A Q‐Learning and Fuzzy Logic Control of Hybrid Energy Storage
In this article, a control strategy based on the combination of Q-learning and fuzzy logic control approaches is presented for tuning the parameters of a utilized two-stage variable
In this article, a control strategy based on the combination of Q-learning and fuzzy logic control approaches is presented for tuning the parameters of a utilized two-stage variable
In this study, a novel control scheme, termed adaptive LPF, which aims to enhance controller performance by dynamically adjusting to changing conditions, is proposed. The adaptive LPF
This study introduces an innovative power-split approach for hybrid energy storage systems (HESS) and diesel generators, utilizing frequency decoupling and a combination of
Abstract alternative but face a crucial challenge in their battery-based Energy Storage System (ESS). The solution to the battery issues is comb ning it with other ESS with high power
This article focuses on the pivotal role of Low Pass Filters (LPFs) within HESS for EVs, facilitating seamless power flow. The novelty lies in the comprehensive review of LPFs in this context,
One of the most widely applied rule-based EMS techniques is the low-pass filter (LPF), valued for its simplicity and ability to mitigate battery stress by decoupling high-frequency transients from
In this paper, we propose a method to improve the quality of the fuzzy controller for the HESS of EVs. The proposed method involves incorporating a LPF into the fuzzy controller,
This work fills this gap and structures, summarizes, and provides mathematical background and guidelines on filter-based control of hybrid energy storage systems.
In order to overcome the problems of power delay and power cycling caused by the traditional low-pass filter (LPF) power allocation strategy in the hybrid energy storage
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