Design and Implementation of Real Time Charging Optimization for Hybrid Electric Vehicles

Ramesh, Konam; Bharatiraja, C.; Raghu, S.; Vijayalakshmi, G.; Sambanthan, Pl.

doi:10.11591/ijpeds.v7.i4.pp1261-1268

Cited by 14 publications

(7 citation statements)

References 18 publications

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“…The power prediction model developed depends on an individual customer's power requirements. During huge power demand, the power prediction model acts quickly and efficiently to respond to the charging station [65,70]. The power required for charging the ith EV is based on the SOC of the vehicle, plugged time, and charging mode: The power prediction model developed depends on an individual customer's power requirements.…”

Section: Grid-connected Res-powered DC Mg For Ev Chargingmentioning

confidence: 99%

Electric Vehicles Charging Stations’ Architectures, Criteria, Power Converters, and Control Strategies in Microgrids

Abraham

Verma

Kanagaraj³

et al. 2021

Electronics

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The usage of electric vehicles (EV) has been increasing over the last few years due to a rise in fossil fuel prices and the rate of increasing carbon dioxide (CO2) emissions. EV-charging stations are powered by existing utility power grid systems, increasing the stress on the utility grid and the load demand at the distribution side. DC grid-based EV charging is more efficient than AC distribution because of its higher reliability, power conversion efficiency, simple interfacing with renewable energy sources (RESs), and integration of energy storage units (ESU). RES-generated power storage in local ESU is an alternative solution for managing the utility grid demand. In addition, to maintain the EV charging demand at the microgrid levels, energy management and control strategies must carefully power the EV battery charging unit. In addition, charging stations require dedicated converter topologies, control strategies, and need to follow set levels and standards. Based on EV, ESU, and RES accessibility, different types of microgrid architecture and control strategies are used to ensure optimum operation at the EV-charging point. Based on the above said merits, this review paper presents different RES-connected architecture and control strategies used in EV-charging stations. It highlights the importance of different charging station architectures with current power converter topologies proposed in the literature. In addition, a comparison of microgrid-based charging station architecture with its energy management, control strategies, and charging converter controls are also presented. The different levels and types of charging stations used for EV charging, in addition to controls and connectors used, are also discussed. An experiment-based energy management strategy was developed to control power flow among the available sources and charging terminals for the effective utilization of generated renewable power. The main motive of the EMS and its control is to maximize the usage of RES consumption. This review also provides the challenges and opportunities in EV-charging, and parameters in selecting appropriate charging stations.

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Section: Grid-connected Res-powered DC Mg For Ev Chargingmentioning

confidence: 99%

Electric Vehicles Charging Stations’ Architectures, Criteria, Power Converters, and Control Strategies in Microgrids

Abraham

Verma

Kanagaraj³

et al. 2021

Electronics

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“…The wearable devices and other battery-operated devices encounter power and performance conditions [74]. The IoT based use-cases have been proposed for smart energy management to automate and analyze energy usage in different infrastructures [75][76][77]. The power management varies upon devices from the smart meter to laptops.…”

Section: Security and Standardsmentioning

confidence: 99%

Systematic Approach for State-of-the-Art Architectures and System-on-Chip Selection for Heterogeneous IoT Applications

et al. 2021

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The Internet of Things (IoT) refers to a network of physical devices, which collects data and processes into a system without human intervention. In the commercialized market, IoT architectures are upgrading day by day to reduce data transmission costs, latency, and bandwidth usage for various application requirements. The extensively available IoT architectures and their specification resist the researchers to select a system-on-chip (SoC) for heterogeneous IoT applications. This paper seeks to comprehend the various IoT device specifications and their characteristics to support multiple applications. Moreover, microprocessor architectures and their components are detailed to facilitate developer knowledge in advanced methodology and technology. The various instructions set architectures (ISA) are implemented in a Zynq-7000 (xc7Zz20clg484-1) FPGA device to examine the feasibility of design space requirements for real-time hardware execution. To select specific system-on-chip (SoC) architecture for heterogeneous IoT applications, a genetic algorithm (GA) based optimization method is implemented in MATLAB. The proposed algorithm identifies the optimized SoC architecture concerning device parameters such as a clock, cache, RAM space, external storage, network support, etc. Further, the confusion matrix method evaluates the proposed algorithm's accuracy, which yields 84.62% accuracy. The outcome of SoCs attained through the GA are tested by analyzing their execution time and performance using various evaluation benchmarks. This article helps the researchers and field engineers to comprehend the microarchitecture device configurations and to identify the superior SoC for next-generation IoT practices.INDEX TERMS Internet of Things, Microprocessors, System-on-chip, Heterogeneous Architectures, and Edge Computing.

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“…The main advantage of using this controller is because it is cheap unit as well as open source code application [19]. 4) HC-5 Bluetooth communication device [20][21][22], Bluetooth is one of the devices used for wireless communication. B) Android smartphone monitoring application, this application designed by using AppyBuilde [ an open source evolution of that prototype, in order to obtain a new monitoring and control system at a lower cost and with increased reliability of the instrument [18][22].…”

Section: Introductionmentioning

confidence: 99%

Smart Monitoring System of DC to DC Converter for Photovoltaic Application

Abed

2018

IJPEDS

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This paper presents a new smart monitoring system designed based on dc to dc converter for photovoltaic application. This system design according two parts to monitor input-output voltages and currents for dc/dc converter, (a) control system: the control system using Arduino NANO as microcontroller to read the measuring voltage and current values from sensor circuits of voltage and current. The measuring data send by Bluetooth HC-05 to end user (monitor system). Bluetooth as wireless communication between the control system and monitoring system (end users). (b) monitoring system: The monitoring system application program as a new application designed to monitor the received data from control system from safety distance (around 10m). the application program designed by the open source AppyBuilder software. The AppyBuilder is an open source software for easily building Android smartphone application. The advantages of the final circuit can be used to monitor step-up or step-down topologies, low-cost, and high-efficiency performance.

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Design and Implementation of Real Time Charging Optimization for Hybrid Electric Vehicles

Cited by 14 publications

References 18 publications

Electric Vehicles Charging Stations’ Architectures, Criteria, Power Converters, and Control Strategies in Microgrids

Electric Vehicles Charging Stations’ Architectures, Criteria, Power Converters, and Control Strategies in Microgrids

Systematic Approach for State-of-the-Art Architectures and System-on-Chip Selection for Heterogeneous IoT Applications

Smart Monitoring System of DC to DC Converter for Photovoltaic Application

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