TY - JOUR
T1 - A Novel Hybrid Energy Storage System With an Adaptive Digital Filter-Based Energy Management Strategy for Electric Vehicles
AU - Lee, Yu Lin
AU - Lin, Chang Hua
AU - Chang, Chun Hsin
AU - Liu, Hwa Dong
AU - Chen, Chun Cheng
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2024
Y1 - 2024
N2 - This study aims to develop a novel hybrid energy storage system (HESS) with an adaptive digital filter-based energy management strategy (ADFBEMS) for electric vehicles (EVs). The proposed HESS comprises a lithium-ion (Li-ion) supercapacitor (SC) and a battery module. An interleaved boost converter with synchronous rectification, which can achieve the load power distribution function, connects the SC with the battery module. Furthermore, the proposed ADFBEMS utilizes the sliding discrete fast Fourier transform (SDFFT) to track the instant load spectrum and the low-pass filter with the adaptive cutoff frequency to realize the load distribution based on frequency, where the SCs take charge of the load's high-frequency component, and the battery module supplies the rest of the load component. A model of the proposed HESS with ADFBEMS is developed in MATLAB and verified through the hardware experiments under the worldwide harmonized light vehicles test cycle (WLTC) Class 1. Both the simulation and hardware experimental results prove the proposed HESS with ADFBEMS's effectiveness by comparing it with the traditional filter-based (fixed cutoff frequency) energy management strategy (EMS). With the help of the proposed HESS with ADFBEMS, Δ P stress and the high-frequency ratio (HFR) can be reduced by 11.06% and 27.46%, respectively, which was beneficial to the battery module's lifetime.
AB - This study aims to develop a novel hybrid energy storage system (HESS) with an adaptive digital filter-based energy management strategy (ADFBEMS) for electric vehicles (EVs). The proposed HESS comprises a lithium-ion (Li-ion) supercapacitor (SC) and a battery module. An interleaved boost converter with synchronous rectification, which can achieve the load power distribution function, connects the SC with the battery module. Furthermore, the proposed ADFBEMS utilizes the sliding discrete fast Fourier transform (SDFFT) to track the instant load spectrum and the low-pass filter with the adaptive cutoff frequency to realize the load distribution based on frequency, where the SCs take charge of the load's high-frequency component, and the battery module supplies the rest of the load component. A model of the proposed HESS with ADFBEMS is developed in MATLAB and verified through the hardware experiments under the worldwide harmonized light vehicles test cycle (WLTC) Class 1. Both the simulation and hardware experimental results prove the proposed HESS with ADFBEMS's effectiveness by comparing it with the traditional filter-based (fixed cutoff frequency) energy management strategy (EMS). With the help of the proposed HESS with ADFBEMS, Δ P stress and the high-frequency ratio (HFR) can be reduced by 11.06% and 27.46%, respectively, which was beneficial to the battery module's lifetime.
KW - Adaptive digital filter-based energy storage system (ADFBEMS)
KW - hybrid energy storage system (HESS)
KW - interleaved boost converter with synchronous rectification
KW - sliding discrete fast Fourier transform (SDFFT)
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U2 - 10.1109/TTE.2023.3320817
DO - 10.1109/TTE.2023.3320817
M3 - Article
AN - SCOPUS:85174812556
SN - 2332-7782
VL - 10
SP - 5131
EP - 5142
JO - IEEE Transactions on Transportation Electrification
JF - IEEE Transactions on Transportation Electrification
IS - 3
ER -