Implementation of reduced-order physics-based model and multi-parameters identification strategy for lithium-ion battery

Deng, Zhongwei; Deng, Hao; Yang, Lin; Cai, Yunze; Zhao, Xiaowei

doi:10.1016/j.energy.2017.07.069

Cited by 48 publications

(26 citation statements)

References 31 publications

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“…Zarc is the impedance of the parallel connection of these two parameters. If τ=(A0•Rct) 1/Ψ , Zarc can be expressed as: (29) Given that Rct depends on SOC and T, τ also has a dependency on these two variables. An exponential relationship between τ and SOC and a quadratic expression to relate τ and T are empirically proposed for the temperature range analyzed in this model.…”

Section: Charge Transfer Through the Seimentioning

confidence: 99%

“…The impedance of a battery is characterized by Rohm and Zarc, defined in Eq. (29). In order to determine its value, type c experiments (EIS) were carried out on a number of values of SOC and T. The frequency analyzed in the EIS experiments ranges from 100 mHz to 10 kHz.…”

Section: Battery Impedancementioning

confidence: 99%

“…On the other hand, the battery impedance can be designed by simplifying the physical equations in order to speed up the computer simulation while keeping the accuracy as high as possible [26][27][28][29]. In this case, the impedance parameters represent the primary physical processes which determine the battery performance.…”

Section: -Introductionmentioning

confidence: 99%

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A comprehensive model for lithium-ion batteries: From the physical principles to an electrical model

Berrueta

Urtasun

Ursúa

et al. 2018

Energy

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The growing interest in e-mobility and the increasing installation of renewable energy-based systems are leading to rapid improvements in lithium-ion batteries. In this context, battery manufacturers and engineers require advanced models in order to study battery performance accurately. A number of Li-ion battery models are based on the representation of physical phenomena by electrochemical equations. Although providing detailed physics-based information, these models cannot take into account all the phenomena for a whole battery, given the high complexity of the equations. Other models are based on equivalent circuits and are easier to design and use. However, they fail to relate these circuit parameters to physical properties. In order to take the best of both modeling techniques, we propose an equivalent circuit model which keeps a straight correlation between its parameters and the battery electrochemical principles. Consequently, this model has the required simplicity to be used in the simulation of a whole battery, while providing the depth of detail needed to identify physical phenomena. Moreover, due to its high accuracy, it can be used in a wide range of environments, as shown in the experimental validations carried out in the final section of this paper.

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Section: Charge Transfer Through the Seimentioning

confidence: 99%

Section: Battery Impedancementioning

confidence: 99%

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A comprehensive model for lithium-ion batteries: From the physical principles to an electrical model

Berrueta

Urtasun

Ursúa

et al. 2018

Energy

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show abstract

“…In other approaches such as the frequency-based method in [18], the transcendental transfer function is obtained and then reduced to a selected-order rational transfer function. The challenge when using reduced-order models is that although the computational time is relatively less than the time required by the electrochemical model, it is still not sufficiently efficient for online control applications [18,19].…”

Section: Introductionmentioning

confidence: 99%

A lumped thermal model of lithium-ion battery cells considering radiative heat transfer

Allafi

Zhang

Uddin³

et al. 2018

Applied Thermal Engineering

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“…The problem of reducing the number of variables of the finite element model to a number of main components can be solved using the reduced-order model (ROM) approach [16][17][18][19][20][21][22]. This approach allows us to take into account only the most important features of the modeling object with the help of several state variables and several ordinary differential equations.…”

Section: Reduced-order Modelsmentioning

confidence: 99%

Regulator synthesis for the self-sensing control system of the proportional electromagnet dc based on reduced-order models

et al. 2017

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Abstract. Modern DC proportional solenoid control systems use current values in magnetizing coils, or specialized sensors for position determination. These methods do not provide the possibility of accurate control and diagnostics, in case of aiming to the miniaturization of finished devices. In this article, it is proposed to use methods of self-sensory identification of the moving element position based on the method of the full-scale-model experiment. The functioning of the method is based on the electromagnet model obtained by the reduced-order model approach. These models have an advantage in the calculation speed in comparison with finite element models and have an advantage in accuracy in comparison with analytical models. Ansys Electronics is used to obtain the model. The electromagnetic control system is proposed. Its model is implemented in the system Matlab Simulink. Synthesis of PID-regulator parameters using Matlab is performed. The results of a study of a control system for a given displacement with the aid of the obtained control system are presented.

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Implementation of reduced-order physics-based model and multi-parameters identification strategy for lithium-ion battery

Cited by 48 publications

References 31 publications

A comprehensive model for lithium-ion batteries: From the physical principles to an electrical model

A comprehensive model for lithium-ion batteries: From the physical principles to an electrical model

A lumped thermal model of lithium-ion battery cells considering radiative heat transfer

Regulator synthesis for the self-sensing control system of the proportional electromagnet dc based on reduced-order models

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