AN EVALUATION METHOD OF AN ENERGY CONSUMPTION AS AN OPERATION PARAMETER IN A CYBER-PHYSICAL SYSTEM

Authors

DOI:

https://doi.org/10.37943/18XCMY8200

Keywords:

cyber-physical system, battery management, power consumption, power mode, gain

Abstract

The research of energy consumption in an Internet of Things network and its analytical evaluation is the goal of this work. The authors of this work concentrate on developing a model for calculating the actual gain in power consumption in order to estimate the actual energy required. The method suggests measuring the difference in energy usage under three primary battery-powered working modes to maximize a device's lifetime. Due to the fact that each CPS device state has its own energy metrics, it is feasible to choose the best operation course for entire network. The presented technique is certainly viable, as demonstrated by the experimental examination of Zigbee and BLE devices. The comparison of power levels using a temperature sensor in three basic scenarios (power modes) dictates how the CPS device lifetime can be optimized. Multi-regime consumption models, in which the rates of charging and discharging are dependent upon the energy level, are analyzed in this paper. This work aimed to state an optimal energy consumption by finding the right balance between operational power and battery lifetime through mathematical modeling. Therefore, it is easy to determine the energy cost of power stage, for instance, to send data by setting the minimal duration of each working condition in terms of power consumption. Moreover, a reasonable balance of power consumption and battery lifetime which impacts the data collection from sensors is vital to the development of data extraction algorithms. The practical results depict how device should be accessible to be able to lose less power even during switching on/off or how operate more effective if it used for a short period of time. A long-term network could become a reality once battery life is optimized enough to not disturb a user.

Author Biographies

Kenzhegali Nurgaliyev, L.N. Gumilyov Eurasian National University, Kazakhstan

PhD candidate, Department of Information Systems

Akylbek Tokhmetov, L.N. Gumilyov Eurasian National University, Kazakhstan

Candidate of Physical and Mathematical Sciences, Associate Professor

Department of Information Systems

Liliya Tanchenko, L.N. Gumilyov Eurasian National University, Kazakhstan

Master’s degree, Postdoctoral, Department of Information Systems

References

Verma, M. (2023). Cyber-Physical Systems: Bridging the Digital and Physical Realms for a Smarter Future. Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN, 2456-6470.

Lesch, V., Züfle, M., Bauer, A., Iffländer, L., Krupitzer, C., & Kounev, S. (2023). A literature review of IoT and CPS—What they are, and what they are not. Journal of Systems and Software, 200, 111631.

Shinde, G., Mohapatra, R., Krishan, P., Garg, H., Prabhu, S., Das, S., Masum, M., & Sengupta, S. (2024). The State of Lithium-Ion Battery Health Prognostics in the CPS Era. ArXiv, abs/2403.19816.

Marwedel, P. (2021). Embedded System Design: Embedded Systems Foundations of Cyber-Physical Systems and the Internet of Things. Springer International Publishing, 244-250.

Alharthi, S., Johnson, P., & Randles, M. (2020). Secure and energy-efficient communication in IoT/CPS. Recent Trends in Communication Networks, 205.

Bundalo, Z. V. (2021, November). Energy efficient embedded systems and their application in wireless sensor networks. In IOP Conference Series: Materials Science and Engineering (Vol. 1208, No. 1, p. 012002

Morella, P., Lambán, M. P., Royo, J. A., & Sánchez, J. C. (2021). The importance of implementing cyber physical systems to acquire real-time data and indicators. J-Multidisciplinary Scientific Journal, 4(2), 147-153.

Li, S., & Zhao, P. (2021). Big data driven vehicle battery management method: A novel cyber-physical system perspective. Journal of Energy Storage, 33, 102064.

Liu, W., Placke, T., & Chau, K. T. (2022). Overview of batteries and battery management for electric vehicles. Energy Reports, 8, 4058-4084.

Kim, T., Ochoa, J., Faika, T., Mantooth, H. A., Di, J., Li, Q., & Lee, Y. (2020). An overview of cyber-physical security of battery management systems and adoption of blockchain technology. IEEE Journal of Emerging and Selected Topics in Power Electronics, 10(1), 1270-1281.

Inderwildi, O., Zhang, C., Wang, X., & Kraft, M. (2020). The impact of intelligent cyber-physical systems on the decarbonization of energy. Energy & Environmental Science, 13(3), 744-771.

Panwar, N. G., Singh, S., Garg, A., Gupta, A. K., & Gao, L. (2021). Recent advancements in battery management system for Li‐ion batteries of electric vehicles: future role of digital twin, cyber‐physical systems, battery swapping technology, and nondestructive testing. Energy Technology, 9(8), 2000984.

Singh, A., Feltner, C., Peck, J., & Kuhn, K. I. (2021). Data driven prediction of battery cycle life before capacity degradation. arXiv preprint arXiv:2110.09687.

Sun, B., Pan, J., Wu, Z., Xia, Q., Wang, Z., Ren, Y., & Feng, Q. (2023). Adaptive evolution enhanced physics-informed neural networks for time-variant health prognosis of lithium-ion batteries. Journal of Power Sources, 556, 232432.

Xue, Z., Zhang, Y., Cheng, C., & Ma, G. (2020). Remaining useful life prediction of lithium-ion batteries with adaptive unscented kalman filter and optimized support vector regression. Neurocomputing, 376, 95-102.

Ayevide, F. K., Kelouwani, S., Amamou, A., Kandidayeni, M., & Chaoui, H. (2022). Estimation of a battery electric vehicle output power and remaining driving range under subfreezing conditions. Journal of Energy Storage, 55, 105554.

Kuaban, G. S., Gelenbe, E., Czachórski, T., Czekalski, P., & Tangka, J. K. (2023). Modelling of the energy depletion process and battery depletion attacks for battery-powered internet of things (iot) devices. Sensors, 23(13), 6183.

Kovilpillai, J. J. A., & Jayanthy, S. (2022). Parameter Analysis in a Cyber-Physical System. In Pervasive Computing and Social Networking: Proceedings of ICPCSN 2021, 361-371. Springer Singapore.

Nurgaliyev, K., Tokhmetov, A., & Tanchenko, L. (2023). An analysis of the heterogeneous IoT device network interaction in a cyber-physical system. Scientific Journal of Astana IT University, 16(16).

Akbarzadeh, A., & Katsikas, S. (2020, June). Identifying critical components in large scale cyber physical systems. In Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops, 230-236.

Agostinelli, S., Cumo, F., Guidi, G., & Tomazzoli, C. (2021). Cyber-physical systems improving building energy management: Digital twin and artificial intelligence. Energies, 14(8), 2338.

Park, J., Bhat, G., Nk, A., Geyik, C. S., Ogras, U. Y., & Lee, H. G. (2020). Energy per operation optimization for energy harvesting wearable IoT devices. Sensors, 20(3), 764.

Chetoui, S., & Reda, S. (2021, February). Workload-and user-aware battery lifetime management for mobile socs. In 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE), 1679-1684.

Li, S., He, H., & Zhao, P. (2021). Energy management for hybrid energy storage system in electric vehicle: A cyber-physical system perspective. Energy, 230, 120890.

Hosseinzadeh, E., Arias, S., Krishna, M., Worwood, D., Barai, A., Widanalage, D., & Marco, J. (2021). Quantifying cell-to-cell variations of a parallel battery module for different pack configurations. Applied Energy, 282, 115859.

Hortelano, D., Olivares, T., & Ruiz, M. C. (2021). Reducing the energy consumption of the friendship mechanism in Bluetooth mesh. Computer Networks, 195, 108172.

Yin, J. (2022). Ultra-Low Power Zigbee/BLE Transmitter for IoT Applications. In Selected Topics in Power, RF, and Mixed-Signal ICs, 315-337.

Downloads

Published

2024-06-30

How to Cite

Nurgaliyev, . K., Tokhmetov, A., & Tanchenko, L. (2024). AN EVALUATION METHOD OF AN ENERGY CONSUMPTION AS AN OPERATION PARAMETER IN A CYBER-PHYSICAL SYSTEM. Scientific Journal of Astana IT University, 18, 30–40. https://doi.org/10.37943/18XCMY8200

Issue

Section

Information Technologies
betpas
pendik escort anadolu yakasi escort bostanci escort kadikoy escort kartal escort kurtkoy escort umraniye escort
maltepe escort ataşehir escort ataşehir escort ümraniye escort pendik escort kurtköy escort anadolu yakası escort üsküdar escort şerifali escort kartal escort gebze escort kadıköy escort bostancı escort göztepe escort kadıköy escort bostancı escort üsküdar escort ataşehir escort maltepe escort kurtköy escort anadolu yakası escort ataşehir escort beylikdüzü escort