Bidirectional converter based on G2V and V2G operation with time of usage-based tariff analysis and monitoring of charging parameters using IoT

Adhikary, Sarasij; Biswas⃰, Pabitra Kumar; Sain, Chiranjit; Babu, Thanikanti Sudhakar; Nwulu, Nnamdi

doi:10.1016/j.egyr.2023.04.358

Cited by 14 publications

(4 citation statements)

References 35 publications

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“…Similar to this, the maximal SoC starts to drop as a cell age. Accordingly, a 100% SoC for an old cell would be similar to a 75%-80% SoC for a young cell [27].…”

Section: ) Features Descriptionmentioning

confidence: 99%

Efficient Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles Using Classifier Fusion Technique

Chatterjee,

Biswas,

Sain

et al. 2023

IEEE Access

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This paper presents an efficient energy management strategy for Fuel Cell Hybrid Electric Vehicles (FCHEV) using a Machine Learning (ML) approach. Petroleum-based fuels are utilised in conventional cars to provide good performance and long-distance speed. There are certain disadvantages to using petrol or diesel, such as poor fuel economy and pollution-causing exhaust gas emissions. Furthermore, there are some limitations with existing available work, and the merger of these different optimisation techniques will be advantageous for achieving optimal performance. To address them, the purpose of this research is to create an efficient energy management approach by combining SVM, KNN, and the Naive Bayes technique. Additionally, by combining these classifier techniques better performing EMS is developed. Using the proposed features, the optimisation approach's performance accuracy is increased. Furthermore, these individual classifiers comprising of SVM, KNN & Naïve Bayes is giving accuracy percentage of 96%, 92% & 94% respectively. Finally, after combining these three classifiers we have achieved an accuracy percentage of 98%.

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“…Similar to this, the maximal SoC starts to drop as a cell age. Accordingly, a 100% SoC for an old cell would be similar to a 75%-80% SoC for a young cell [27].…”

Section: ) Features Descriptionmentioning

confidence: 99%

Efficient Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles Using Classifier Fusion Technique

Chatterjee,

Biswas,

Sain

et al. 2023

IEEE Access

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“…V2G technology can enable the batteries of electric vehicles not only to store electricity to provide power, but also to store the remaining power to support the grid balance by connecting it to the grid [3]. This technology can regard electric vehicles as flexible loads, rather than loads that only consume electrical energy.…”

Section: V2g Definitionmentioning

confidence: 99%

Research and Analysis on V2G Technology and Its Application

Qiu

2023

HSET

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In recent years, with the increasing popularity of new energy vehicles and the gradual increase in the number of charging piles, V2G technology has gradually emerged. Compared with the traditional grid charging system, which mostly uses natural energy, has unstable charging, and is difficult to interact with the grid, V2G technology uses new energy electric vehicles to interact with the grid, which has a better effect of adjusting the grid balance, peak shaving and filling, adjusting power consumption, and allowing more users to participate in power generation. This article studies the definition and principles of V2G technology, as well as its development history, relevant research and innovation achievements in this field. Secondly, the article expounds on the basic working principle and practical application of V2G, including interaction control systems, grid interaction, and virtual power plants. In order to verify the basic principles of V2G technology, this article constructs and simulates a Simulink circuit to convert the direct current of electric vehicles into alternating current of the grid by step-up inverters, further verifying the basic working principles of V2G.

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“…Figure 1 depicts the various types of EVs which are available in the global market. Clustering methods are employed to overcome power grid issues caused by electric vehicle growth [3]. It evaluates current approaches, examines user behavior, driving patterns, batteries, and charging stations, and offers study on distribution implications, emergency charging, rebate equity, and big data in transportation management.…”

Section: Introductionmentioning

confidence: 99%

Soft-switching dual Active Bridge Converter-based Bidirectional On-Board Charger for Electric Vehicles under Vehicle-to-Grid and Grid-to-Vehicle Control Optimization

Sonnati,

Arandhakar,

Phani Kumar

2024

E3S Web Conf.

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Electric Vehicles (EVs) are rapidly replacing conventional fuel vehicles, offering powerful, emission-free performance. This paper introduces an innovative three-phase bidirectional charger for Grid-to-Vehicle (G2V) and Vehicle-to-Grid (V2G) applications, strengthening the connection between EVs and the power grid. The charger employs a two-stage power conversion approach with advanced converters and a simplified dq-based charging control strategy. An efficient AC-DC converter facilitates smooth transitions between modes, responding to grid directives for active and reactive power. A Soft Switching Dual Active Bridge (SS-DAB) DC-DC converter optimally interfaces with the EV battery pack, while dual active LCL filters suppress harmonics, enhancing system performance. Simulated results confirm the charger’s effectiveness in a 3.5kW prototype using MATLAB/Simulink.

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Bidirectional converter based on G2V and V2G operation with time of usage-based tariff analysis and monitoring of charging parameters using IoT

Cited by 14 publications

References 35 publications

Efficient Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles Using Classifier Fusion Technique

Efficient Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles Using Classifier Fusion Technique

Research and Analysis on V2G Technology and Its Application

Soft-switching dual Active Bridge Converter-based Bidirectional On-Board Charger for Electric Vehicles under Vehicle-to-Grid and Grid-to-Vehicle Control Optimization

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