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Title: Two-Layer Predictive Controller for V2G and G2V Services Using on Wireless Power Transfer Technology

Abstract

This paper presents a comprehensive solution that allows electric vehicles (EV) to autonomously charge and discharge their batteries wirelessly during long term parking and/or the transient stops. A two-layer power-flow controller for bidirectional wireless power transfer system (BWPTS) in EVs applications is proposed. The proposed controller can manage the bidirectional power-flow between EV and surrounding infrastructures such as power grid, home microgrid, building micro-grid, road or another vehicle. It consists of two levels of control; the first is responsible for communicating with the surrounding infrastructures and gathering information from driver, charging station, power grid and battery management system and then, based on these information, it estimates the EV's psychological price as a function of its battery's state-of-charge (SOC) and compares it with the energy price to decide whether to charge, discharge or abstain, and how much the charging or discharging rate. The second layer receives the reference signal from the first one and generates the control parameters for two synchronized resonant converters (one is on the vehicle side and the other is on the grid side) to provide the requited power-flow. The proposed controller is adaptively estimating the system parameters to consider the misalignment conditions effects on the system performance.more » The parameter estimation is achieved using only one voltage sensor. The second layer control is designed based on a new analytical modeling for the power flow in the system. For verification purposes, a prototype for BWPTS was built and driven by the proposed controller, which was implemented using a field-programmable gate array (FPGA) integrated circuit. The proposed controller provides very fast and stable response during both the transient and steady state operation in comparison with the conventional PI controller.« less

Authors:
ORCiD logo [1];  [2]
  1. National Renewable Energy Laboratory (NREL), Golden, CO (United States)
  2. Florida International University
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
OSTI Identifier:
1493866
Report Number(s):
NREL/CP-5400-73232
DOE Contract Number:  
AC36-08GO28308
Resource Type:
Conference
Resource Relation:
Conference: Presented at the 2018 IEEE Industry Applications Society Annual Meeting (IAS), 23-27 September 2018, Portland, Oregon
Country of Publication:
United States
Language:
English
Subject:
33 ADVANCED PROPULSION SYSTEMS; electric vehicle; vehicle-to-grid; wireless power transfer; predictive control; autonomous control

Citation Formats

Mohamed, Ahmed A, and Mohammed, Osama. Two-Layer Predictive Controller for V2G and G2V Services Using on Wireless Power Transfer Technology. United States: N. p., 2018. Web. doi:10.1109/IAS.2018.8544722.
Mohamed, Ahmed A, & Mohammed, Osama. Two-Layer Predictive Controller for V2G and G2V Services Using on Wireless Power Transfer Technology. United States. doi:10.1109/IAS.2018.8544722.
Mohamed, Ahmed A, and Mohammed, Osama. Thu . "Two-Layer Predictive Controller for V2G and G2V Services Using on Wireless Power Transfer Technology". United States. doi:10.1109/IAS.2018.8544722.
@article{osti_1493866,
title = {Two-Layer Predictive Controller for V2G and G2V Services Using on Wireless Power Transfer Technology},
author = {Mohamed, Ahmed A and Mohammed, Osama},
abstractNote = {This paper presents a comprehensive solution that allows electric vehicles (EV) to autonomously charge and discharge their batteries wirelessly during long term parking and/or the transient stops. A two-layer power-flow controller for bidirectional wireless power transfer system (BWPTS) in EVs applications is proposed. The proposed controller can manage the bidirectional power-flow between EV and surrounding infrastructures such as power grid, home microgrid, building micro-grid, road or another vehicle. It consists of two levels of control; the first is responsible for communicating with the surrounding infrastructures and gathering information from driver, charging station, power grid and battery management system and then, based on these information, it estimates the EV's psychological price as a function of its battery's state-of-charge (SOC) and compares it with the energy price to decide whether to charge, discharge or abstain, and how much the charging or discharging rate. The second layer receives the reference signal from the first one and generates the control parameters for two synchronized resonant converters (one is on the vehicle side and the other is on the grid side) to provide the requited power-flow. The proposed controller is adaptively estimating the system parameters to consider the misalignment conditions effects on the system performance. The parameter estimation is achieved using only one voltage sensor. The second layer control is designed based on a new analytical modeling for the power flow in the system. For verification purposes, a prototype for BWPTS was built and driven by the proposed controller, which was implemented using a field-programmable gate array (FPGA) integrated circuit. The proposed controller provides very fast and stable response during both the transient and steady state operation in comparison with the conventional PI controller.},
doi = {10.1109/IAS.2018.8544722},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2018},
month = {11}
}

Conference:
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