This study proposes an evaluation method for the consistency of lithium-ion battery packs in EVs based on the Mahalanobis-Taguchi system (MTS). First, a Douglas-Peucker (D P) algorithm was developed to compress high-dimensional cell voltage data, which reduced the feature extraction time by 81.64 %. Next, the consistency features were extracted based on
This paper starts from the consistency evaluation method based on voltage curve similarity and determines the characterization parameters that can characterize the
Lithium-ion batteries (LIBs), the main pillar of energy storage technology for electric vehicles (EVs), suffer from performance degradation during usage and storage in terms of capacity and power [1].Typically, they reach their end-of-life when their remaining capacity reaches 80% of the nominal capacity [2] or their internal resistance reaches 200% of that of
This article proposes an information analysis-based multiple adaptive forgetting factors (FFs) recursive least squares (IA-MAFF-RLS) method to identify model parameters of
Download Citation | On Dec 1, 2024, Yanru Zhang and others published Consistency evaluation of Lithium-ion battery packs in electric vehicles based on incremental capacity curves transformation
Consistency is an essential factor affecting the operation of lithium-ion battery packs. Pack consistency evaluation is of considerable significance to the usage of batteries. Many existing methods are limited for they are based on a single feature or can only be implemented offline. This paper develops a compre- hensive method to evaluate the pack
In this work, a battery pack consistency evaluation approach is proposed based on multi-feature information fusion. Ohmic resistance, polarization resistance and open circuit voltage are identified as feature parameters from electric vehicle operation data.
Consistency is an essential factor affecting the operation of lithium-ion battery packs. Pack consistency evaluation is of considerable significance to the usage of batteries. Many existing methods are limited for they are based on a single feature or can only be implemented offline. This paper develops a comprehensive method to evaluate the pack consistency based
In this paper, the lithium iron phosphate battery capacity increase curve (IC curve) was used as an analysis tool. It is found that the IC curve characteristic peaks of different monomers in the battery pack can reflect the consistency between the monomers.
The consistency among lithium-ion battery pack is an important factor affecting their performance. The paper analyzes the impact sensitivity of parameters consistency including capacity, internal resistance and state of charge (SOC) on energy utilization efficiency of the battery pack. It turns out that SOC variations is the most
In this work, a battery pack consistency evaluation approach is proposed based on multi-feature information fusion. Ohmic resistance, polarization resistance and open circuit voltage are
This study proposes an evaluation method for the consistency of lithium-ion battery packs in EVs based on the Mahalanobis-Taguchi system (MTS). First, a Douglas
In this paper, the lithium iron phosphate battery capacity increase curve (IC curve) was used as an analysis tool. It is found that the IC curve characteristic peaks of
This study proposes an evaluation method for the consistency of lithium-ion battery packs in EVs based on the Mahalanobis-Taguchi system (MTS). First, a Douglas-Peucker (D P) algorithm was developed to compress high-dimensional cell voltage data, which reduced the feature extraction time by 81.64 %.
This method can quickly describe the battery pack consistency problem, and can be applied during the normal charging process of the battery pack. During the whole life of the battery pack, the battery consistency can be determined in real time, which has certain practical value for the utilization and accurate management of the battery pack. References [1] Minggao
This article proposes an information analysis-based multiple adaptive forgetting factors (FFs) recursive least squares (IA-MAFF-RLS) method to identify model parameters of lithium-ion batteries...
The consistency among lithium-ion battery pack is an important factor affecting their performance. The paper analyzes the impact sensitivity of parameters consistency
Consistency evaluation based on multi-feature weighted for batteries is proposed. The weights of features are determined by the entropy weight method. Consistency evaluation
This paper starts from the consistency evaluation method based on voltage curve similarity and determines the characterization parameters that can characterize the inconsistency in capacity, internal resistance, and state of charge (SOC). Then, from the perspective of the aging evolution law, the error sources and limitations of the
Bonnen Battery supply 48V 72V 96V lithium ion electric car battery. Custom battery packs are available. Lithium Battery Consistency And Sorting Method 1 nsistency of lithium batteries definition. At present, it refers to the convergence of a group of important characteristic parameters of lithium batteries. It is a relative . Skip to content. LinkedIn
Abstract: The performance inconsistency of lithium-ion battery packs is one of the key factors that lead to their accelerated lifespan degradation and reduced reliability. Hence, it is of great
The consistency of battery cells is important for power battery pack. The current large-scale application of lithium-ion batteries in new energy vehicles, smart grids and other fields is increasing year by year, but the current inconsistency of battery parameters is a key factor affecting the service life of battery packs, although the improvement of thermal management
To solve this problem, a non-destructive testing method for capacity consistency of lithium-ion battery pack based on 1-D magnetic field scanning is proposed in this article. First, a magnetic field simulation model and measurement setup of lithium-ion battery are developed to study the principle of detection technology. On such
Consistency evaluation based on multi-feature weighted for batteries is proposed. The weights of features are determined by the entropy weight method. Consistency evaluation features can be extracted online. An improved fuzzy clustering algorithm is developed to evaluate pack consistency.
Abstract: The performance inconsistency of lithium-ion battery packs is one of the key factors that lead to their accelerated lifespan degradation and reduced reliability. Hence, it is of great significance to accurately detect the consistency of cell parameters within the pack without destructive testing. The working current of the cell is the
To solve this problem, a non-destructive testing method for capacity consistency of lithium-ion battery pack based on 1-D magnetic field scanning is proposed in this article.
DOI: 10.1016/j.energy.2020.116944 Corpus ID: 213175255; Consistency evaluation and cluster analysis for lithium-ion battery pack in electric vehicles @article{Tian2020ConsistencyEA, title={Consistency evaluation and cluster analysis for lithium-ion battery pack in electric vehicles}, author={Jiaqiang Tian and Yujie Wang and Chang Liu and Zonghai Chen}, journal={Energy},
6 天之前· Consistency is the main indicator for evaluating battery pack performance, and its characterization method needs to be able to express the external discharge capability of the battery pack and truly describe its current state without changes in external factors. Single-factor indicators cannot fully describe the battery state. Multi
The EUE estimation value is obtained using the MC method. The proposed battery pack consistency modeling and EUE estimation method is verified based on the test results of a retired lithium-ion battery pack with 95 in-series connected LiFePO 4 battery cells. The EUE estimation errors at various discharge current rates are within 0.6%.
Consistency evaluation features can be extracted online. An improved fuzzy clustering algorithm is developed to evaluate pack consistency. The proposed methods are validated by nine months of electric vehicle data. Consistency is an essential factor affecting the operation of lithium-ion battery packs.
Qian et al. evaluated the consistency of grouped lithium-ion batteries based on characteristic peaks of incremental capacity curves. This method can quickly describe the consistency issue of battery packs and can be applied during the charging process of battery packs.
The evaluation of consistency in battery packs is therefore crucial. The initial consistency concerns the differences between batteries, even for those manufactured in the same batch .
In Ref. , the voltage variation rate is employed to evaluate the pack consistency. Model-based: These approaches employ filters or parameter identification algorithms to estimate the battery parameters. Then, the pack consistency is evaluated by the parameter distribution.
The SOC consistency of battery pack can be employed as evaluation index representing the battery consistency level. As is known, the SOC-OCV function is a representative for a particular battery, and is generally a nonlinear monotone function between SOC and OCV for all lithium-ion batteries.
The results show that the proposed method can accurately diagnose the capacity consistency of the tested battery pack, which provides a basis for battery pack performance testing and maintenance. The capacity inconsistency among commercial lithium-ion battery packs is an important factor affecting their service life.
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