Control Strategies, Economic Benefits, and Challenges of Vehicle-to-Grid Applications: Recent Trends Research

Chen, Guangjie; Zhang, Zhaoyun

doi:10.3390/wevj15050190

Cited by 5 publications

(1 citation statement)

References 46 publications

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“…Furthermore, IBDCs play a core role in energy recovery, particularly during regenerative braking, where they convert electrical energy generated by the electric motor into a form suitable for battery storage. In terms of charging [7] control, they optimize the charging efficiency by adjusting the charging current and voltage while protecting the battery from the risks of overcharging or overheating. IBDCs also enhance the compatibility between electric vehicles and different charging stations and grid systems [8], improving charging flexibility.…”

Section: Introductionmentioning

confidence: 99%

Overview of Isolated Bidirectional DC–DC Converter Topology and Switching Strategies for Electric Vehicle Applications

Wang,

Su,

Zeng

et al. 2024

Energies

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Isolated bidirectional DC–DC converters are becoming increasingly important in various applications, particularly in the electric vehicle sector, due to their ability to achieve bidirectional power flow and their safety features. This paper aims to review the switch strategies and topologies of isolated bidirectional DC–DC converters, with a specific focus on their applications in the field of electric vehicles. From the perspective of topology, PWM-type isolated bidirectional DC–DC converters, dual active bridge converters, and resonant-type isolated bidirectional DC–DC converters constitute the three main categories of these converters. The paper further examines the traditional switch strategies of these converters and discusses how specific switch technologies, such as single-phase shift, expanding-phase shift, double-phase shift, and triple-phase shift, can enhance the overall performance of isolated bidirectional DC–DC converters. The paper meticulously examines the characteristics of each topology and control scheme, as well as their typical use cases in practical applications. Particularly, the paper delves into the applications of isolated bidirectional DC–DC converters in the electric vehicle sector and draws conclusions regarding their potential and trends in future electric vehicle technology.

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Section: Introductionmentioning

confidence: 99%

Overview of Isolated Bidirectional DC–DC Converter Topology and Switching Strategies for Electric Vehicle Applications

Wang,

Su,

Zeng

et al. 2024

Energies

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Artificially Intelligent Vehicle-to-Grid Energy Management: A Semantic-Aware Framework Balancing Grid Demands and User Autonomy

Elkhodr

2024

Computers

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As the adoption of electric vehicles increases, the challenge of managing bidirectional energy flow while ensuring grid stability and respecting user preferences becomes increasingly critical. This paper aims to develop an intelligent framework for vehicle-to-grid (V2G) energy management that balances grid demands with user autonomy. The research presents VESTA (vehicle energy sharing through artificial intelligence), featuring the semantic-aware vehicle access control (SEVAC) model for efficient and intelligent energy sharing. The methodology involves developing a comparative analysis framework, designing the SEVAC model, and implementing a proof-of-concept simulation. VESTA integrates advanced technologies, including artificial intelligence, blockchain, and edge computing, to provide a comprehensive solution for V2G management. SEVAC employs semantic awareness to prioritise critical vehicles, such as those used by emergency services, without compromising user autonomy. The proof-of-concept simulation demonstrates VESTA’s capability to handle complex V2G scenarios, showing a 15% improvement in energy distribution efficiency and a 20% reduction in response time compared to traditional systems under high grid demand conditions. The results highlight VESTA’s ability to balance grid demands with vehicle availability and user preferences, maintaining transparency and security through blockchain technology. Future work will focus on large-scale pilot studies, improving AI reliability, and developing robust privacy-preserving techniques.

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A Feed-Forward Back-Propagation Neural Network Approach for Integration of Electric Vehicles into Vehicle-to-Grid (V2G) to Predict State of Charge for Lithium-Ion Batteries

Cervellieri

2024

Energies

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The accurate prediction and efficient management of the State of Charge (SoC) of electric vehicle (EV) batteries are critical challenges in the integration of vehicle-to-grid (V2G) systems within multi-energy microgrid (MMO) models. Inaccurate SoC estimation can lead to inefficiencies, increased costs, and potential disruptions in power generation. This paper addresses the problem of optimizing SoC estimation to enhance the reliability and efficiency of V2G scheduling and MMO coordination. In this work, we develop a Feed-Forward Back-Propagation Network (FFBPN) using MATLAB 2024 software, employing the Levenberg–Marquardt algorithm and varying the number of hidden neurons to achieve better performance; performance was measured by the maximum coefficient of determination (R2) and the minimum mean squared error (MSE). Utilizing the NASA Prognostics Center of Excellence (PCoE) dataset, we validate the model’s capability to accurately predict the life cycle of EV batteries. Our proposed FFBPN model demonstrates superior performance compared to existing methods from the literature, offering significant implications for future V2G system developments. The comparison between training, validation, and testing phases underscores the model’s validity and precisely identifies the characteristic curves of FFBPN, showcasing its potential to enhance profitability, efficiency, production, energy savings, and minimize environmental impact.

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Control Strategies, Economic Benefits, and Challenges of Vehicle-to-Grid Applications: Recent Trends Research

Cited by 5 publications

References 46 publications

Overview of Isolated Bidirectional DC–DC Converter Topology and Switching Strategies for Electric Vehicle Applications

Overview of Isolated Bidirectional DC–DC Converter Topology and Switching Strategies for Electric Vehicle Applications

Artificially Intelligent Vehicle-to-Grid Energy Management: A Semantic-Aware Framework Balancing Grid Demands and User Autonomy

A Feed-Forward Back-Propagation Neural Network Approach for Integration of Electric Vehicles into Vehicle-to-Grid (V2G) to Predict State of Charge for Lithium-Ion Batteries

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