CEEMD-Fuzzy Control Energy Management of Hybrid Energy Storage Systems in Electric Vehicles

IEEE TRANSACTIONS ON ENERGY CONVERSION(2024)

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Abstract
To improve the performance of the energy storage system of electric vehicles, a complete ensemble empirical mode decomposition-fuzzy logic control energy management strategy is proposed to attenuate the aging of lithium-ion batteries caused by high-frequency power demand. Firstly, the electric vehicle power demand is decomposed into a finite number of intrinsic mode functions components, and each component is reconstructed into low-frequency or high-frequency components according to its permutation entropy. Then, the low-frequency and high-frequency components of electric vehicle power demand are allocated to lithium-ion batteries and ultracapacitors, respectively. Finally, fuzzy logic based closed loop controller is designed to maintain the state of charge of ultracapacitors at the desired level. Experiments under HWFET, UDDS, US06 and combined drive cycles are performed, and experimental results show that compared with single energy storage system and other state-of-the-art methods, the proposed strategy can effectively reduce the maximum discharge current of the lithium-ion batteries and maintenance the state of charge balance of the ultracapacitor.
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Key words
Power demand,Fuzzy logic,Energy management,Voltage control,Energy storage,Resource management,Voltage,Complete ensemble empirical mode decomposition,electric vehicle,fuzzy logic control,hybrid energy storage systems,power distribution
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