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Wireless Charging for EV/HEV with Prescriptive Analytics, Machine Learning, Cybersecurity and Blockchain Technology: Ongoing and Future Trends

机译:EV / HEV的无线充电,具有规定的分析,机器学习,网络安全和区块技术:持续和未来的趋势

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Due to the rapid development in the technological aspect of the autonomous vehicle (AV), there is a compelling need for research in the field vehicle efficiency and emission reduction without affecting the performance, safety and reliability of the vehicle. Electric vehicle (EV) with rechargeable battery has been proved to be a practical solution for the above problem. In order to utilize the maximum capacity of the battery, a proper power management and control mechanism need to be developed such that it does not affect the performance, reliability and safety of vehicle. Different optimization techniques along with deterministic dynamic programming (DDP) approach are used for the power distribution and management control. The battery-operated electric vehicle can be recharged either by plug-in a wired connection or by the inductive mean (i.e. wirelessly) with the help of the electromagnetic field energy. These inductive and wireless charging techniques utilize the principle of electromagnetic induction for transferring the power. The design of the wireless charging system, can be divided into three primary stage such as coil design, compensation topology and power converter with the control mechanism for transferring power efficiently. Different coil structures are proposed for maximizing the magnetic flux therefore helping in transferring the energy effectively. Compensation topology is used for the tuning of the high-frequency AC ranging from a few kHz to MHz between the primary coil and secondary coil. Different advance machine learning techniques are evolved for optimization of the parameters such as state of charge (SoC) and state of health (SoH), temperature, current etc. Based on the data obtained by pre-processing through data analysis techniques and then applying ML technique and prescriptive analytics are applied to estimate the value. In order to provide the secure charging environment, blockchain technology framework is proposed along with appropriate cyber security algorithm where ever required.
机译:由于自主车辆技术方面的快速发展(AV),对现场车辆效率和减排的研究具有令人信服的需要,而不会影响车辆的性能,安全性和可靠性。具有可充电电池的电动车(EV)已被证明是上述问题的实用解决方案。为了利用电池的最大容量,需要开发适当的电源管理和控制机制,使得它不会影响车辆的性能,可靠性和安全性。不同的优化技术以及确定性动态编程(DDP)方法用于配电和管理控制。在电磁场能量的帮助下,电池操作的电动车辆可以通过插入有线连接或通过电感平均值(即无线)再充电。这些电感和无线充电技术利用电磁诱导原理转移电力。无线充电系统的设计,可分为三个初级级,如线圈设计,补偿拓扑和功率转换器,具有有效地传送功率的控制机构。提出了不同的线圈结构,用于最大化磁通量,因此有助于有效地转移能量。补偿拓扑用于调谐从初级线圈和次级线圈之间的几kHz到MHz的高频交流。用于优化参数(SOC)和健康状态(SOH),温度,电流等的参数的优化,基于通过通过数据分析技术获得的数据,然后施加ML而获得不同的推进机器学习技术技术和规定的分析应用于估计值。为了提供安全的充电环境,建议块技术框架以及需要的适当网络安全算法。

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