Secure power management strategy for direct torque controlled fuel cell/ supercapacitor electric vehicles

Oubelaid, Adel; Taib, Nabil; Rekioua, Toufik; Bajaj, Mohit; Yadav, Arvind Kumar; Shouran, Mokhtar; Kamel, Salah

doi:10.3389/fenrg.2022.971357

Cited by 36 publications

(11 citation statements)

References 44 publications

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“…To create a robust controller for the HEV system, a model which considers the mechanical behavior of the vehicle based on the traction forces produced by its motors and the forces of reluctance to movement must be constructed which are given by Figure 2. The HEV's trajectory is given as follow according to Newton's law 33 :…”

Section: The Hybrid Systemmentioning

confidence: 99%

“…During emergency scenarios such as an accident, reference 32 studies control solutions for swiftly and safely discharging the high‐voltage dc bus capacitor for the PMSM. It has been discovered in 33 that by making a few changes to the position control technique, torque ripples may be reduced to the level of a sinusoidal stator current response. In addition, for the first time in this technique, the performance indicator 'sensor angle' is used to evaluate the rotor position.…”

Section: Introductionmentioning

confidence: 99%

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Hybrid power management and control of fuel cells‐battery energy storage system in hybrid electric vehicle under three different modes

2023

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In most situations, fuel cells (FCs) are insufficient to supply power demands in hybrid electric vehicles (HEVs), thus battery storage systems (BSSs) are used to make the system more efficient like as rapid starting, high power density, and enhanced dynamic set response. How the power sources are regulated and distributed determines the accomplishment efficiency of the driving forces in such a configuration. The most critical aspect should be how to guarantee torque stability of the traction motor which is in our case a permanent magnet synchronous motor (PMSM) while attaining quick reaction. This study discusses a hybrid battery‐FCs energy storage and management system for a hybrid electric vehicle (HEV), as well as an integrated PMSM's passivity‐based control (PBC) technique to enable power integration and increase the hybrid electric vehicle (HEV)'s operating speed. The present paper is separated into two sections. First, a power management control (PMC) technology is used to manage the FCs‐battery system to guarantee that the HEV gets continuous power from the hybrid energy resources, where a fuzzy logic controller is used as an artificial intelligence system for the FCs converter to maximize the power produced. The second is dedicated to the new proposed PBC control of the EV's PMSM to rectify non‐linearities, external disturbances, and parametric fluctuations. The standard proportional‐integral (PI) control and sliding mode control (SMC) are built for comparison with the proposed PBC dedicated to the PMSM in order to properly assess the efficacy of the proposed control strategy. The simulation results obtained using MATALB/Simulink show that the proposed PBC technique and hybrid battery‐ proton‐exchange membrane PEMFCs energy management enables high power integration and increase the EV's operational speed.

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Section: The Hybrid Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Hybrid power management and control of fuel cells‐battery energy storage system in hybrid electric vehicle under three different modes

2023

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“…These EVCSs are utilized as power filters in bandwidth regulation, load shifting, generation balance, and STATCOM (Wang and Wang, 2013;Liu and Liu, 2021a;Kumar et al, 2023). In their work, S. Devassy and B. Singh (Devassy and Singh, 2018;Liu and Liu, 2021b;Oubelaid et al, 2022a) devised an integrated approach incorporating a unified power quality conditioner (UPQC) with a three-phase solar PV system. The study involved an analysis of dynamic performance under varying irradiation levels and instances of grid voltage sags or swells.…”

Section: Introductionmentioning

confidence: 99%

“…Hence, it improves the quality of power. Due to the restricted cost and complex control of the UPQC, its utilization is limited in local distribution networks (Oubelaid et al, 2022a). In their studies, Yan and Wen (2021); Gao et al (2022); Yang et al (2022) introduced the DC-UPQC approach, incorporating a series-side distribution static synchronous compensator (DAB), a parallel-side DAB, and a superconducting magnetic energy storage (SMES) system.…”

Section: Introductionmentioning

confidence: 99%

Unified power quality conditioner-based solar EV charging station using the GBDT–JS technique

Prasada Rao,

Pandian,

Reddy

et al. 2024

Front. Energy Res.

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This manuscript proposes a novel hybrid artificial intelligence (AI) approach for a unified power quality conditioner (UPQC) designed specifically for electric vehicle charging stations (EVCSs). The aim is to integrate multiple vehicle-to-grid (V2G) functionalities, thereby mitigating the challenges associated with electric vehicle (EV) grid integration and the incorporation of distributed energy resources (DERs). The hybrid technique presented in this manuscript combines the gradient boosting decision tree (GBDT) algorithm and the jellyfish search (JS) algorithm, referred to as the GBDT–JS technique. This innovative approach involves utilizing the charging station to offer EV charging services and facilitating the discharge of EVs to the power grid. Integration of the UPQC with DERs, such as photovoltaic (PV), is implemented to decrease the power rating of converters and fulfill power demand requirements. The initial converter within the UPQC is employed to manage the direct current (DC) voltage, while the second converter oversees the power charging or discharging processes of EVs. Additionally, it mitigates the impact of battery voltage fluctuations. The UPQC with vehicle-to-grid functionality minimizes the load pressure on the grid, preventing over-current issues. The presented approach regulates the UPQC converters to mitigate power quality issues such as harmonic currents and voltage sags. Subsequently, the effectiveness of this technique is demonstrated using the MATLAB/Simulink operating platform. The evaluation of GBDT–JS performance involves a comparative analysis with existing techniques. This assessment reveals that the proposed method effectively alleviates power quality issues, specifically reducing total harmonic distortion (THD), and delivers optimal outcomes.

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“…Integration of electric vehicles with microgrids has also been presented by various researchers. In [25], the authors discussed the bidirectional power flow of EV charging stations.…”

Section: Introductionmentioning

confidence: 99%

A Novel Electric Vehicle Battery Management System Using an Artificial Neural Network-Based Adaptive Droop Control Theory

Afzal

Aurangzeb

Iqbal

et al. 2023

International Journal of Energy Research

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The novelty of this research lies in the development of a new battery management system (BMS) for electric vehicles, which utilizes an artificial neural network (ANN) and fuzzy logic-based adaptive droop control theory. This innovative approach offers several advantages over traditional BMS systems, such as decentralized control architecture, communication-free capability, and improved reliability. The proposed BMS control system incorporates an adaptive virtual admittance, which adjusts the value of the virtual admittance based on the current state of charge (SOC) of each battery cell. This allows the connected battery cells to share the load evenly during charging and discharging, which improves the overall performance and efficiency of the electric vehicle. The effectiveness of the proposed control structure was verified through simulation and experimental prototype testing with three linked battery cells. The small signal model testing demonstrated the stability of the control, while the experimental results confirmed the system’s ability to evenly distribute the load among battery cells during charging and discharging. We introduce a unique battery management system (BMS) for electric cars in this paper. Our suggested BMS was implemented and tested satisfactorily on a 100 kWh lithium-ion battery pack. When compared to typical BMS systems, the results show a surprising 15% increase in overall energy efficiency. Furthermore, the adaptive virtual admission function resulted in a 20% boost in battery life. These large gains in energy efficiency and battery longevity demonstrate our BMS’s efficacy and superiority over competing systems. Overall, the proposed BMS represents a significant innovation in the field of electric vehicle battery management. This combination of ANN and adaptive droop control theory based on fuzzy logic provides a highly efficient, reliable, and economical solution for EV battery cell management.

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Secure power management strategy for direct torque controlled fuel cell/ supercapacitor electric vehicles

Cited by 36 publications

References 44 publications

Hybrid power management and control of fuel cells‐battery energy storage system in hybrid electric vehicle under three different modes

Hybrid power management and control of fuel cells‐battery energy storage system in hybrid electric vehicle under three different modes

Unified power quality conditioner-based solar EV charging station using the GBDT–JS technique

A Novel Electric Vehicle Battery Management System Using an Artificial Neural Network-Based Adaptive Droop Control Theory

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