Advanced Battery Management &amp; diagnostic system for smart grid infrastructure

Elsayed, Ahmed T.; Lashway, Christopher R.; Mohammed, Osama A.

doi:10.1109/pesgm.2016.7741171

Cited by 19 publications

(19 citation statements)

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“…One of the reasons for the high price of battery modules is that their electrochemical properties are difficult to grasp. Nowadays, battery-related research, in addition to materials and electrochemical fields, generally includes monitoring of battery characteristics [1][2][3][4][5][6][7][8][9][10], design of battery management systems [11][12][13][14], estimation of state of charge [15][16][17][18][19][20], estimation of state of health [21][22][23][24][25][26], and so on.…”

Section: Introductionmentioning

confidence: 99%

“…First, the voltage, current, and temperature of all battery cells need to be detected and made sure to be normal. The second part concerns SOC/SOH, which are two critical performance indicators of batteries; many estimation techniques have been proposed in [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26] for SOC/SOH. Battery diagnostic techniques can also be combined with chargers, battery analyzers, or monitoring equipment, and suitable diagnostic algorithms and interfaces can be applied according to the type of battery to fully to grasp the electrical characteristics of the battery.Recently it has been recognized that in order to obtain dynamic characteristics for calculating the SOC/SOH of a power battery and to recycle the extracted electrical energy from a tested power battery, a programmable AC electronic load is essential to emulate a variety of dynamic load behaviors, and sequence control is also required [27][28][29][30].…”

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confidence: 99%

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A Low-Cost Programmable High-Frequency AC Electronic Load with Energy Recycling for Battery Module Diagnostics

et al. 2020

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A low-cost programmable high-frequency alternating current (AC) electronic load for battery module diagnosis which possesses energy recycling and portability is proposed. The proposed AC electronic load consists of a micro-controller, a signal capturing circuit, and a resonant circuit, and can be integrated with a human–machine interface (HMI). To diagnose the dynamic characteristics of a lithium battery module, the proposed AC electronic load is served as a test load for providing a wide-range slew-rate loading function. In this study, the extracted energy from the tested battery module during the diagnostic process can be recycled to save energy. In addition, all of the battery module parameters and test conditions can be preset in the HMI, and the battery characteristics and the recycling rate of the electrical energy also can be estimated. Analysis of operation modes and simulations and some experimental results are used to verify the theoretical predictions.

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Section: Introductionmentioning

confidence: 99%

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confidence: 99%

A Low-Cost Programmable High-Frequency AC Electronic Load with Energy Recycling for Battery Module Diagnostics

et al. 2020

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“…25 Furthermore, the polynomial equivalent circuit model was constructed 26 for the electrochemical impedance spectroscopy of the lithium-ion batteries. 35 Moreover, the maximum available power state estimation was conducted by using the Particle-filtering (PF) algorithm 36 and it was also achieved by using the temperature-compensated model. 27 The related research work was concentrated on the energy transferring consumption policies 28 and the SOC determination methods were analyzed.…”

Section: Introductionmentioning

confidence: 99%

“…33 The iterate calculation was obtained by conducting the evolutionary Gaussian mixture regression 34 and the advanced BMS equipment was designed for the smart grid infrastructure. 35 Moreover, the maximum available power state estimation was conducted by using the Particle-filtering (PF) algorithm 36 and it was also achieved by using the temperature-compensated model. 37 The SOC estimation method was obtained for a latent heat storage 38 and a neural network-based observer was designed.…”

Section: Introductionmentioning

confidence: 99%

An improved packing equivalent circuit modeling method with the cell‐to‐cell consistency state evaluation of the internal connected lithium‐ion batteries

Wang

Shi

Fernandez

et al. 2019

Energy Science & Engineering

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The existing equivalent modeling methods reported in literature focuses mainly on the battery cells and do not take the packing consistency state into consideration, which exists on the internal connected cells of the lithium‐ion battery pack. An improved equivalent circuit model is constructed and reported in this manuscript for the first time, which can be used to characterize the working characteristics of the packing lithium‐ion batteries. A new equilibrium concept named as state of balance is proposed as well as the calculation process, which is realized by considering the real‐time detected internal battery cell voltages. In addition, this new equilibrium concept aims to obtain more information on the real‐time consistency characterization of the battery pack. The improved adaptive equivalent circuit model is investigated by using the improved splice modeling method, in which the statistical noise properties are corrected and the additional parallel resistance‐capacitance circuit is introduced. The parameter correction treatment is carried out by comparing the estimated and experimental detected closed circuit voltages. Furthermore, the tracking error is found to be 0.005 V and accounts for 0.119% of the nominal battery voltage. By taking the packing consistency state and temperature correction into consideration, the accurate working characteristic expression is realized in the improved equivalent circuit modeling process. Finally, the model proposed in this manuscript presents a great number of advantages compared to other methods reported so far, like has the high accuracy, and the ability to protect the security of the lithium‐ion battery pack in the power supply application.

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“…An innovative data-driven approach using an experimental dataset to predict the SOC by using support vector regression (SVR) to indicate good performance has been proposed in [22]. An advanced BMS system will monitor individual batteries inside a series configuration and identify the independent voltages and current contributions as well as the SOC levels of each battery [23]. An improved and fault tolerant voltage measurement for battery management systems has been introduced in [24].…”

Section: Introductionmentioning

confidence: 99%

Performance Analysis of Energy Storage in Smart Microgrid Based on Historical Data of Individual Battery Temperature and Voltage Changes

Haq

Kurniadi

Leksono

et al. 2019

J. Eng. Technol. Sci.

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In this work, a historical data based battery management system (BMS) was successfully developed and implemented using an embedded system for condition monitoring of a battery energy storage system in a smart microgrid. The performance was assessed for 28 days of operating time with a one-minute sampling time. The historical data showed that the maximum temperature increment and the maximum temperature difference between the batteries were 4.5 °C and 2.8 °C. One of the batteries had a high voltage rate of change, i.e. above 3.0 V/min, and its temperature rate of change was very sensitive, even at low voltage rate of changes. This phenomenon tends to indicate problems that may deplete the battery energy storage system's total capacity. The primary findings of this study are that the voltage and temperature rates of change of individual batteries in real operating conditions can be used to diagnose and foresee imminent failure, and in the event of a failure occurring the root cause of the problem can be found by using the historical data based BMS. To ensure further safety and reliability of acceptable practical operating conditions, rate of change limits are proposed based on battery characteristics for temperatures below 0.5 °C/min and voltages below 3.0 V/min.

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Advanced Battery Management & diagnostic system for smart grid infrastructure

Cited by 19 publications

References 0 publications

A Low-Cost Programmable High-Frequency AC Electronic Load with Energy Recycling for Battery Module Diagnostics

A Low-Cost Programmable High-Frequency AC Electronic Load with Energy Recycling for Battery Module Diagnostics

An improved packing equivalent circuit modeling method with the cell‐to‐cell consistency state evaluation of the internal connected lithium‐ion batteries

Performance Analysis of Energy Storage in Smart Microgrid Based on Historical Data of Individual Battery Temperature and Voltage Changes

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