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IoT Enabled Monitoring of an Optimized Electric Vehicle’s Battery System

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Abstract

The rising number of distributed generation, aging of existing grid infrastructure and appeal for the transformation of networks have sparked the interest in smart grid. For the development and improvement of smart grid, Internet of Things (IoT) technology is an important enabler. Use of Electric Vehicles (EVs) as dynamic electrical energy storage system in smart grid offers numerous advantages while affecting the grid and EV battery pack. To diminish the impact of mass adoption of EVs, this paper proposes an optimization model aimed at maximizing the trade revenue for EV’ aggregator for enabling the smart charging. Further, to circumvent the possibility of damage to the EV battery, real-time Battery Monitoring System (BMS) using less complex and easy to implement Enhanced Coulomb Counting Method for SoC estimation and messaging based MQTT as the communication protocol is presented. The proposed BMS is implemented on hardware platform using appropriate sensing technology, central processor, interfacing devices and the Node-RED environment. The Enhanced Coulomb counting method incorporates self-discharge, temperature dependency and degradation due to aging otherwise absent in popular Coulomb counting method.

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Acknowledgements

This research is aided by Centre of Advanced Research in Electrified Transportation (CARET), Aligarh Muslim University, India sponsored by the grant from Department of Heavy Industries, Govt. of India under FAME Mission.

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Authors and Affiliations

  1. Department of Electrical Engineering, Aligarh Muslim University, Aligarh, India

    Mohammad Asaad, Furkan Ahmad & Mohammad Saad Alam

  2. Department of Mechanical Engineering, Aligarh Muslim University, Aligarh, India

    Yasser Rafat

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  1. Mohammad Asaad
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  2. Furkan Ahmad
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  3. Mohammad Saad Alam
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  4. Yasser Rafat
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Correspondence to Mohammad Asaad.

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Asaad, M., Ahmad, F., Alam, M.S. et al. IoT Enabled Monitoring of an Optimized Electric Vehicle’s Battery System. Mobile Netw Appl 23, 994–1005 (2018). https://doi.org/10.1007/s11036-017-0957-z

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