A Review of Problem Variants and Approaches for Electric Vehicle Charging and Location Identification

D. Prakash, G. Jeyakumar
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Abstract

The optimization of electric vehicles (EVs) utilizing meta-heuristics has arisen as the way to propel state-of-the-art advancements, making ready for boundless reception, and reforming the flow transportation framework while lessening ozone-depleting substance discharges. The two factors that keep on obstructing the improvement of EVs are reach and cost. This study digs profoundly into the five significant EV enhancement regions: plan advancement, energy the board, ideal control, upgraded charging and releasing, and steering. Methods for single-objective and multi-objective enhancement are examined and talked about. Following a broad survey of the latest works in every space, an investigation of numerical demonstrating, the development of goal capabilities, time management for charging, and limitations are introduced. What’s more, the different scientific, regular, and nature-roused advancement calculations (swarm-optimization, transformative, and recent meta-heuristics) are arranged in view of their fame. Their merits and detriments are then analyzed, similar to the different requirements for taking care of procedures. This survey of the high-level and redesigned variants of these meta-heuristics likewise gives a precise reference to EV streamlining utilizing wise calculations.
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电动汽车充电与位置识别问题变体与方法综述
利用元启发式优化电动汽车(ev)已经成为推动最先进技术进步的一种方式,为无限接收做好准备,并在减少臭氧消耗物质排放的同时改革流动运输框架。阻碍电动汽车发展的两个因素是可及性和成本。本研究深入探讨了电动汽车的五个显著增强区域:计划推进、能量板、理想控制、升级充放电和转向。探讨了单目标增强和多目标增强的方法。在广泛调查了各个领域的最新研究成果之后,介绍了数值演示、目标能力的发展、充电时间管理和局限性的研究。更重要的是,不同的科学、常规和自然激发的进步计算(群体优化、变革和最近的元启发式)是根据它们的名声来安排的。然后分析它们的优缺点,类似于照顾程序的不同要求。对这些元启发式的高级和重新设计的变体的调查同样给出了利用明智计算的EV流线型的精确参考。
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