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'Measurement and Analysis of Indian Road Drive Cycles for Efficient and Economic Design of HEV Component'

机译:“HEV组件高效经济设计的印度道路驱动循环的测量与分析”

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摘要

Drive cycle pattern is different for different countries which depends on their traffic density, road condition and driver discipline. Drive cycle influences HEV's components design, sizing and their ratings. Standard drive cycle data doesn't reveal much information to determine efficient and economic design of HEV's components. In this research paper measurement and analysis of real time Indian road drive cycles (IRDC) are carried out for urban roads, state highway, national highway and express Highway where vehicles have their most run. Real time drive cycle data will expose impact of driver's skills, traffic, road conditions and short acceleration/deceleration period, which can be represented on drive cycle chart. Analysis of IRDC in terms of rate of acceleration and deceleration, top speed, average speed with road length and analysed mathematically to find energy and power required for acceleration, normal operation and energy harvested during deceleration. Based on information from IRDC HEV's components initial size are estimated. Initial estimated size is optimized to make HEV's components design more efficient and economic. Teaching and learning based optimization algorithm (TLBO) and Multi objective genetic algorithm (MOGA) are used to optimize HEV's components. Constraint of optimization algorithm are like engine and motor rating should be selected such that it has effective top speed with enough acceleration capability and can run enough distance to reach destination according to Indian urban, state, national and express highway pattern where cities are very closed compared with other countries and its regeneration component design should able to harvest maximum deceleration energy. For economic operation of HEV's, running cost in terms of Rs./Km. should be minimum.
机译:不同国家的驱动周期模式不同,这取决于其交通密度,道路状况和驾驶员纪律。驱动周期影响HEV的组件设计,尺寸和评级。标准驱动循环数据没有透露许多信息,以确定HEV组件的高效和经济设计。在本研究纸张上,对城市道路,州公路,国家公路和快车工高速公路进行了实时印度道路驱动周期(IRDC)的测量和分析。实时驱动周期数据将暴露驾驶员技能,交通,道路条件和短加速度/减速期的影响,这可以在驱动周期图上表示。 IRDC在加速和减速率,顶级速度,道路长度的平均速度和数学分析,以找到加速,正常运行和减速期间的能量所需的能量和功率。根据IRDC HEV的信息,估计初始大小的初始大小。初始估计大小被优化,使HEV的组件设计更有效和经济。基于教学和基于学习的优化算法(TLBO)和多目标遗传算法(MOGA)用于优化HEV的组件。优化算法的约束就像发动机和电机等级,使其具有足够的加速度的最高速度,并且根据印度城市,国家,国家和快速的公路模式,可以运行足够的距离达到目的地,其中城市比较非常封闭与其他国家及其再生组件设计应能够收取最大减速能量。对于HEV的经济运行,rs./km的运行成本。应该是最小的。

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