Assessment of supercapacitor performance in a hybrid energy storage system with an EMS based on the discrete wavelet transform. (January 2023)

• Record Type: Journal Article
• Authors: Robayo, Miguel; Mueller, Markus; Sharkh, Suleiman; Abusara, Mohammad
• Is Part Of: Journal of energy storage. Volume 57(2023)
• Publication Date: 2023-01
• Subjects: Hybrid energy storage -- Discrete wavelet transform -- Electric vehicle -- Energy management system -- Long-short term memory neural network; Energy storage -- Periodicals; Energy storage -- Research -- Periodicals; 621.3126
• DOI: 10.1016/j.est.2022.106200
• Languages: English
• ISSNs: 2352-152X

Abstract

Abstract: When battery and supercapacitor (SC) Energy Storage Systems (ESSs) coexist in electric vehicles, energy management is imperative to ensure efficient power distribution based on the strengths and weaknesses of each ESS. The decoupling of highly dynamic power demands into components that match the dynamic nature of each ESS is essential. The Discrete Wavelet Transform (DWT) has been widely recommended for this purpose as part of real time energy management systems. However, due to DWT signal processing, delays in the frequency components can undermine the benefits of hybridization. This paper analyses the contribution of the SC to alleviate the battery when the DWT is used with and without time delay compensation using future demand prediction. Four different implementation strategies for a DWT based EMS have been evaluated using different metrics to quantify energy circulation and SC assistance during acceleration and braking. Simulation results using urban and highway driving cycles, show that obtaining the SC current reference as the difference between the real time current demand and the DWT low frequency component enhances SC assistance during acceleration and braking at the expense of higher energy circulation. The complexity added by future demand prediction does not reap SC performance benefits.