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Control Strategy for Parallel Hybrid Electric Vehicles

机译:并联混合动力电动汽车控制策略

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In the recent years, emission norms are becoming more stringent due to increased environmental effects of the fossil fuels used in vehicles. The need for obtaining less polluting and more fuel efficient vehicles has paved the way for Hybrid Electric Vehicles (HEVs). The performance of an HEV relies on the effective usage of the two power sources (ICE and electric motor). The aim is to develop a control strategy to optimize the torque split between the power sources. The road grade has a considerable effect on the overall performance of the vehicle. The optimization of torque splitting is done by acquiring the road grade information with the help of Geographic Information System (GIS) maps. The approach makes use of the Adaptive fuzzy logic in which the output torque of the IC Engine is computed based on the battery State Of Charge (SOC) constraints, driver demand and road grade. In this paper, the design, implementation and testing of the adaptive fuzzy logic based strategy using real world elevation data are presented.
机译:近年来,由于车辆中使用的化石燃料的环境影响增加,排放规范正变得更加严格。获得较少污染和更多燃料效率车辆的需求已经为混合动力电动车(HEV)铺平了道路。 HEV的性能依赖于两个电源(冰和电动机)的有效使用情况。目的是制定控制策略,以优化电源之间的扭矩。道路等级对车辆的整体性能有相当大的影响。通过在地理信息系统(GIS)地图的帮助下通过获取道路等级信息来完成扭矩分离的优化。该方法利用自适应模糊逻辑,其中基于电池充电状态(SOC)约束,驾驶员需求和道路等级来计​​算IC发动机的输出扭矩。本文介绍了使用真实世界高程数据的自适应模糊逻辑策略的设计,实施和测试。

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