State of the art and materials based characteristics in power converters for electric vehicles

Aglawe, Kapil R.; Dhande, Mahindra; Matey, Munindra S.; Shelare, Sagar D.

doi:10.1016/j.matpr.2022.02.384

Cited by 16 publications

(3 citation statements)

References 38 publications

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“…The implementation of fuzzy control in irrigation systems ensures the mitigation of the potential hazard of under-irrigation by regulating soil moisture levels to remain above the predetermined threshold set by the user [43]. The findings gained demonstrate the system's effectiveness and dependability in both the summer and autumn [44].…”

Section: Figure 1 Categorize Of Irrigation Systemmentioning

confidence: 90%

Fuzzy rules based smart irrigation system using adaptive bacterial foraging optimization

Bhoyar,

Kanojia,

Chourasia

2024

IOP Conf. Ser.: Earth Environ. Sci.

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The practice of agriculture is heavily reliant on the implementation of irrigation systems. Technology improvements have made it unnecessary to rely on someone else to perform irrigation when we are out and whenever crops need to be watered. Many researchers have attempted to autonomously irrigate crops, but difficulties with accuracy, timing, and cost are rarely addressed and given top priority. The proposed approach employs a real-time sensor, wireless sensor network, the adaptive bacterial foraging optimization (ABFO) algorithm, and a fuzzy irrigation system control to achieve autonomous watering, thereby enabling smart irrigation. This method reduces waste while preserving the container’s water supply. Automated irrigation determines whether crops need to be watered by considering the type of crop, the weather, and the soil moisture and not soil moisture alone. The need for water is calculated using the three aforementioned criteria and fuzzy control drives the automation. Using an arduino-based IoT circuitry, the bioinspired model with algorithm adaptive bacterial foraging optimization, generates the optimized values for three parameters, which are then used by fuzzy logic control to predict the watering requirements of the plants. In terms of accuracy, timeliness, and cost, the suggested approach is advantageous. With this model, it is now possible to completely automate the irrigation system.

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Section: Figure 1 Categorize Of Irrigation Systemmentioning

confidence: 90%

Fuzzy rules based smart irrigation system using adaptive bacterial foraging optimization

Bhoyar,

Kanojia,

Chourasia

2024

IOP Conf. Ser.: Earth Environ. Sci.

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“…For such high-power cases, full-bridge topology or its derived topology is used. 10 The same charger can be used to charge any EV. However, not only will the high-power converter be underutilized to deliver very low power for charging the electric bike (say 250 W as in the case of Hero Electric Flash electric bike used in India); the cost per unit will be high when operated at low power.…”

Section: Need For Simultaneous Charging Of Ev Batteriesmentioning

confidence: 99%

“…Let us consider a two‐output charger designed for 30 kW employed as an off‐board charging system. For such high‐power cases, full‐bridge topology or its derived topology is used 10 . The same charger can be used to charge any EV.…”

Section: Introductionmentioning

confidence: 99%

SiC switch‐based isolated DC‐DC converter for simultaneous charging of Li‐ion batteries of different voltage ratings for low‐ and medium‐power electric vehicle battery charging application

B.S

Arunkumar

2023

Circuit Theory & Apps

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SummaryThe use of electric vehicles (EVs) has gained traction in recent years. With the widespread use of EVs in the future, the waiting time before charging will be high due to the use of slow chargers in developing countries. This work proposes a novel DC‐DC converter based on an isolated single‐ended primary inductor converter (SEPIC) and isolated Ćuk converter to enable simultaneous charging of batteries of low‐ and medium‐power EVs. The proposed converter operates without spikes in input and output currents, even during a sudden source disturbance. It can charge one battery at the output voltage level and simultaneously charge two batteries at half the output voltage. Simulation results for open‐loop and closed‐loop operations are provided to validate the converter operation and the simplicity of control. The proposed converter operation has been experimentally validated using a scaled‐down prototype by charging one 48 V lithium‐ion battery and then simultaneously charging two 24 V lithium‐ion batteries. The converter's response is provided to present the novelty and advantages of the proposed converter. The proposed converter uses fewer switches, diodes, inductors, and capacitors. The size of the system is reduced due to the high switching frequency operation of SiC devices. A low‐side gate driver is sufficient for driving the MOSFET, and the control is simple. The proposed converter offers a new and simple converter to charge multiple low‐ and medium‐power EV batteries of different ratings simultaneously with a low component count.

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Development of IOT-Based Hybrid Helium Drone for Flight Time Enhancement

Waghmare¹,

Shelare²,

Mungle³

et al. 2023

Lecture Notes in Mechanical Engineering

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State of the art and materials based characteristics in power converters for electric vehicles

Cited by 16 publications

References 38 publications

Fuzzy rules based smart irrigation system using adaptive bacterial foraging optimization

Fuzzy rules based smart irrigation system using adaptive bacterial foraging optimization

SiC switch‐based isolated DC‐DC converter for simultaneous charging of Li‐ion batteries of different voltage ratings for low‐ and medium‐power electric vehicle battery charging application

Development of IOT-Based Hybrid Helium Drone for Flight Time Enhancement

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