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Journal ArticleDOI

Reliable and Robust Observer for Simultaneously Estimating State-of-Charge and State-of-Health of LiFePO4 Batteries

TL;DR: A reliable and robust observer is proposed which could estimate the SOC and SOH of LiFePO4 batteries simultaneously with high accuracy rates and the designed observer was proved by simulating ill-conditions that involve wrong initial estimates and wrong model parameters.
Abstract: Batteries are everywhere, in all forms of transportation, electronics, and constitute a method to store clean energy. Among the diverse types available, the lithium-iron-phosphate (LiFePO4) battery stands out for its common usage in many applications. For the battery’s safe operation, the state of charge (SOC) and state of health (SOH) estimations are essential. Therefore, a reliable and robust observer is proposed in this paper which could estimate the SOC and SOH of LiFePO4 batteries simultaneously with high accuracy rates. For this purpose, a battery model was developed by establishing an equivalent-circuit model with the ambient temperature and the current as inputs, while the measured output was adopted to be the voltage where current and terminal voltage sensors are utilized. Another vital contribution is formulating a comprehensive model that combines three parts: a thermal model, an electrical model, and an aging model. To ensure high accuracy rates of the proposed observer, we adopt the use of the dual extend Kalman filter (DEKF) for the SOC and SOH estimation of LiFePO4 batteries. To test the effectiveness of the proposed observer, various simulations and test cases were performed where the construction of the battery system and the simulation were done using MATLAB. The findings confirm that the best observer was a voltage-temperature (VT) observer, which could observe SOC accurately with great robustness, while an open-loop observer was used to observe the SOH. Furthermore, the robustness of the designed observer was proved by simulating ill-conditions that involve wrong initial estimates and wrong model parameters. The results demonstrate the reliability and robustness of the proposed observer for simultaneously estimating the SOC and SOH of LiFePO4 batteries.
Citations
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Journal ArticleDOI
TL;DR: The enhanced operation and control of DC microgrid systems, which are based on photovoltaic modules, battery storage systems, and DC load, are presented and it is illustrated that the grid-tied mode of operation regulated by voltage source converter control offers more stability than the islanded mode.
Abstract: Recently, the penetration of energy storage systems and photovoltaics has been significantly expanded worldwide. In this regard, this paper presents the enhanced operation and control of DC microgrid systems, which are based on photovoltaic modules, battery storage systems, and DC load. DC–DC and DC–AC converters are coordinated and controlled to achieve DC voltage stability in the microgrid. To achieve such an ambitious target, the system is widely operated in two different modes: stand-alone and grid-connected modes. The novel control strategy enables maximum power generation from the photovoltaic system across different techniques for operating the microgrid. Six different cases are simulated and analyzed using the MATLAB/Simulink platform while varying irradiance levels and consequently varying photovoltaic generation. The proposed system achieves voltage and power stability at different load demands. It is illustrated that the grid-tied mode of operation regulated by voltage source converter control offers more stability than the islanded mode. In general, the proposed battery converter control introduces a stable operation and regulated DC voltage but with few voltage spikes. The merit of the integrated DC microgrid with batteries is to attain further flexibility and reliability through balancing power demand and generation. The simulation results also show the system can operate properly in normal or abnormal cases, thanks to the proposed control strategy, which can regulate the voltage stability of the DC bus in the microgrid with energy storage systems and photovoltaics.

45 citations

Journal ArticleDOI
TL;DR: In this paper , a new intelligent integration between an IoT platform and deep learning neural network (DNN) algorithm for the online monitoring of computer numerical control (CNC) machines is introduced.
Abstract: This paper introduces a new intelligent integration between an IoT platform and deep learning neural network (DNN) algorithm for the online monitoring of computer numerical control (CNC) machines. The proposed infrastructure is utilized for monitoring the cutting process while maintaining the cutting stability of CNC machines in order to ensure effective cutting processes that can help to increase the quality of products. For this purpose, a force sensor is installed in the milling CNC machine center to measure the vibration conditions. Accordingly, an IoT architecture is designed to connect the sensor node and the cloud server to capture the real-time machine’s status via message queue telemetry transport (MQTT) protocol. To classify the different cutting conditions (i.e., stable cutting and unstable cuttings), an improved model of DNN is designed in order to maintain the healthy state of the CNC machine. As a result, the developed deep learning can accurately investigate if the transmitted data of the smart sensor via the internet is real cutting data or fake data caused by cyber-attacks or the inefficient reading of the sensor due to the environment temperature, humidity, and noise signals. The outstanding results are obtained from the proposed approach indicating that deep learning can outperform other traditional machine learning methods for vibration control. The Contact elements for IoT are utilized to display the cutting information on a graphical dashboard and monitor the cutting process in real-time. Experimental verifications are performed to conduct different cutting conditions of slot milling while implementing the proposed deep machine learning and IoT-based monitoring system. Diverse scenarios are presented to verify the effectiveness of the developed system, where it can disconnect immediately to secure the system automatically when detecting the cyber-attack and switch to the backup broker to continue the runtime operation.

43 citations

Journal ArticleDOI
TL;DR: A new intelligent integration between an IoT platform and deep learning neural network (DNN) algorithm for the online monitoring of computer numerical control (CNC) machines is introduced, indicating that deep learning can outperform other traditional machine learning methods for vibration control.
Abstract: This paper introduces a new intelligent integration between an IoT platform and deep learning neural network (DNN) algorithm for the online monitoring of computer numerical control (CNC) machines. The proposed infrastructure is utilized for monitoring the cutting process while maintaining the cutting stability of CNC machines in order to ensure effective cutting processes that can help to increase the quality of products. For this purpose, a force sensor is installed in the milling CNC machine center to measure the vibration conditions. Accordingly, an IoT architecture is designed to connect the sensor node and the cloud server to capture the real-time machine’s status via message queue telemetry transport (MQTT) protocol. To classify the different cutting conditions (i.e., stable cutting and unstable cuttings), an improved model of DNN is designed in order to maintain the healthy state of the CNC machine. As a result, the developed deep learning can accurately investigate if the transmitted data of the smart sensor via the internet is real cutting data or fake data caused by cyber-attacks or the inefficient reading of the sensor due to the environment temperature, humidity, and noise signals. The outstanding results are obtained from the proposed approach indicating that deep learning can outperform other traditional machine learning methods for vibration control. The Contact elements for IoT are utilized to display the cutting information on a graphical dashboard and monitor the cutting process in real-time. Experimental verifications are performed to conduct different cutting conditions of slot milling while implementing the proposed deep machine learning and IoT-based monitoring system. Diverse scenarios are presented to verify the effectiveness of the developed system, where it can disconnect immediately to secure the system automatically when detecting the cyber-attack and switch to the backup broker to continue the runtime operation.

36 citations

Journal ArticleDOI
TL;DR: In this paper , the authors present a recent review supported by a statistical analysis about the current situation in Egypt according to the last data carried out from local/global reports, and discuss specifications of technical design standards, terms, and equipment parameters for connecting small, medium, and large-scale solar plants, respectively to the Egyptian grid in accordance with the Electricity Distribution Code (EDC), Solar Energy Grid Connection Code (SEGCC), and the Grid Code (GC).
Abstract: The development of the energy sector in Egypt is considered an urgent issue due to the rapid population rise rate. In particular, renewable energy sources (RESs) applications play an essential role in the coverage of energy demand. Therefore, Egypt has ambitious plans towards RESs to combine a sustainable energy future with economic growth. Egypt has high potentiality for RESs and their applications, nevertheless, the study of this modality remains below the required level. Due to the widespread use of RESs, communities are facing stability issues as the power converters-based RESs create a significant lack of power inertia, causing system instability and power blackouts as well as issues of power quality such as harmonics or resonances due to the power converters and their interactions with the system. This work presents a recent review supported by a statistical analysis about the current situation in Egypt according to the last data carried out from local/global reports. In addition, this review discusses specifications of technical design standards, terms, and equipment parameters for connecting small, medium, and large-scale solar plants, respectively to the Egyptian grid in accordance with the Electricity Distribution Code (EDC), Solar Energy Grid Connection Code (SEGCC), and the Grid Code (GC). Interestingly, the use of hydropower and emergent solar energy is considered the most promising RES variant, besides the wind energy at the coastal sites. This review characterizes the progress in Egypt and classifies interest areas for RESs recent study, e.g., photovoltaic (PV), solar chimney (SC), concentrated solar plant (CSP), and wind energy in Egypt. To maximize the RES hosting capacity in Egypt, various energy storage systems are required to be integrated into the distribution networks. Finally, a view of existing gaps, future visions and projects, and visible recommendations are defined for the Egyptian grid.

29 citations

Journal ArticleDOI
TL;DR: In this article , the authors present a recent review supported by a statistical analysis about the current situation in Egypt according to the last data carried out from local/global reports, and discuss specifications of technical design standards, terms, and equipment parameters for connecting small, medium, and large-scale solar plants, respectively to the Egyptian grid in accordance with the Electricity Distribution Code (EDC), Solar Energy Grid Connection Code (SEGCC), and the Grid Code (GC).
Abstract: The development of the energy sector in Egypt is considered an urgent issue due to the rapid population rise rate. In particular, renewable energy sources (RESs) applications play an essential role in the coverage of energy demand. Therefore, Egypt has ambitious plans towards RESs to combine a sustainable energy future with economic growth. Egypt has high potentiality for RESs and their applications, nevertheless, the study of this modality remains below the required level. Due to the widespread use of RESs, communities are facing stability issues as the power converters-based RESs create a significant lack of power inertia, causing system instability and power blackouts as well as issues of power quality such as harmonics or resonances due to the power converters and their interactions with the system. This work presents a recent review supported by a statistical analysis about the current situation in Egypt according to the last data carried out from local/global reports. In addition, this review discusses specifications of technical design standards, terms, and equipment parameters for connecting small, medium, and large-scale solar plants, respectively to the Egyptian grid in accordance with the Electricity Distribution Code (EDC), Solar Energy Grid Connection Code (SEGCC), and the Grid Code (GC). Interestingly, the use of hydropower and emergent solar energy is considered the most promising RES variant, besides the wind energy at the coastal sites. This review characterizes the progress in Egypt and classifies interest areas for RESs recent study, e.g., photovoltaic (PV), solar chimney (SC), concentrated solar plant (CSP), and wind energy in Egypt. To maximize the RES hosting capacity in Egypt, various energy storage systems are required to be integrated into the distribution networks. Finally, a view of existing gaps, future visions and projects, and visible recommendations are defined for the Egyptian grid.

29 citations

References
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TL;DR: In this article, extended Kalman filtering (EKF) is used to estimate battery state-of-charge, power fade, capacity fade, and instantaneous available power for hybrid-electric-vehicle battery packs.

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TL;DR: In this paper, an extended Kalman filter (EKF) was proposed to estimate the battery state of charge, power fade, capacity fade, and instantaneous available power of a hybrid-electric-vehicle battery pack.

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TL;DR: In this paper, the methods for monitoring the battery state of charge, capacity, impedance parameters, available power, state of health, and remaining useful life are reviewed with the focus on elaboration of their strengths and weaknesses for the use in on-line BMS applications.

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Journal ArticleDOI
TL;DR: This paper proposes an innovative approach to devising optimally health-conscious fast-safe charge protocols using the Legendre–Gauss–Radau pseudospectral method with adaptive multi-mesh-interval collocation to solve the resulting highly nonlinear six-state optimal control problem.
Abstract: Fast and safe charging protocols are crucial for enhancing the practicality of batteries, especially for mobile applications, such as smartphones and electric vehicles. This paper proposes an innovative approach to devising optimally health-conscious fast-safe charge protocols. A multiobjective optimal control problem is mathematically formulated via a coupled electro-thermal-aging battery model, where electrical and aging submodels depend upon the core temperature captured by a two-state thermal submodel. The Legendre–Gauss–Radau pseudospectral method with adaptive multi-mesh-interval collocation is employed to solve the resulting highly nonlinear six-state optimal control problem. Charge time and health degradation are, therefore, optimally traded off, subject to both electrical and thermal constraints. Minimum-time, minimum-aging, and balanced charge scenarios are examined in detail. Sensitivities to the upper voltage bound, ambient temperature, and cooling convection resistance are investigated as well. Experimental results are provided to compare the tradeoffs between a balanced and traditional charge protocol.

208 citations