Simulation of lead-acid battery using model order reduction

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

doi:10.1016/j.jpowsour.2014.12.149

Cited by 30 publications

(20 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…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%

“…In order to have a complete problem, initial conditions should be specified. The acid concentration at the beginning of the process is

c false(x, t = 0 false) = c_{0},

and the initial condition for solid and liquid potentials should be obtained by solving the elliptic system of Equations (3) and …”

Section: Theorymentioning

confidence: 99%

“…As it can be seen from Equation , the BCs of the solid potential equation in the constant current condition are Neumann or second‐type. Due to the ellipticity of potential equations and BCs of Neumann type, the compatibility condition should be applied in numerical simulation to have a well‐posed problem . In order to apply the compatibility condition, Newton‐Raphson (or secant) iterative method can be employed as shown in the algorithm of Figure .…”

Section: Numerical Proceduresmentioning

confidence: 99%

“…As it can be seen from Equation (10) problem. 42,45 In order to apply the compatibility condition, Newton-Raphson (or secant) iterative method can be employed as shown in the algorithm of Figure 4. In this way, the constant voltage BCs is set as ϕ s (t,L)=ϕ s, R =0 and ϕ s (t,0)=ϕ s,L and the value of ϕ s,L is corrected using Newton-Raphson method.…”

Section: Numerical Proceduresmentioning

confidence: 99%

See 3 more Smart Citations

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

Shahbazi

Esfahanian

2019

Int J Energy Res

Self Cite

View full text Add to dashboard Cite

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%.

show abstract

Section: Resultsmentioning

confidence: 99%

“…In order to have a complete problem, initial conditions should be specified. The acid concentration at the beginning of the process is

c false(x, t = 0 false) = c_{0},

and the initial condition for solid and liquid potentials should be obtained by solving the elliptic system of Equations (3) and …”

Section: Theorymentioning

confidence: 99%

Section: Numerical Proceduresmentioning

confidence: 99%

Section: Numerical Proceduresmentioning

confidence: 99%

See 2 more Smart Citations

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

Shahbazi

Esfahanian

2019

Int J Energy Res

Self Cite

View full text Add to dashboard Cite

show abstract

“…In 2014, Esfahanian et al [14] simulated a LAB in a one-dimensional model using the CFD commercial software package FLUENT in order to parametric study. 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.

Self Cite

View full text Add to dashboard Cite

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.

show abstract