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CC-CV Charging Control Based on Modified Hamiltonian Control Law for EV Application
(2024-01-01)
Somboonpanya, Nattapon
;
Khomfoi, Surin
;
Phophongviwat, Teeraphon
;
Jamshidpour, Ehsan
;
Thounthong, Phatiphat
This paper proposes constant current-constant voltage (CC-CV) charging control based on Hamiltonian control law with a state observer for a bidirectional buck-boost converter on an EV charger. The CC-CV charging scheme is mainly utilized to charge lithium-ion batteries on an electric vehicle. In CC mode, the battery is charged with a preset value until the battery voltage reaches the desired equalized voltage. During CV mode, equalized current is used to maintain battery voltage to equalize the battery. In this work, equalization current requires the actual battery voltage, desired battery voltage, and the battery current for its calculation. Additionally, a state observer is implemented to estimate voltage across uncertainties of resistance and the battery current. Also, it can enhance the performance of the proposed control scheme and minimize the required sensors. Furthermore, the 1 kW prototype of the bidirectional buck-boost converter is developed to demonstrate the feasibility of the proposed controlled scheme.
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Electric Vehicle Charging Station incorporating with an Energy Management and Demand Response Technique
(2022-01-01)
Peanjad, Pannawat
;
Khomfoi, Surin
A study of Demand Response (DR) function and Energy management for an electrical vehicle (EV) charger is presented in this paper. The proposed technique is to prevent the electrical system within the rated power by controlling electric vehicle chargers loads to the electrical system. A power management method for limiting the charging current and charging time by using state of charge (SoC) as a priority point index is developed. The power management method is also developed as a calculation algorithm for determining the charging current limit rating for electric vehicle chargers. The simulation model is also developed for validating a DR management function of the electric vehicle charger according to Provincial Electricity Authority of Thailand (PEA) load characteristic data. The results show that the proposed DR function can manage the charging current of each electric vehicle charger appropriately. Also. the proposed technique can prevent the rated power demand of the transformer distribution. The study illustrates that this method is an effective protection for the distribution transformer and can be able to apply as a DR function to manage electrical energy more efficiently.
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Experimental Study and Modeling of Automatic Home Energy Management System Using AI
(2021-01-01)
Pranee, Piyanut
;
Jirasuwankul, Nirudh
This paper proposes an experimental study and modeling of Fuzzy logic based-AI for home energy management system. The management model has been designed for home in the subtropical climate zone-like, i.e., Thailand, which having yearly and monthly average temperature of 28°c and 30-38°c in the hottest season respectively. The studied system model comprises of the grid-connected load of home appliances, air conditioner, type-1 EV charger and solar rooftop PV supply. The objective of energy management is to minimize grid power consuming as well as maximizing solar PV utilization with 24-hour load profile, principally running of air conditioner and EV charging load. By testing the proposed management system comparatively to the generic system without managing scheme, energy saving of 43.90% can be achieved under the same operating and environmental conditions. Those are illustrated by the simulation results.

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