首页> 外文会议>Computational Intelligence and Design, 2009. ISCID '09 >Intelligent Energy Management Based on the Driving Cycle Sensitivity Identification Using SVM
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Intelligent Energy Management Based on the Driving Cycle Sensitivity Identification Using SVM

机译:基于支持向量机的驾驶循环灵敏度识别的智能能源管理

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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 driverȁ9;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 machines (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 itȁ9;s great in improving fuel economy and reducing emissions.
机译:混合动力电动汽车(HEV)能够显着减少燃油消耗和排放。能源管理是实施混合动力电动汽车的基本要素之一。发动机和电动机应满足驾驶员在不同驾驶环境中的需求。本文定义了一个驾驶循环灵敏度参数,该参数用于创建不同的驾驶循环以替代一种公路驾驶条件。控制策略的参数由遗传机构在这些不同的周期上进行优化。在本文中,支持向量机(SVM)用于识别驾驶循环灵敏度参数。并建立了智能能源管理系统,可以将控制策略中的参数更改为遗传优化结果。进行了仿真工作,验证了所提出的智能管理,其结果表明show9对改善燃油经济性和减少排放具有很大的作用。

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