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

Format:

Book

Conference/Event

Author/Creator:

Mishra, Mishra, author.

Contributor:

Kodakkadan, Abid Rahman

Koduri, Rajesh

Manalikandy, Mithun

Nandyala, Sivaprasad

Conference Name:

WCX SAE World Congress Experience (2019-04-09 : Detroit, Michigan, United States)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2019

Summary:

AbstractDue 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 (id est 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 et cetera 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

Notes:

Vendor supplied data

Publisher Number:

2019-01-0790

Access Restriction:

Restricted for use by site license