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Parametric performance analysis of battery operated electric vehicle

机译:电池电动车的参数性能分析

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The issues pertaining to global warming and greenhouse effects have become more prominent. One of the measures being taken by the world countries to address these key issues is adoption of Electrical Vehicle (EV) technology that has revolutionized the mobility industry by gradually grabbing the market share of fossil fuel-based automobiles. A battery-operated electric vehicle (BEV) uses chemical energy stored in a rechargeable battery pack for operation, and emits zero pollutants. Apart from plug-in charging, the BEVs charge their batteries through a regenerative braking system by recovering kinetic energy lost during braking. The EV manufacturers put forth relentless effort to enhance the performance of EVs through new technologies. The efficiency of regenerative braking, and battery capacity largely affect certain performance parameter, i.e., factors of EVs. An analysis of key performance parameters and their relations are of great importance as far as the performance enhancement is concerned. Industries do employ simulation software for carrying out these analyses, but without considering interrelation between performance-influencing factors. An analysis of correlating factors that influence the EV performance can be of good tool to help group the factors that can affect one another. In this paper, an attempt is made to conduct a correlation study between performance-influencing factors of various commercially available electric vehicles. The factors considered for this study are; battery capacity, power, driving range and pick-up. The relations between these factors are established through conducting Pearson correlation. This study will help guide the EV manufacturers to understand the parametric relations to optimize the performance of their EVs. In addition, the findings obtained from the post-sale analysis of the performance factors can be useful in validating the simulation results.
机译:与全球变暖和温室效果有关的问题变得更加突出。世界各国采取了其中一种措施,以解决这些关键问题是通过逐步抓住化石燃料汽车的市场份额来彻底改变流动产业的电气汽车(EV)技术。电池供电的电动车(BEV)使用存储在可充电电池组中的化学能量进行操作,并发出零污染物。除了插入式充电外,BEV通过恢复制动期间损失的动能损失,通过再生制动系统充电。 EV制造商提出了无情的努力,通过新技术提高EVS的性能。再生制动的效率和电池容量在很大程度上影响了某些性能参数,即EVS的因素。就绩效增强而言,关键性能参数及其关系的分析非常重要。行业确实采用了仿真软件来执行这些分析,但在不考虑性能影响因素之间的相互关系。影响EV性能的关联因子的分析可以是良好的工具,以帮助群体可能影响彼此的因素。在本文中,尝试进行各种市售电动车辆的性能影响因素之间的相关研究。考虑本研究的因素是;电池容量,电源,驾驶范围和拾取。通过进行Pearson相关性建立这些因素之间的关系。本研究将帮助指导EV制造商了解参数关系以优化其EV的性能。此外,从销售后的性能因子的销售分析中获得的结果可用于验证仿真结果。

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