Recent years have witnessed a growing trend in the utilization of Electric Vehicles (EVs), however with the increased usage of EVs, appropriate strategies for supporting the charging demands has not garnered much attention. The absence of adaptable plans in charging may result in minimized participation; further, the charging demands have to be addressed with utmost care for ensuring reliability and efficiency of the grid. In this paper, an efficient EV charging technique based on blockchain based user transaction and smart contract is devised. Here, charge scheduling is performed by acquiring the information the charging demand of the EV over Internet of things. In case the EV does not have sufficient power to reach the target, nearest Charging Station (CS) with the minimal electricity price is identified. The CS is selected considering various factors, such average waiting time, distance, power, traffic, and so on. Here, power prediction is performed using the Deep Maxout Network (DMN), whose weights are adapted based on the devised Exponentially Snake Optimization (ESO) algorithm. Furthermore, the efficacy of the devised ESO-DMN is examined considering metrics, like average waiting time, distance, and number of EVs charged and power and is found to have attained values of 1.937 s, 13.952 km, 55 and 2.876 J.

近年来，电动汽车 （EV） 的使用呈增长趋势，但随着电动汽车使用量的增加，支持充电需求的适当策略并未引起太多关注。缺乏适应性的收费计划可能会导致参与度最低;此外，必须非常谨慎地解决充电需求，以确保电网的可靠性和效率。在本文中，设计了一种基于区块链的用户交易和智能合约的高效电动汽车充电技术。在这里，通过物联网获取 EV 充电需求的信息来执行充电调度。如果 EV 没有足够的动力到达目标，则会确定最近的电价最低的充电站 （CS）。选择 CS 时考虑了各种因素，例如平均等待时间、距离、功率、交通等。在这里，使用深度 Maxout 网络 （DMN） 执行功率预测，其权重根据设计的指数蛇优化 （ESO） 算法进行调整。此外，根据平均等待时间、距离、充电的电动汽车数量和功率等指标检查了设计的 ESO-DMN 的有效性，发现其达到了 1.937 秒、13.952 公里、55 和 2.876 焦耳的值。