Dependency analysis and degradation process-dependent modeling of lithium-ion battery packs

Wang, Xiaohong; Wang, Zhuo; Wang, Lizhi; Wang, Zhuoqi; Guo, Hongzhou

doi:10.1016/j.jpowsour.2019.01.021

Cited by 44 publications

(31 citation statements)

References 41 publications

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“…To study the dependency among cells, it is necessary to obtain the actual degradation data of cells and battery packs. In this work, the degradation test and the schematic diagram of battery packs were designed according to the degradation test platform in reference [2]. Degradation tests were carried out on the lithium-ion battery packs in the four battery packs of Pack A (series configuration), Pack B (parallel configuration), Pack C (series and parallel configuration), Pack D (parallel and series configuration), as shown in Figure 1.…”

Section: The Dependency Phenomenon and Its Influence On A Lithium-mentioning

confidence: 99%

“…Previous studies have found that the dependency among cells during battery charging and discharging, as well as the degradation of each cell, will affect the degradation process of the associated single battery. Because of the dependency among cells, the degradation amount and the degradation rate of a battery pack are neither equal to those of the cells nor to the sum of those of cells [2]. Accordingly, the degradation process of a battery pack depends not only on the performance of a single battery, but also on the dependency among the individual cells.…”

Section: Introductionmentioning

confidence: 99%

“…In order to improve the inconsistency of the series lithium-ion battery, Ma et al proposed the use of fuzzy logic control (FLC) to reduce battery pack energy consumption and equalization time based on a non-dissipative equalization scheme [9]. Wang et al carried out degradation tests on battery packs connected in series, in parallel, in series-parallel, and in parallel-series, and established a capacity degradation model considering the dependency of battery packs [2]. In summary, most of the existing work on the reliability of lithium-ion batteries does not consider the influence of dependency among cells, which leads to low accuracy of reliability estimation.…”

Section: Introductionmentioning

confidence: 99%

“…Published research that considers the inconsistencies of battery packs are mostly related to specific battery pack configurations [6,7,8,9]. These studies have built capacity degradation models, but they lack reliability models between cells and the entire battery pack that consider dependency [2,7]. Hence, this work focuses on a reliability model that considers the dependency among cells for various battery pack configurations.…”

Section: Introductionmentioning

confidence: 99%

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Reliability Modeling Method for Lithium-ion Battery Packs Considering the Dependency of Cell Degradations Based on a Regression Model and Copulas

et al. 2019

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Lithium-ion batteries are widely used as basic power supplies and storage units for large-scale electric drive products such as electric vehicles. Their reliability is directly related to the life and safe operation of the electric drive products. In fact, the cells have a dependent relationship with the degradation process and they affect the degradation rate of the entire battery pack, thereby affecting its reliability. At present, most research focuses on the reliability of battery packs and assumes that their cells are independent of each other, which may cause the reliability of the evaluation to deviate greatly from the actual level. In order to accurately assess the reliability of lithium-ion batteries, it is necessary to build a reliability model considering the dependency among cells for the overall degradation of lithium-ion battery packs. Therefore, in this study, based on a lithium-ion battery degradation test, the Wiener process is used to analyze the reliability of four basic configurations of lithium-ion battery packs. According to the degradation data of the battery packs, the Copula function is used to quantitatively describe the dependent relationship in the degradation process of a single battery, and the quantitative dependent relationship is combined with the reliability model to form a new reliability model. Finally, taking the battery system of Tesla S as an example, a feasible optimization method for battery pack design is provided based on the model constructed in this work.

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Section: The Dependency Phenomenon and Its Influence On A Lithium-mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Reliability Modeling Method for Lithium-ion Battery Packs Considering the Dependency of Cell Degradations Based on a Regression Model and Copulas

et al. 2019

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“…There is a variety of articles focusing on modeling [11][12][13][14][15], aging [16][17][18], safety [19][20][21], state estimation [22,23] and measurement [24][25][26] of parallel-connected cells. Mostly qualitative effects like OCV [27], SoC [13], temperature [13,26,28,29] and current differences [13] are demonstrated but quantitative relationships are missing, especially with regard to the thermal connection of the cells to neighboring cells and cooling.…”

Section: Introductionmentioning

confidence: 99%

Measuring Test Bench with Adjustable Thermal Connection of Cells to Their Neighbors and a New Model Approach for Parallel-Connected Cells

et al. 2019

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This article presents a test bench with variable temperature control of the individual cells connected in parallel. This allows to reconstruct arising temperature gradients in a battery module and to investigate their effects on the current distribution. The influence of additional contact resistances induced by the test bench is determined and minimized. The contact resistances are reduced from R Tab + = 81.18 μ Ω to R Tab + = 55.15 μ Ω at the positive respectively from R Tab − = 35.59 μ Ω to R Tab − = 28.2 μ Ω at the negative tab by mechanical and chemical treating. An increase of the contact resistance at the positive tab is prevented by air seal of the contact. The resistance of the load cable must not be arbitrarily small, as the cable is used as a shunt for current measurement. In order to investigate their impacts, measurements with two parallel-connected cells and different load cables with a resistance of R Cab + = 0.3 m Ω , R Cab + = 1.6 m Ω and R Cab + = 4.35 m Ω are conducted. A shift to lower current differences with decreasing cable resistance but qualitatively the same dynamic of the current distribution is found. An extended dual polarization model is introduced, considering the current distribution within the cells as well as the additional resistances induced by the test bench. The model shows a high correspondence to measurements with two parallel-connected cells, with a Root Mean Square Deviation (RMSD) of ξ RMSD = 0.083 A.

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Highly active Mo doping TiO ₂ as sulfur loaded matrix material for lithium‐sulfur batteries with excellent electrochemical performances

Yan

Lang

et al. 2021

Intl J of Energy Research

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Lithium-sulfur batteries have attracted much attention for a long time owing to their high theoretical specific capacity. In this paper, a type of highly active Mo doping TiO 2 as sulfur loaded matrix material has been synthesized by a facile solvothermal method. X-ray diffraction and Raman spectrum tests show that Mo atom can enter into the interlayer of TiO 2 crystal face and increase the interplanar spacing of titanium dioxide in order to possess a higher electrochemical activity. Small particles morphology and uniform particle size can be evidently observed by scanning electron microscope and after sulfur loading (1:1), it still retains the similar morphology as matrix material. This illustrates that a considerable amount of sulfur has penetrated into the matrix material in order to achieve the ideal sulfur loading effect. When used as electrode active material, it displays the lowest electrochemical and concentration polarization resistance and the specific capacities can reach 1483.08, 1208.57, and 1004.17 mAh g −1 at 0.1, 0.2, and 0.5 C current rates and after 150 cycles, the capacity retention is over 60%. When the sulfur loading mass ratio increases to 1:2 (Mo/TiO 2 :S), the sulfur composite cathode still maintains considerable lithium-ion diffusion channels and 753.54 mAh g −1 of specific discharge capacity at 0.5 C current rate. K E Y W O R D Sa facile solvothermal method, highly active matrix material, lithium-sulfur batteries, Mo doping TiO 2 , sulfur composite cathode

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Dependency analysis and degradation process-dependent modeling of lithium-ion battery packs

Cited by 44 publications

References 41 publications

Reliability Modeling Method for Lithium-ion Battery Packs Considering the Dependency of Cell Degradations Based on a Regression Model and Copulas

Reliability Modeling Method for Lithium-ion Battery Packs Considering the Dependency of Cell Degradations Based on a Regression Model and Copulas

Measuring Test Bench with Adjustable Thermal Connection of Cells to Their Neighbors and a New Model Approach for Parallel-Connected Cells

Highly active Mo doping TiO ₂ as sulfur loaded matrix material for lithium‐sulfur batteries with excellent electrochemical performances

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Dependency analysis and degradation process-dependent modeling of lithium-ion battery packs

Cited by 44 publications

References 41 publications

Reliability Modeling Method for Lithium-ion Battery Packs Considering the Dependency of Cell Degradations Based on a Regression Model and Copulas

Reliability Modeling Method for Lithium-ion Battery Packs Considering the Dependency of Cell Degradations Based on a Regression Model and Copulas

Measuring Test Bench with Adjustable Thermal Connection of Cells to Their Neighbors and a New Model Approach for Parallel-Connected Cells

Highly active Mo doping TiO 2 as sulfur loaded matrix material for lithium‐sulfur batteries with excellent electrochemical performances

Contact Info

Product

Resources

About

Highly active Mo doping TiO ₂ as sulfur loaded matrix material for lithium‐sulfur batteries with excellent electrochemical performances