A Technology Review of Energy Storage Systems, Battery Charging Methods and Market Analysis of EV Based on Electric Drives

Shahapure, Sachin Baliram; Kulkarni, Vikas; Shinde, Sanjay M.

doi:10.37391/ijeer.100104

Cited by 14 publications

(5 citation statements)

References 53 publications

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“…The DC/DC converter is controlled by pulses generated from an external PI block's output. The electric vehicle may be charged to a maximum of 6 kW when overall power generation exceeds consumption [121].…”

Section: I-v Controller For Electric Vehiclementioning

confidence: 99%

A Comprehensive Review of Electric Vehicle Charging Stations with Solar Photovoltaic System Considering Market, Technical Requirements, Network Implications, and Future Challenges

et al. 2023

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Electric cars (EVs) are getting more and more popular across the globe. While comparing traditional utility grid-based EV charging, photovoltaic (PV) powered EV charging may significantly lessen carbon footprints. However, there are not enough charging stations, which limits the global adoption of EVs. More public places are adding EV charging stations as EV use increases. However, using the current utility grid, which is powered by the fossil fuel basing generating system, to charge EVs has an impact on the distribution system and could not be ecologically beneficial. The current electric vehicle (EV) market, technical requirements including recent studies on various topologies of electric vehicle/photovoltaic systems, charging infrastructure as well as control strategies for Power management of electric vehicle/photovoltaic system., and grid implications including electric vehicle and Plug-in hybrid electric vehicles charging systems, are all examined in depth in this paper. The report gives overview of present EV situation as well as a thorough analysis of significant global EV charging and grid connectivity standards. Finally, the challenges and suggestions for future expansion of the infrastructure of EV charging, grid integration, are evaluated and summarized. It has been determined that PV-grid charging has the ability to create a profit. However, due to the limited capacity of the PV as well as the batteries, the Power system may not be cost effective. Furthermore, since PV is intermittent, it is probable that it will not be able to generate enough electricity to meet consumer demand.

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Section: I-v Controller For Electric Vehiclementioning

confidence: 99%

A Comprehensive Review of Electric Vehicle Charging Stations with Solar Photovoltaic System Considering Market, Technical Requirements, Network Implications, and Future Challenges

et al. 2023

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“…Bearings and gears are one of the most important components in the manufacture of wireless chargers. They affect the transmission efficiency, alignment error tolerance, charging power matching and thermal reliability of wireless charger performance [1][2][3]. For example, the shaft of the wireless charger is a key component, and the installation of the shaft is related to the service life and experience of the wireless charger.…”

Section: Introductionmentioning

confidence: 99%

“…Many results show that DL has strong scalability and generalisation capability compared to previously used machine learning algorithms (ML) such as Logistic Regression (LR), k-Nearest Neighbour (k-NN) and Support Vector Machine (SVM) and does not require manual feature extraction [14][15][16]. However, DL-enabled methods still have some limitations, such as: (1) source and target domains are evenly distributed; (2) the target domain has enough error data. Moreover, it is still difficult to meet both of the above requirements simultaneously.…”

Section: Introductionmentioning

confidence: 99%

A Deep Transfer Learning-Based Network for Diagnosing Minor Faults in the Production of Wireless Chargers

Wang,

Li,

Zhu

2023

Applied Sciences

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Wireless charger production is critical to energy storage, and effective fault diagnosis of bearings and gears is essential to ensure wireless charging performance with high efficiency, high tolerance to misalignment, and thermal safety. As minor faults are usually difficult to detect, timely diagnosis and detection of minor faults can prevent the fault from worsening and ensure the safety of wireless charging systems. Diagnosing minor faults in bearings and gears with data is a useful but difficult task. To achieve a satisfactory diagnosis of minor faults in the production of wireless charging systems related to the mechanical system that produces wireless charging devices, such as robot arms, this paper proposes a deep learning network based on CNN and LSTM (DTLCL). The method uses deep learning network, model-based transfer learning and range adaptation technology. First, a deep neural network is built to extract significant fault features. Second, the deep transfer network is initialised using model-based transfer learning with a good starting point. Finally, range adaptation using the maximum mean discrepancy between the features learned from the source and target ranges is realised by a multi-layer adaptive technology. The effectiveness of the method was verified using actual measurement data. The training time is 19 s, and the accuracy exceeds 94.5%. The explanation results show that the proposed DTLCL method provides higher accuracy and robust identification of smaller errors compared to the current combination of integrated and single non-transmission models. Due to its data-driven nature, the DTLCL method could be used for fault diagnosis of bearings and gears, which would further promote the application process of wireless charging.

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“…Many automotive sectors are giving priority to BLDC motors in testing their electrified vehicle designs. To assure improved characteristics, the cogging torque is a relatively difficult problem in BLDC motors that demands an urgent solution [5][6][7].…”

Section: ░ 1 Introductionmentioning

confidence: 99%

FEA Based Design of Outer Rotor BLDC Motor for Battery Electric Vehicle

Rupam

Marwaha

2022

IJEER

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Due to enormous advantages, BLDC motors have been identified for the design in various applications. With its good power density, this motor is being used by the automobile industry. The paper aims to design the motor for the battery electric vehicle. The major challenge of the BLDC motor is to reduce torque ripples which appear because of high cogging torque. Torque ripple results in acoustic noise and vibrations in the battery electric vehicle which badly affects the performance of the vehicle. The cogging torque and efficiency are characterized by a parametric technique with varying pole embrace factor and magnetic thickness. The selection of optimum values of rotor pole embrace factor and magnetic thickness has a significant role in the reduction of cogging torque. The Ansys Maxwell tool helps in the optimum designing of the motor by mitigating the torque ripples and thus increasing the average torque. The proposed model has 5.7% better efficiency in comparison to the base model and has a small number of torque ripples.

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A Technology Review of Energy Storage Systems, Battery Charging Methods and Market Analysis of EV Based on Electric Drives

Cited by 14 publications

References 53 publications

A Comprehensive Review of Electric Vehicle Charging Stations with Solar Photovoltaic System Considering Market, Technical Requirements, Network Implications, and Future Challenges

A Comprehensive Review of Electric Vehicle Charging Stations with Solar Photovoltaic System Considering Market, Technical Requirements, Network Implications, and Future Challenges

A Deep Transfer Learning-Based Network for Diagnosing Minor Faults in the Production of Wireless Chargers

FEA Based Design of Outer Rotor BLDC Motor for Battery Electric Vehicle

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