Nonlinear Temperature-Dependent State Model of Cylindrical LiFePO4 Battery for Open-Circuit Voltage, Terminal Voltage and State-of-Charge Estimation with Extended Kalman Filter

Chin, Cheng Siong; Gao, Zhiqiang; Chiew, J; Zhang, Caizhi

doi:10.3390/en11092467

Cited by 25 publications

(16 citation statements)

References 70 publications

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“…The technologies of coating the cathode surface with finely dispersed oxides are also being mastered. The problems of the synthesis of these compounds, associated with the difference in the structures of nickelate (layered hexagonal) and lithium manganate (layered rhombohedral), were overcome by using nickel and manganese double hydroxide systems for the synthesis, after which work on the synthesis of mixed oxides began to be intensively carried out in different countries (USA, Canada, South Korea, China) [84][85][86][87][88].…”

Section: Processes On the Positive Electrode Of The Li-ion Batterymentioning

confidence: 99%

Degradation of Lithium-Ion Batteries in an Electric Transport Complex

et al. 2021

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The article provides an overview and comparative analysis of various types of batteries, including the most modern type—lithium-ion batteries. Currently, lithium-ion batteries (LIB) are widely used in electrical complexes and systems, including as a traction battery for electric vehicles. Increasing the service life of the storage devices used today is an important scientific and technical problem due to their rapid wear and tear and high cost. This article discusses the main approaches and methods for researching the LIB resource. First of all, a detailed analysis of the causes of degradation was carried out and the processes occurring in lithium-ion batteries during charging, discharging, resting and difficult operating conditions were established. Then, the main factors influencing the service life are determined: charging and discharging currents, self-discharge current, temperature, number of cycles, discharge depth, operating range of charge level, etc. when simulating a real motion process. The work considers the battery management systems (BMS) that take into account and compensate for the influence of the factors considered. In the conclusion, the positive and negative characteristics of the presented methods of scientific research of the residual life of LIB are given and recommendations are given for the choice of practical solutions to engineers and designers of batteries. The work also analyzed various operating cycles of electric transport, including heavy forced modes, extreme operating modes (when the amount of discharge and discharge of batteries is greater than the nominal value) and their effect on the degradation of lithium-ion batteries.

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Section: Processes On the Positive Electrode Of The Li-ion Batterymentioning

confidence: 99%

Degradation of Lithium-Ion Batteries in an Electric Transport Complex

et al. 2021

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“…Energies 2020, 13, 121 3 of 16 where U 1 represents terminal voltage, R pol and C pol represent the polarization resistance and the polarization capacitance, respectively; the terminal voltage of C pol is the polarization voltage U pol . R ohm and R i are the ohmic internal resistance and the other internal resistance, respectively, and I 1 is the battery charging or discharging current.…”

Section: Battery Thevenin Modelmentioning

confidence: 99%

A Dynamic State-of-Charge Estimation Method for Electric Vehicle Lithium-Ion Batteries

Liu

Deng

et al. 2019

Energies

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With the increasing environmental concerns, plug-in electric vehicles will eventually become the main transportation tools in future smart cities. As a key component and the main power source, lithium-ion batteries have been an important object of research studies. In order to efficiently control electric vehicle powertrains, the state of charge (SOC) of lithium-ion batteries must be accurately estimated by the battery management system. This paper aims to provide a more accurate dynamic SOC estimation method for lithium-ion batteries. A dynamic Thevenin model with variable parameters affected by the temperature and SOC is established to model the battery. An unscented Kalman particle filter (UPF) algorithm is proposed based on the unscented Kalman filter (UKF) algorithm and the particle filter (PF) algorithm to generate nonlinear particle filter according to the advantages and disadvantages of various commonly used filtering algorithms. The simulation results show that the unscented Kalman particle filter algorithm based on the dynamic Thevenin model can predict the SOC in real time and it also has strong robustness against noises.

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“…On the other hand, equivalent circuit model relies on external dynamic appearances that can sidestep the comprehensive deviousness of internal electrochemical progressions. Therefore, Equivalent circuit model is frequently enrolled to replicate the cells' peripheral characteristics and enhance the truthfulness of BMS [13], [14]. This paper contains the first-order Thevenin Equivalent circuit model which is shown in Fig.…”

Section: A Battery Modelingmentioning

confidence: 99%

Active Cell Balancing Control Method for Series-Connected Lithium-Ion Battery

Qays¹,

Buswig²,

Anyi³

2019

IJITEE

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Power conveyance potentiality for series and parallel allied battery-packages are constrained by the wickedest cell of the string. Every cell contains marginally dissimilar capability and terminal voltage because of industrialized acceptances and functional situations. During charging or discharging progression, the charge status of the cell strings become imbalanced and incline to loss equalization. Therefore, the enthusiasm of this paper is to design an active charge balancing system for Lithium-ion battery pack with the help of online state of charge (SOC) estimation technique. A Battery Management System (BMS) is modeled by means of controlling the SOC of the cells to upsurge the efficacy of rechargeable batteries. The capacity of each cell is calculated by dint of SOC function estimated as a result of Backpropagation Neural Network (BPNN) algorithm through four switched DC/DC Buck-Boost converter. The simulation results confirm that the designed BMS can synchronize the cell equalization via curtailing the SOC estimation error (RMSE 1.20%) productively.

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Nonlinear Temperature-Dependent State Model of Cylindrical LiFePO4 Battery for Open-Circuit Voltage, Terminal Voltage and State-of-Charge Estimation with Extended Kalman Filter

Cited by 25 publications

References 70 publications

Degradation of Lithium-Ion Batteries in an Electric Transport Complex

Degradation of Lithium-Ion Batteries in an Electric Transport Complex

A Dynamic State-of-Charge Estimation Method for Electric Vehicle Lithium-Ion Batteries

Active Cell Balancing Control Method for Series-Connected Lithium-Ion Battery

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