Two-Layer Predictive Controller for V2G and G2V Services Using on Wireless Power Transfer Technology
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.
Citation Formats
TY - DATA
AB - 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.
AU - Mohamed, Ahmed
A2 - Mohammed, Osama
DB - C-MIX - Community Microgrid Information Exchange
DP - Open EI | National Laboratory of the Rockies
DO - 10.1109/IAS.2018.8544722
KW - Power electronics and inverters
KW - Power electronics
KW - Inverters
KW - Electric vehicles
KW - Electric vehicle charging
KW - Battery energy storage
KW - Solar
KW - Photovoltaics
KW - PV
KW - Power plant controls
KW - SCADA
KW - Transportation electrification
KW - Demand flexibility
KW - Load management
KW - Maintenance and operations
KW - Operations
KW - Maintenance
KW - Commissioning
LA - English
DA - 2018/01/01
PY - 2018
PB - Florida International University
T1 - Two-Layer Predictive Controller for V2G and G2V Services Using on Wireless Power Transfer Technology
UR - https://doi.org/10.1109/IAS.2018.8544722
ER -
Mohamed, Ahmed, and Osama Mohammed. Two-Layer Predictive Controller for V2G and G2V Services Using on Wireless Power Transfer Technology. Florida International University, 1 January, 2018, C-MIX - Community Microgrid Information Exchange. https://doi.org/10.1109/IAS.2018.8544722.
Mohamed, A., & Mohammed, O. (2018). Two-Layer Predictive Controller for V2G and G2V Services Using on Wireless Power Transfer Technology. [Data set]. C-MIX - Community Microgrid Information Exchange. Florida International University. https://doi.org/10.1109/IAS.2018.8544722
Mohamed, Ahmed and Osama Mohammed. Two-Layer Predictive Controller for V2G and G2V Services Using on Wireless Power Transfer Technology. Florida International University, January, 1, 2018. Distributed by C-MIX - Community Microgrid Information Exchange. https://doi.org/10.1109/IAS.2018.8544722
@misc{CMIX_Dataset_2,
title = {Two-Layer Predictive Controller for V2G and G2V Services Using on Wireless Power Transfer Technology},
author = {Mohamed, Ahmed 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.},
url = {https://cmix.openei.org/submissions/2},
year = {2018},
howpublished = {C-MIX - Community Microgrid Information Exchange, Florida International University, https://doi.org/10.1109/IAS.2018.8544722},
note = {Accessed: 2026-10-11},
doi = {10.1109/IAS.2018.8544722}
}
https://dx.doi.org/10.1109/IAS.2018.8544722
Details
Data from Jan 1, 2018
Last updated Mar 30, 2026
Submitted Jun 2, 2026
Organization
Florida International University
Contact
Ahmed Mohamed

