A Novel Grouping Method for Lithium Iron Phosphate Batteries Based on a Fractional Joint Kalman Filter and a New Modified K-Means Clustering Algorithm

Li, Xiaoyu; Song, Kai; Wei, Guo; Lu, Rengui; Zhu, Chunbo

doi:10.3390/en8087703

Cited by 25 publications

(12 citation statements)

References 26 publications

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“…Because the porous structure of the electrode has a fractal dimension, the fractal morphology of the charge distribution on the electrode has nonlinear characteristics, which cannot be expressed accurately by integer order calculus. Finally, when other electrochemical reactions are ignored, a fractional capacitor can be used to approximately characterize the battery polarization phenomenon between point B and point C [21,22]. The capacitor Q which has a fractional property is called fractional capacitor in general and its impedance can be defined as:…”

Section: Battery Modelingmentioning

confidence: 99%

Rapid Estimation Method for State of Charge of Lithium-Ion Battery Based on Fractional Continual Variable Order Model

Li²,

et al. 2018

Energies

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In recent years, the fractional order model has been employed to state of charge (SOC) estimation. The non integer differentiation order being expressed as a function of recursive factors defining the fractality of charge distribution on porous electrodes. The battery SOC affects the fractal dimension of charge distribution, therefore the order of the fractional order model varies with the SOC at the same condition. This paper proposes a new method to estimate the SOC. A fractional continuous variable order model is used to characterize the fractal morphology of charge distribution. The order identification results showed that there is a stable monotonic relationship between the fractional order and the SOC after the battery inner electrochemical reaction reaches balanced. This feature makes the proposed model particularly suitable for SOC estimation when the battery is in the resting state. Moreover, a fast iterative method based on the proposed model is introduced for SOC estimation. The experimental results showed that the proposed iterative method can quickly estimate the SOC by several iterations while maintaining high estimation accuracy.

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Section: Battery Modelingmentioning

confidence: 99%

Rapid Estimation Method for State of Charge of Lithium-Ion Battery Based on Fractional Continual Variable Order Model

Li²,

et al. 2018

Energies

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“…The k-means algorithm is a hard clustering algorithm and is a typical representative of a prototype-based objective function clustering. It is an objective function that takes the distance between data points and the prototype as optimization [16]. The adjustment rules of the iterative operation are obtained through finding the extremum of the function.…”

Section: Binary K-means Clustering Algorithmmentioning

confidence: 99%

Research on Key Parameters Operation Range of Central Air Conditioning Based on Binary K-Means and Apriori Algorithm

2018

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As the energy-saving control of central air conditioning has been widely applied in modern architecture, research of real-time optimal control based on historical data and identification of its optimal control strategies are of great importance for reducing energy wasting of buildings. However, due to the property of easily falling into local optimum, conventional k-means approach cannot achieve the goal of real-time optimal control, we therefore propose an innovative binary k-means clustering algorithm which is used to adjust the target value of temperature difference (TD) in the control system of chilled water and cooling water of central air conditioning system (CACS). Thanks to the clustering control, among the 304 test data, the coefficient of performance (COP) of 211 sets of data, which accounted for 69.41%, are higher than those of the traditional control method. In the simulation system, the COP of 191 sets of data, which accounted for 62.83%, are higher than those of traditional control methods, achieving better energy efficiency. To achieve the goal of identify potential energy-saving control strategies, the Apriori algorithm is proposed to correlate the key parameters and energy consumption efficiency of the CACS. The results show when the chilled water temperature difference (CWTD) > 2.0 °C and the cooling water temperature difference (COWTD) > 2.4 °C, some rules are discovered as follows: 1. The probability of a larger system COP will increase if the CWTD is set lower than the third quartile value or the COWTD is set lower than the first quartile value. 2. The probability of a larger system COP will also increase if the CTWD is set lower than the first quartile and the COWTD is set between the first and the third quartile. These underlying regularity is useful for technicians to adjust the control parameters of the equipment, to improve energy efficiency and to reduce energy consumption.

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“…Moreover, it is necessary to add an electric contact resistance to the ECM to present the contact resistances in the battery pack connections, as the contact resistances are comparable to internal resistances and cannot be neglected [14]. Thus, the ECM which considers the contact resistance of the cell is taken to analyze the capacity fade fault, as shown in Figure 5 [18][19][20]. Based on the literature [15], the state equations of the ECM in Figure 5 are shown in Equations (4) and (5).…”

Section: Description Of the Battery Behaviormentioning

confidence: 99%

Online Diagnosis for the Capacity Fade Fault of a Parallel-Connected Lithium Ion Battery Group

et al. 2016

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In a parallel-connected battery group (PCBG), capacity degradation is usually caused by the inconsistency between a faulty cell and other normal cells, and the inconsistency occurs due to two potential causes: an aging inconsistency fault or a loose contacting fault. In this paper, a novel method is proposed to perform online and real-time capacity fault diagnosis for PCBGs. Firstly, based on the analysis of parameter variation characteristics of a PCBG with different fault causes, it is found that PCBG resistance can be taken as an indicator for both seeking the faulty PCBG and distinguishing the fault causes. On one hand, the faulty PCBG can be identified by comparing the PCBG resistance among PCBGs; on the other hand, two fault causes can be distinguished by comparing the variance of the PCBG resistances. Furthermore, for online applications, a novel recursive-least-squares algorithm with restricted memory and constraint (RLSRMC), in which the constraint is added to eliminate the "imaginary number" phenomena of parameters, is developed and used in PCBG resistance identification. Lastly, fault simulation and validation results demonstrate that the proposed methods have good accuracy and reliability.

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A Novel Grouping Method for Lithium Iron Phosphate Batteries Based on a Fractional Joint Kalman Filter and a New Modified K-Means Clustering Algorithm

Cited by 25 publications

References 26 publications

Rapid Estimation Method for State of Charge of Lithium-Ion Battery Based on Fractional Continual Variable Order Model

Rapid Estimation Method for State of Charge of Lithium-Ion Battery Based on Fractional Continual Variable Order Model

Research on Key Parameters Operation Range of Central Air Conditioning Based on Binary K-Means and Apriori Algorithm

Online Diagnosis for the Capacity Fade Fault of a Parallel-Connected Lithium Ion Battery Group

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