An Energy Efficient Battery Management System using Pulse Width Modulation and Maximum Power Point Tracking

International Journal of Electrical and Electronics Engineering

© 2023 by SSRG - IJEEE Journal

Volume 10 Issue 8

Year of Publication : 2023

Authors : Jenifer Labi Labence, Radhika Sivashanmugam

10.14445/23488379/IJEEE-V10I8P118

How to Cite?

Jenifer Labi Labence, Radhika Sivashanmugam, "An Energy Efficient Battery Management System using Pulse Width Modulation and Maximum Power Point Tracking," SSRG International Journal of Electrical and Electronics Engineering, vol. 10,  no. 8, pp. 185-194, 2023. Crossref, https://doi.org/10.14445/23488379/IJEEE-V10I8P118

Abstract:

In a recent invention, a Wireless Sensor Networking (WSN) node with low energy is given access to solar energy harvesting as an alternative power source. The industrialised nations conducting research can offer these solutions for issues with sustainable energy producers, like China, Finland, Mexico, the United States, and others. The WSN nodes can be rendered entirely autonomous using an indefinite network lifespan by utilizing rechargeable batteries, low-power energy harvester circuits, tiny solar panels, and low-power energy harvester control systems. The performance of one or more battery modules can be tracked, managed, and optimized, which is a crucial component of electric garage equipment. Another opportunity is knowing how to take one or more modules out of the device in case of a malfunction. The BMS, which is named for this management approach, is one of the crucial components of electrical equipment. A BMS’s primary function is to keep a battery within a safe operating range of voltage, current, and temperature when charged, discharged, or in certain situations, even when an open circuit is present. Both internal and external events have an impact on the BMS. The automatic detection of COVID-19 patients using DCNN with X-ray imaging was discussed. This study uses a novel technique to identify COVID-19 from X-ray pictures automatically. It has been suggested to take untreated chest radiographs. The suggested approach is made to offer precise detection in instances including both binary and multiclass classification. Pulse Width Modulation (PWM) and peak energy factor tracking (MPPT) are technologies developed to boost PV system performance. In this regard, a combinatorial MPPT method based on SEH-WSN node modelling is described in this study.

Keywords:

Active balancers, MPPT controller, Passive balancers, Solar energy harvesting, Wireless sensor networking node.

References:

[1] Burak Tarhan, Ozge Yetik, and Tahir Hikmet Karakoc, “Hybrid Battery Management System Design for Electric Aircraft,” Energy, vol. 234, p. 121227, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[2] Ahilan A, and Deepa P, “Modified Decimal Matrix Codes in FPGA Configuration Memory for Multiple Bit Upsets,” 2015 International Conference on Computer Communication and Informatics (ICCCI), Coimbatore, India, pp. 1-5, 2015.
[CrossRef] [Google Scholar] [Publisher Link]
[3] A. Karthikeyan et al., “Automata Theory-Based Energy Efficient Area Algorithm for an Optimal Solution in Wireless Sensor Networks,” Wireless Personal Communications, vol. 120, pp. 1125-1143, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[4] CH. Mounica et al., “A Brief Overview about Energy-Aware, Location-Specific, and Topology Adjustment Routing Protocols for Wireless Sensor Networks,” International Journal of P2P Network Trends and Technology, vol. 5, no. 2, pp. 21-27, 2015.
[CrossRef] [Publisher Link]
[5] P. Maxmillon, and R. Franklin, “A Review on Authentication and Security Maintenance in Wireless Sensor Network,” SSRG International Journal of Mobile Computing and Application, vol. 3, no. 2, pp. 10-13, 2016.
[CrossRef] [Publisher Link]
[6] A. Karthikeyan, V. P. Arunachalam, and S. Karthik, “Attempting to Model A Fresh Three-Dimensional Coverage Scheme for Wireless Sensor Networks,” Wireless Personal Communications, vol. 110, pp. 847-859, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[7] Prasad Reddy, “Programmable Wireless Sensor Network for Industrial Automation and Environmental Safety,” SSRG International Journal of Industrial Engineering, vol. 1, no. 1, pp. 4-6, 2014.
[CrossRef] [Publisher Link]
[8] M. Supriya, and T. Adilakshmi, “Secure Routing using ISMO for Wireless Sensor Networks,” SSRG International Journal of Computer Science and Engineering, vol. 8, no. 12, pp. 14-20, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[9] Mohd Rizuan Baharon et al., “An Improved Fully Homomorphic Encryption Scheme for Cloud Computing,” International Journal of Communiation Networks Information Security, vol. 10, no. 3, pp. 502-508, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Giacomo Peruzzi, and Alessandro Pozzebon, “A Review of Energy Harvesting Techniques for Low Power Wide Area Networks (LPWANs),” Energies, vol. 13, no. 13, pp. 1-24, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[11] Hossam A. Gabbar, Ahmed M. Othman, and Muhammad R. Abdussami, “Review of Battery Management Systems (BMS) Development and Industrial Standards,” Technologies, vol. 9, no. 2, pp. 1-23, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Abdelrahman O. Ali et al., “Energy Management of Photovoltaic-Battery System Connected with the Grid,” Journal of Energy Storage, vol. 55, part D, p. 105865, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[13] Kotb M. Kotb et al., “Enriching the Stability of Solar/Wind DC Microgrids using Battery and Superconducting Magnetic Energy Storage Based Fuzzy Logic Control,” Journal of Energy Storage, vol. 45, p. 103751, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[14] S. Arun et al., “An Autonomous Solar PV System using Boost TPC for Energy Harvesting with Mode-Based Power Flow Management Control,” Sustainable Energy Technologies and Assessments, vol. 53, part B, p. 102528, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[15] Leandro L. O. Carralero et al., “An Isolated Standalone Photovoltaic-Battery System for Remote Areas Applications,” Journal of Energy Storage, vol. 55, part B, p. 105568, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[16] Nabil Mohammed, and Ahmed Majed Saif, “Programmable Logic Controller-Based Lithium-Ion Battery Management System for Accurate State of Charge Estimation,” Computers & Electrical Engineering, vol. 93, p. 107306, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[17] Farrukh Sayeed et al., “A Novel and Comprehensive Mechanism for the Energy Management of a Hybrid Micro-Grid System,” Energy Reports, vol. 8, pp. 847-862, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[18] P. Sathish Kumar et al., “Energy Management System for Small Scale Hybrid Wind-Solar Battery-Based Microgrid,” IEEE Access, vol. 8, pp. 8336-8345, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[19] Andrea Trovò, and Massimo Guarnieri, “Battery Management Systems for Redox Flow Batteries and Controllers for Fuel Cells,” Encyclopedia of Energy Storage, vol. 2, pp. 557-567, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[20] Sivasankar Gangatharan et al., “A Novel Battery Supported Energy Management System for the Effective Handling of Feeble Power in Hybrid Microgrid Environment,” IEEE Access, vol. 8, pp. 217391-217415, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[21] Yaze Li, and Jingxian Wu, “Optimum Integration of Solar Energy with Battery Energy Storage Systems,” IEEE Transactions on Engineering Management, vol. 69, no. 3, pp. 697-707, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[22] Priyanka Kishor Sorte, Kaibalya Prasad Panda, and Gayadhar Panda, “Current Reference Control Based MPPT and Investigation of Power Management Algorithm for Grid-Tied Solar PV-Battery System,” IEEE Systems Journal, vol. 16, no. 1, pp. 386-396, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[23] Ahmed Sayed Abdelaal, Shayok Mukhopadhyay, and Habibur Rehman, “Battery Energy Management Techniques for an Electric Vehicle Traction System,” IEEE Access, vol. 10, pp. 84015-84037, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[24] Mahdi Rouholamini et al., “A Review of Modeling, Management, and Applications of Grid Connected Li-ion Battery Storage Systems,” IEEE Transactions on Smart Grid, vol. 13, no. 6, pp. 4505-4524, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[25] Haakon Karlsen et al., “Temperature-Dependence in Battery Management Systems for Electric Vehicles: Challenges, Criteria, and Solutions,” IEEE Access, vol. 7, pp. 142203-142213, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[26] Rui Xiong et al., “Lithium-Ion Battery Health Prognosis Based on a Real Battery Management System used in Electric Vehicles,” IEEE Transactions on Vehicular Technology, vol. 68, no. 5, pp. 4110-4121, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[27] Shahid A. Hasib et al., “A Comprehensive Review of Available Battery Datasets, RUL Prediction Approaches, and Advanced Battery Management,” IEEE Access, vol. 9, pp. 86166-86193, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[28] Kiran Liaqat, Zubair Rehman, and Iftikhar Ahmad, “Nonlinear Controllers for Fuel Cell, Photovoltaic Cell and Battery-Based Hybrid Energy Management System,” Journal of Energy Storage, vol. 32, p. 101796, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[29] Arturo Conde et al., “Frequency Improvement in Microgrids through Battery Management System Control Supported by a Remedial Action Scheme,” IEEE Access, vol. 10, pp. 8081-8091, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[30] Giovane Ronei Sylvestrin, Helton Fernando Scherer, and Oswaldo Hideo Ando Junior, “Hardware and Software Development of an Open-Source Battery Management System,” IEEE Latin America Transactions, vol. 19, no. 7, pp. 1153-1163, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[31] Al-wesabi Ibrahim et al., “PV Maximum Power-Point Tracking using Modified Particle Swarm Optimization under Partial Shading Conditions,” Chinese Journal of Electrical Engineering, vol. 6, no. 4, pp. 106-121, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[32] Mohammad Al-Soeidat, Dylan Dah-Chuan Lu, and Jianguo Zhu, “An Analog BJT-Tuned Maximum Power Point Tracking Technique for PV Systems,” IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 66, no. 4, pp. 637-641, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[33] Menaga D, and Sankaranarayanan V, “Robust Nonlinear Controller Design for Optimized Battery Performance in the PhotovoltaicBattery Tied Hybrid System using Sliding Mode Control,” European Journal of Control, vol. 65, p. 100636, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[34] Ibrahim Saiful Millah et al., “Investigation of Maximum Power Point Tracking of Different Kinds of Solar Panels under Partial Shading Conditions,” IEEE Transactions on Industry Applications, vol. 57, no. 1, pp. 17-25, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[35] Shichun Yang et al., “Implementation for a Cloud Battery Management System Based on the Chain Framework,” Energy and AI, vol. 5, p. 100088, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[36] M. S. Hossain Lipu et al., “Intelligent Algorithms and Control Strategies for Battery Management System in Electric Vehicles: Progress, Challenges and Future Outlook,” Journal of Cleaner Production, vol. 292, p. 126044, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[37] Hongqian Wei et al., “Design and Validation of a Battery Management System for Solar-Assisted Electric Vehicles,” Journal of Power Sources, vol. 513, p. 230531, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[38] Kalimuthukumar Sakthivel et al., “A Revolutionary Partial Resonant Inverter and Doubler Rectifier with MPPT Based on Sliding Mode Controller for Harvesting Solar Photovoltaic Sources,” Sustainable Computing: Informatics and Systems, vol. 36, p. 100811, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[39] Abdallah Aldosary et al., “A Modified Shuffled Frog Algorithm to Improve MPPT Controller in PV System with Storage Batteries under Variable Atmospheric Conditions,” Control Engineering Practice, vol. 112, p. 104831, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[40] Lipsa Priyadarshini, P. K. Dash, and Snehamoy Dhar, “A New Exponentially Expanded Robust Random Vector Functional Link Network Based MPPT Model for Local Energy Management of PV-Battery Energy Storage Integrated Microgrid,” Engineering Applications of Artificial Intelligence, vol. 91, p. 103633, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[41] R. Zahedi, and M. M. Ardehali, “Power Management for Storage Mechanisms Including Battery, Supercapacitor, and Hydrogen of Autonomous Hybrid Green Power System Utilizing Multiple Optimally-Designed Fuzzy Logic Controllers,” Energy, vol. 204, p. 117935, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[42] Sandeep Bishla, and Anita Khosla, “Enhanced Chimp Optimized Self-Tuned FOPR Controller for Battery Scheduling using Grid and Solar PV Sources,” Journal of Energy Storage, vol. 66, p. 107403, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[43] Preetam Kodam et al., “Wireless Sensors Network Based Energy Management System,” International Journal of P2P Network Trends and Technology, vol. 17, pp. 18-20, 2015.
[CrossRef] [Publisher Link]
[44] Sadasiva Behera, and Nalin B. Dev Choudhury, “Modelling and Simulations of Modified Slime Mould Algorithm Based on Fuzzy PID to Design an Optimal Battery Management System in Microgrid,” Cleaner Energy Systems, vol. 3, p. 100029, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[45] Kubra Nur Akpinar et al., “An Intelligent Power Management Controller for Grid-Connected Battery Energy Storage Systems for Frequency Response Service: A Battery Cycle Life Approach,” Electric Power Systems Research, vol. 216, p. 109040, 2023.
[CrossRef] [Google Scholar] [Publisher Link]