Zhao, Ganglei (Xiamen university), Liu, ChangXing (Xiamen University), Li, Xiang (Xiamen University), Zhang, Huiliu (Xiamen University), Li, Po (Xiamen University)

Energy Management Strategy of Fuel Cell/Battery/Supercapacitors Hybrid Storage System Based on Adaptive Real-Time Wavelets_Fuzzy Logic

Scheduled for presentation during the Regular session "Energy Management" (FrB2), Friday, November 1, 2024, 10:30−10:50, Room T2

7th IFAC Conference on Engine and Powertrain Control, Simulation and Modeling, Oct 30 - Nov 1, 2024, Dalian, China

This information is tentative and subject to change. Compiled on January 2, 2025

Abstract

At present, the hybrid energy storage system (HESS) composed of clean energy represented by fuel cells, batteries and supercapacitors has attracted much attention in vehicle applications. However, the HESS has a complex structure. To enhance HESS performance and reliability in electric vehicles, this paper proposes an energy management strategy (EMS) using adaptive real-time wavelet transform and fuzzy logic control. The strategy uses adaptive real-time wavelet transform to dynamically select the number of decomposition layers according to remaining power of the battery, and effectively extracts low-frequency power and allocates it to the battery. Fuzzy logic control keeps state of charge of the supercapacitor at an appropriate level. To ascertain the effectiveness of the proposed approach, based on World Light Vehicle Test Protocol (WLTP) data, the proposed EMS is compared with the EMS based on wavelet transform. The results show that the proposed EMS can effectively reduce the maximum discharge current of lithium-ion batteries and maintain the charge balance state of supercapacitors. It provides an effective method for energy management of HESS.