Predictive Battery State of Charge Reference Generation Using Basic Route Information for Optimal Energy Management of Heavy-Duty Fuel Cell Vehicles

Zendegan, Saeid; Ferrara, Alessandro; Jakubek, Stefan; Hametner, Christoph

doi:10.1109/tvt.2021.3121129

Cited by 25 publications

(7 citation statements)

References 26 publications

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“…Because of the technical and monetary challenges of maintaining a stable, reliable, and cost-effective energy infrastructure, it is essential to perform a comprehensive literature review on the efficient hybridization of renewable energy sources. This study [30,31] explored some of the potential difficulties that could emerge from combining a photovoltaic plant with a wind power station to generate electricity for the traditional grid or a standalone system [32]. Now that we have entered the electric vehicle (EV) era, it is crucial that authors do not forget about EVs' potential contribution to auxiliary services through vehicle-to-grid (V2G) technology, which allows the grid to benefit from EVs' on-board batteries.…”

Section: Related Workmentioning

confidence: 99%

A Novel Hybrid Approach for Power Quality Improvement in a Vehicle-to-Grid Setup Using Droop-ANN Model

Aurangzeb

Xin

Iqbal

et al. 2023

International Journal of Energy Research

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The integration of electric vehicles (EVs) in the power grid has attracted considerable attention due to its potential benefits, such as demand response and power quality improvement. However, the intermittent and unpredictable nature of EVs’ charging and discharging behavior can cause significant challenges to the grid’s stability and power quality. This research study explores the use of a droop-ANN model to improve power quality in vehicle-to-grid (V2G) systems. The proposed approach integrates an artificial neural network (ANN) into the droop control technique to accurately predict the voltage and frequency of the charger. Through simulations, the model’s effectiveness in reducing power fluctuations and enhancing power quality was validated. The results indicate that the droop-ANN model significantly improves power quality across various battery state of charge (SoC) and charging/discharging scenarios. The findings highlight the potential of the droop-ANN model to enhance stability and reliability in V2G systems. Further research is needed to validate the model in real-world applications and explore its full potential. Overall, the droop-ANN model offers a promising solution for improving power quality in V2G systems.

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Section: Related Workmentioning

confidence: 99%

A Novel Hybrid Approach for Power Quality Improvement in a Vehicle-to-Grid Setup Using Droop-ANN Model

Aurangzeb

Xin

Iqbal

et al. 2023

International Journal of Energy Research

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“…Now it is used more and more in electric transportation equipment. However, due to the low dynamic reaction of the FCs, batteries or SCs are incorporated to accelerate the energy system response [19][20][21][22]. As with other microgrids, optimizing the different energy sources on board is one of the main concerns of ship operations.…”

Section: Introductionmentioning

confidence: 99%

Proposed Z-Source Electrical Propulsion System of a Fuel Cell/Supercapacitor-Powered Ship

Gan

Shi

2023

JMSE

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The use of green energy to power ships in the marine industry has attracted increasing attention in recent years. This paper presents an inland river cruise ship supplied by a fuel cell (FC) as the main power source and a supercapacitor (SC) as the auxiliary power source. Its propulsion inverter adopts the proposed high-boost Z-source inverter, and the proposed high-voltage-boost Z-source inverter (HVB-ZSI) principle is studied. The advantages of this proposed HVB-ZSI in two cases are verified through simulation. In case 1, it can be seen that the capacitance voltage is only 250 V, and the maximum inductance’s inrush current at the start is less than 200 A. But the capacitance voltage of HVB-ZSI reaches 383 V, and the inrush current is 300 A. While considering different constraints of the propulsion system, four operating modes for the set of the FC and SC are proposed. The small-signal model of the propulsion system is derived, and the control strategy is studied. By controlling the shoot-through duty cycle and modulation factor, the FC power, output power, and state of charge (SOC) of the SC can be controlled. Finally, to verify the performance of the proposed propulsion system, a hybrid power ship prototype equipped with a 7.5 kw propulsion motor is constructed. Four modes of the entire system are simulated by MATLAB/SIMULINK, and its performance is analyzed with experimental results. These results show that the new Z-source propulsion system has a promising application in new energy ships, as it has higher reliability and lower complexity and cost compared to conventional propulsion systems.

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“…Distribution operators could use this short-term energy storage to diminish the congestion on the grid due to conventional loads [9]. The life of the battery can be maximized by enabling controlled charging [10], although regulated EV charging is difficult to achieve since it includes numerous users, each with its own set of priorities.…”

Section: Introductionmentioning

confidence: 99%

The Impact of V2G Charging/Discharging Strategy on the Microgrid Environment Considering Stochastic Methods

Iqbal

Habib²,

Ali³

et al. 2022

Sustainability

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Although electric vehicles (EVs) play a vital role in realizing remarkable features, however, the integration of a huge number of EVs leads to grid congestion as well. As a result, uncontrolled charging might give rise to undervoltage and complex congestion in the electric grid. The reasons for the uncontrolled charging of EVs have been investigated in the recent past to mitigate the effects thereof. It is very challenging to achieve controlled charging due to different constraints at the customer end; therefore, it is better to take the benefits of power prediction schemes for the charging and discharging of EVs. The power prediction scheme is based on a practical power forecast system that exploits the needs of various patterns, and the current research focuses on considering users’ demands. The primary objective of this study is to develop an effective and efficient coordination system for the charging and discharging of EVs by exploiting a smart algorithm that intelligently tackles the possible difficulties to attain optimum power requirements. In this context, a model is proposed based on stochastic methods for analyzing the impact of vehicle-to-grid (V2G) charging and discharging in the microgrid environment. A Markov model is used to simulate the use of EVs. This method works well with the Markov model because of its ability to adjust to random changes. When considering an EV, its erratic travel patterns suggest a string of events that resemble a stochastic process. The proposed model ensures that high power requirements are met during peak hours in a cost-effective manner. In simpler words, the promising features of the proposed scheme are to meet electricity/power demands, monitoring and the efficient forecasting of power. The outcomes revealed an effective power system, EV scheduling, and power supply without compromising the electric vehicle’s presentation of the EV owner’s tour schedule. In terms of comprehensiveness, the developed algorithm exhibits a significant improvement.

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Predictive Battery State of Charge Reference Generation Using Basic Route Information for Optimal Energy Management of Heavy-Duty Fuel Cell Vehicles

Cited by 25 publications

References 26 publications

A Novel Hybrid Approach for Power Quality Improvement in a Vehicle-to-Grid Setup Using Droop-ANN Model

A Novel Hybrid Approach for Power Quality Improvement in a Vehicle-to-Grid Setup Using Droop-ANN Model

Proposed Z-Source Electrical Propulsion System of a Fuel Cell/Supercapacitor-Powered Ship

The Impact of V2G Charging/Discharging Strategy on the Microgrid Environment Considering Stochastic Methods

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