategy to the genetic optimized results. Simulation work is carried out for the validation of proposed intelligent management, and the results show it's great in improving fuel economy and reducing emissions.
机译:混合动力电动车(HEV)提供了显着降低燃料消耗和排放的能力。能源管理是混合动力电动汽车实施中的基本要素之一。发动机和电机应满足驾驶员在不同的驾驶环境中的需求。本文定义了驱动周期灵敏度参数,用于创造不同的驱动周期,以替换一种通道的驾驶条件。控制策略的参数由遗传学代理对这些不同的循环进行优化。在本文中,支持向量机(SVM)用于识别驱动周期灵敏度参数。估计智能能源管理,可以将控制策略中的参数改变为遗传优化结果。仿真工作是为了验证拟议的智能管理,结果表明它在提高燃油经济性和减少排放方面是很好的。

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