Discharge, rest and charge simulation of lead-acid batteries using an efficient reduced order model based on proper orthogonal decomposition

Ansari, Amir Babak; Esfahanian, Vahid; Torabi, Farschad

doi:10.1016/j.apenergy.2016.04.008

Cited by 32 publications

(30 citation statements)

References 36 publications

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“…The figure shows that the present simulations have a good consistency with previous numerical and experimental results except at the beginning of the process where the experimental results have a small increase. This behavior is called voltage‐dip ( coup de fouet ) phenomenon, which is not considered in the present models (since it is beyond the scope of the present study and require a complete investigation such as Pascoe and Anbuky, Delaille et al, and Ogunniyi and Pienaar). The figure depicts that the reduced‐order models produce so close results to FVM solution.…”

Section: Resultsmentioning

confidence: 99%

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Reduced‐order modeling of lead‐acid battery using cluster analysis and orthogonal cluster analysis method

Shahbazi

Esfahanian

2019

Int J Energy Res

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Summary Real‐time fast simulation of lead‐acid battery (LAB) plays an important role in monitoring, control, optimization, and many other engineering fields. Hence, any improvement toward a reduction in computational time of LAB simulation while maintaining the accuracy of results is of practical interest. Reduced‐order modeling (ROM) is one of the promising tools, which is computationally cost‐effective along with producing accurate results. In this study, ROM is employed in a transient one‐dimensional simulation of LABs within discharge to investigate the variation of battery parameters, eg, cell voltage, acid concentration, and state of charge (SoC). Accordingly, three reduced‐order models are implemented, namely, proper orthogonal decomposition (POD), cluster analysis (CA), and orthogonal cluster analysis (OCA), wherein the latter one is a new hybrid model of POD and CA methods proposed in the present work. The results reveal that ROM of LAB reduces the simulation time significantly (speed‐up factor about 7‐12) and provide good consistency comparing with previous experimental and numerical studies (less than 1% relative error for cell voltage, acid concentration, and SoC). In addition, the results indicate that the new hybrid method inherits the advantages of both POD and CA methods, ie, enhances the speed of POD method by 8% to 24% and accuracy of CA method by 17% to 65%.

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Section: Resultsmentioning

confidence: 99%

“…They showed that ROM runs orders of magnitude faster than the original CFD model. Recently, Esfahanian et al and Ansari et al solved the LAB governing equation, using POD‐based ROM. They obtained not only accurate results but also a speed‐up factor about 10 to 15 against finite volume method (FVM).…”

Section: Introductionmentioning

confidence: 99%

Reduced‐order modeling of lead‐acid battery using cluster analysis and orthogonal cluster analysis method

Shahbazi

Esfahanian

2019

Int J Energy Res

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“…Multi-scale SoC/SoH judgment based on EIS is an extension of threshold-based management [10,11]; circuits elements are nonlinearly influenced by various factors, e.g., SoC, charging or discharging, superimposed DC current [12]; other form signals, such as short step response, can take place of sinusoidal excitation to demonstrate dominant aging mechanisms on battery capacity [8]. The leading edge of BMS to forecast and optimize batteries' SoC/SoH is usually based on time domain simulation [13,14]; therefore, extracting directional DC charge-transfer resistances from an AC Nyquist curve is significant in time domain research on BMS.…”

Section: Introductionmentioning

confidence: 99%

Directional DC Charge-Transfer Resistance on an Electrode–Electrolyte Interface in an AC Nyquist Curve on Lead-Acid Battery

et al. 2020

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Both the frequency domain Nyquist curve of electrochemical impedance spectroscopy (EIS) and time domain simulation of DC equivalent first principle linear circuit (FPLCDCequ) are some of the fundamentals of lead-acid batteries management system design. The Nyquist curve is used to evaluate batteries’ state of health (SoH), but the curve does not distinguish charging/discharging impedances on electrode–electrolyte interfaces in the frequency domain. FPLCDCequ is used to simulate batteries’ terminal electrical variables, and the circuit distinguishes charging/discharging impedances on electrode–electrolyte interfaces in the time domain. Therefore, there is no direct physical relationship between Nyquist and FPLCDCequ This paper proposes an AC equivalent first principle linear circuit (FPLCACequ) by average switch modeling, and the novel circuit distinguishes charging/discharging impedances on electrode–electrolyte interfaces in Nyquist. The novel circuit establishes a physical bridge between Nyquist and FPLCDCequ for lead-acid batteries management system design.

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“…In 2015, a reduced order model using proper orthogonal decomposition method was presented by Esfahanian et al [15] in order to efficiently simulate a one-dimensional LAB cell. In 2016, Ansari et al [16] developed an efficient reduced order model to accurately simulate a LAB without any simplification, which can be used for real-time monitoring and control purposes.…”

Section: Introductionmentioning

confidence: 99%

Single and multi-objective optimization for the performance enhancement of lead-acid battery cell

Pourmirzaagha

Esfahanian

Sabetghadam

et al. 2016

Int. J. Energy Res.

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SUMMARYElectric energy storage systems are used considerably in industries and daily applications. The demand for batteries with high energy content has increased because of their use in hybrid vehicles. Lead-acid batteries have wide applications because of their advantages such as high safety factor and low cost of production. The major shortcoming of lead-acid batteries is low energy content and high dimension and weight. Nowadays, a common method to increase the energy content of lead-acid battery is the experimental method with trial and error, which is time consuming and expensive. In this paper, non-isothermal one-dimensional numerical simulation of lead-acid battery with finite volume method is performed. In addition, a cell with higher energy content and lower thickness is designed by using particle swarm optimization algorithm based on developed simulation code. The results of single objective optimization show that an optimal battery that has 27.6% higher energy can be made with the same cell dimension. The results also show that an optimum cell battery can be obtained with a decrease of 24% in thickness while keeping the energy the same. Moreover, a multi-objective optimization algorithm is utilized to find Pareto optimal solutions while considering the energy content and thickness objectives simultaneously.

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Discharge, rest and charge simulation of lead-acid batteries using an efficient reduced order model based on proper orthogonal decomposition

Cited by 32 publications

References 36 publications

Reduced‐order modeling of lead‐acid battery using cluster analysis and orthogonal cluster analysis method

Reduced‐order modeling of lead‐acid battery using cluster analysis and orthogonal cluster analysis method

Directional DC Charge-Transfer Resistance on an Electrode–Electrolyte Interface in an AC Nyquist Curve on Lead-Acid Battery

Single and multi-objective optimization for the performance enhancement of lead-acid battery cell

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