A novel approach for electrical circuit modeling of Li-ion battery for predicting the steady-state and dynamic I–V characteristics

Saxena, Saurabh; Raman, S. Raghu; Saritha, B.

doi:10.1007/s12046-016-0486-7

Cited by 18 publications

(22 citation statements)

References 25 publications

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“…The aforementioned mathematical and electrochemical models are based on the highlevel representation of the battery with analytic expressions based on physical laws. Conse-quently, these models are computationally complex and tailored to predict only individual behavioural aspects of the battery [31]. Circuit-Oriented Models (COM) are electrical equivalent models.…”

Section: Circuit-oriented Modelling Of a Batterymentioning

confidence: 99%

“…Therefore, the capability of these models to match the complex transient features of the battery is also limited. In addition, these models work only at fixed SoC values [31].…”

Section: Circuit-oriented Modelling Of a Batterymentioning

confidence: 99%

“…Thevenin subclass models provide the transient responses of the battery using resistorcapacitor (RC) networks [11,31], and these models are usually able to capture two timedependent effects, depletion and recovery. They mimic the transient and steady-state behaviour of the battery.…”

Section: Circuit-oriented Modelling Of a Batterymentioning

confidence: 99%

“…Circuit parameters are obtained by either (a) the battery's time response using pulse discharge test, (b) by looking at the instantaneous voltage drop, the time constants of the charge depletion and recovery regions and the current, (c) the least square method, etc. [31]. The precise estimation of internal battery parameters is a difficult task, according to the literature, due to nonlinear effects.…”

Section: Circuit-oriented Modelling Of a Batterymentioning

confidence: 99%

See 3 more Smart Citations

A Review on Battery Modelling Techniques

Tamilselvi¹,

Gunasundari²,

Karuppiah³

et al. 2021

Sustainability

132

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The growing demand for electrical energy and the impact of global warming leads to a paradigm shift in the power sector. This has led to the increased usage of renewable energy sources. Due to the intermittent nature of the renewable sources of energy, devices capable of storing electrical energy are required to increase its reliability. The most common means of storing electrical energy is battery systems. Battery usage is increasing in the modern days, since all mobile systems such as electric vehicles, smart phones, laptops, etc., rely on the energy stored within the device to operate. The increased penetration rate of the battery system requires accurate modelling of charging profiles to optimise performance. This paper presents an extensive study of various battery models such as electrochemical models, mathematical models, circuit-oriented models and combined models for different types of batteries. It also discusses the advantages and drawbacks of these types of modelling. With AI emerging and accelerating all over the world, there is a scope for researchers to explore its application in multiple fields. Hence, this work discusses the application of several machine learning and meta heuristic algorithms for battery management systems. This work details the charging and discharging characteristics using the black box and grey box techniques for modelling the lithium-ion battery. The approaches, advantages and disadvantages of black box and grey box type battery modelling are analysed. In addition, analysis has been carried out for extracting parameters of a lithium-ion battery model using evolutionary algorithms.

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Section: Circuit-oriented Modelling Of a Batterymentioning

confidence: 99%

“…Therefore, the capability of these models to match the complex transient features of the battery is also limited. In addition, these models work only at fixed SoC values [31].…”

Section: Circuit-oriented Modelling Of a Batterymentioning

confidence: 99%

Section: Circuit-oriented Modelling Of a Batterymentioning

confidence: 99%

Section: Circuit-oriented Modelling Of a Batterymentioning

confidence: 99%

See 2 more Smart Citations

A Review on Battery Modelling Techniques

Tamilselvi¹,

Gunasundari²,

Karuppiah³

et al. 2021

Sustainability

132

View full text Add to dashboard Cite

show abstract

“…Furthermore, it did not contain any look-up table. The accuracy of the model was validated with experimental outcomes [12].…”

Section: Introductionmentioning

confidence: 99%

An Electrical Equivalent Circuit Model of a Lithium Titanate Oxide Battery

Madani¹,

Schaltz²,

Kær³

2019

Batteries

102

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A precise lithium-ion battery model is required to specify their appropriateness for different applications and to study their dynamic behavior. In addition, it is important to design an efficient battery system for power applications. In this investigation, a second-order equivalent electrical circuit battery model, which is the most conventional method of characterizing the behavior of a lithium-ion battery, was developed. The current pulse procedure was employed for parameterization of the model. The construction of the model was described in detail, and a battery model for a 13 Ah lithium titanate oxide battery cell was demonstrated. Comprehensive characterization experiments were accomplished for an extensive range of operating situations. The outcomes were employed to parameterize the suggested dynamic model of the lithium titanate oxide battery cell. The simulation outcomes were compared to the laboratory measurements. In addition, the proposed lithium-ion battery model was validated. The recommended model was assessed, and the proposed model was able to anticipate precisely the current and voltage performance.

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Adaptive sliding mode estimation of state of charge implemented on a field programmable gate array Spartan‐6 Xilinx device

2021

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This paper presents the implementation of adaptive sliding mode estimation (ASME) of the state of charge of a battery on a field programmable gate array (FPGA). The study is conducted in two steps: in the first step, we design an adaptive sliding mode observer by taking into account an electrical equivalent circuit describing the battery's behavior and identify the parameters of this equivalent circuit by using the recursive least squares estimation method. In the second step, we study the implementation of this ASME on an FPGA card.

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A novel approach for electrical circuit modeling of Li-ion battery for predicting the steady-state and dynamic I–V characteristics

Cited by 18 publications

References 25 publications

A Review on Battery Modelling Techniques

A Review on Battery Modelling Techniques

An Electrical Equivalent Circuit Model of a Lithium Titanate Oxide Battery

Adaptive sliding mode estimation of state of charge implemented on a field programmable gate array Spartan‐6 Xilinx device

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