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针对插入式电动车(Plug-in Electric Vehicles,PEV)到停车场电池能量的调度问题,提出了一种云计算环境下的智能调度控制算法。首先,将智能停车场代理商作为服务提供商,并向用户开放许多重要的PEV和停车场数据;然后,考虑用户的请求,根据PEV的位置和蓄电池电荷状态(SOC)找到最优(距离近、价格优)的停车场;最后,若司机不能接受停车场价格,则利用模糊逻辑预测精确预测PEV蓄电池的SOC,从而找到更合适的停车场。在包含10 000辆PEV、10 000个停车场和10个停车场代理商的数据集进行了仿真实验,仿真结果表明,该算法明显减少了PEV与停车场的交互次数,能够提前根据PEV自身的局限性计算和预测路载需求。相比传统的调度服务算法,该算法可更加有效地管理和控制停车场电池能量。
In order to solve the scheduling problem of battery energy in parking lots from Plug-in Electric Vehicles (PEV), an intelligent scheduling control algorithm in cloud computing environment is proposed. First, smart parking agents act as service providers and open up many important PEV and parking lot data to users. Then, consider the user’s request and find the optimal (close to the nearest neighbor) based on the PEV’s location and battery state of charge (SOC) , The price is excellent) parking lot; Finally, if the driver can not accept the parking lot price, then use fuzzy logic to predict accurately forecast PEV battery SOC, in order to find a more suitable parking lot. The simulation experiment is carried out in a dataset containing 10 000 PEVs, 10 000 parking lots and 10 parking agents. The simulation results show that the algorithm significantly reduces the number of interactions between PEVs and parking lots, Limitations Calculate and predict road load requirements. Compared with the traditional scheduling service algorithm, the algorithm can manage and control the parking battery energy more effectively.