Ding, H.; Tian, R.; Wang, J.; Yang, X. Power Measurement Using Adaptive Chirp Mode Decomposition for Electrical Vehicle Charging Load. Energies2023, 16, 5305.
Ding, H.; Tian, R.; Wang, J.; Yang, X. Power Measurement Using Adaptive Chirp Mode Decomposition for Electrical Vehicle Charging Load. Energies 2023, 16, 5305.
Ding, H.; Tian, R.; Wang, J.; Yang, X. Power Measurement Using Adaptive Chirp Mode Decomposition for Electrical Vehicle Charging Load. Energies2023, 16, 5305.
Ding, H.; Tian, R.; Wang, J.; Yang, X. Power Measurement Using Adaptive Chirp Mode Decomposition for Electrical Vehicle Charging Load. Energies 2023, 16, 5305.
Abstract
Due to nonlinear components in the charging piles of electric vehicles, harmonics and non-stationary signals in the electric vehicle charging load brings voltage and current distortion, seriously affecting the accuracy of the power-related calculation in non-sinusoidal environments. This paper proposed a new approach to calculate the active power and root mean square values from decomposed components using the adaptive chirp mode decomposition (ACMD) method on voltage and current. The advantage of the ACMD-based method is that it correctly provides the power-related quantities of harmonics or non-stationary components for the electric vehicle charging load. The performance of the proposed method was verified using synthetic signals and simulation tests. The experimental results presented better estimations for each quantity defined in IEEE Standard 1459-2010, compared with the discrete wavelet transform approach.
Keywords
Electric vehicles; Power calculation; Harmonics; Non-stationary; Adaptive chirp mode decomposition.
Subject
Computer Science and Mathematics, Computational Mathematics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
