How are power lithium batteries sorted and allocated into groups?

The inconsistency between single cells often causes problems such as rapid capacity decay and short life of the battery pack during the cycle. It is of great significance for the popularization and application of lithium-ion batteries in power batteries to select batteries with as consistent performance as possible for grouping.

This paper analyzes the performance and causes of lithium-ion battery inconsistency, summarizes the methods to improve the consistency of lithium-ion batteries, and reviews the existing matching schemes.

How are power lithium batteries sorted and allocated into groups?

1. Analysis of Inconsistency

1.1 Definition of Inconsistency

Inconsistency in lithium-ion battery packs refers to the variation in parameters such as voltage, capacity, internal resistance, lifespan, temperature sensitivity, and self-discharge rate among individual cells of the same specifications and model, after they are assembled into a battery pack.Upon manufacturing, individual battery cells inherently exhibit initial performance differences. As these cells are used, these performance variations accumulate. Additionally, variations in the usage environment within the battery pack further amplify the inconsistencies, accelerating the degradation of battery performance and ultimately leading to premature failure of the battery pack.

1.2 Manifestation of Inconsistency

The inconsistency in lithium-ion batteries primarily manifests in two aspects: the differences in performance parameters of individual cells (such as capacity, internal resistance, and self-discharge rate) and the differences in State of Charge (SOC) among cells.

Research conducted by Dai Haifeng et al. indicates that the distribution of capacity differences between individual cells follows a similar distribution to the Weibull distribution. The variability of internal resistance is more significant than that of capacity, and internal resistance within a batch of cells generally conforms to a normal distribution. Self-discharge rate also approximates a normal distribution. SOC represents the battery’s charge status, defined as the ratio of remaining capacity to rated capacity. Due to the inconsistency in capacity degradation rates among cells, the maximum available capacity among cells varies. Cells with lower capacity experience a faster SOC change rate compared to cells with higher capacity, reaching the cutoff voltage more quickly during charge and discharge.

1.3 Causes of Inconsistency

There are numerous factors contributing to inconsistency issues in lithium-ion batteries, primarily arising from both the manufacturing and usage processes. Each step of the manufacturing process, such as the uniformity of the slurry during electrode preparation, control of coating density and surface tension during electrode coating, can introduce differences in the performance of individual cells.

Research by Luo Yu and others examined the impact of production processes on battery consistency. Specifically, the study focused on the impact of the production process of lithium-ion batteries using water-based binders on battery consistency. In the usage process of batteries, Xie Jiao and colleagues concluded that connection methods, structural components/devices, usage conditions, and environmental factors all influence battery pack consistency. Since the energy consumed at each connection point is inconsistent and the performance and aging rate of each component or structural part differ, the effects on battery consistency are also inconsistent. Moreover, the varying positions and temperatures of individual cells within the battery result in varying degrees of performance degradation, further exacerbating cell inconsistency.

2. Methods to Improve Battery Consistency

2.1 Control of Production Process

Control over the production process primarily involves two aspects: raw materials and manufacturing techniques. Regarding raw materials, it’s essential to select materials from the same batch to ensure consistent particle size and properties. In terms of manufacturing techniques, strict control must be maintained over the entire production process. For instance, uniform mixing of slurry, avoiding prolonged idle times, regulating the speed of coating machines to ensure uniform thickness, appearance inspection of electrode sheets, weight classification, controlling electrolyte injection and formation, cell matching, and storage conditions.Through research into the technological process of lithium-ion battery preparation, Luo Yu identified key processes significantly affecting battery consistency. These include material mixing, coating, calendering, winding/stacking, electrolyte injection, and formation. An in-depth study and analysis of the relationship between critical process parameters and battery performance were conducted.

2.2 Control of Grouping Process

Control over the grouping process mainly refers to the selection of battery cells. Uniform specifications and models of cells are used in battery pack assembly, with measurements conducted for voltage, capacity, and internal resistance to ensure the initial performance consistency of the cells.

Xu Haitao and others discovered that voltage differences between individual cells during grouping significantly influence the consistency of each cell’s charge and discharge at later stages. Meanwhile, disparities in internal resistance among individual cells lead to significant voltage disparities during the charge and discharge process. Wang Linxia and colleagues conducted research on the inconsistency of single cells in parallel and series combination batteries. They analyzed the impact of DC resistance (DCR) on parallel battery packs and the impact of capacity on series battery packs, providing essential insights for combined battery packs. Chen Ping and co-researchers investigated the impact of discharge rates on the consistency of battery grouping. They found that increasing the discharge rate amplified the inconsistency, leading to the elimination of defective cells.

2.3 Control of Usage and Maintenance Process

Real-time monitoring of batteries is imperative. Grouping ensures initial consistency during the early stages of battery pack use. In the usage process, real-time monitoring allows observation of consistency issues as they arise. However, poor consistency might lead to circuit cutoff, causing a decrease in performance. Balancing between the two must be achieved. Real-time monitoring can also facilitate timely adjustment or replacement of extreme parameter cells, preventing inconsistency from expanding over time.

Introduction of balance management systems is key. Batteries are intelligently managed through appropriate balancing strategies and circuits. Common balancing strategies include those based on external voltage, state of charge (SOC), and capacity. In terms of energy consumption, balance circuits can be passive or active. Active balancing achieves non-loss energy flow between batteries, garnering global attention in research. Active balancing methods include bypassing, switching capacitors, switching inductors, DC/DC conversion, and more.

Thermal management of batteries is essential. In addition to maintaining the battery pack’s operating temperature within an optimal range, efforts should be made to ensure consistent temperature conditions among the batteries, effectively ensuring performance consistency among all cells. Adopting rational control strategies is crucial. Within permissible output power, minimizing discharge depth while avoiding overcharging prolongs the battery pack’s cycle life. Enhanced maintenance of the battery pack is also vital. Regular low-current maintenance charging should be conducted at intervals, and cleanliness should be maintained.

3. Methods for Grouping Power Lithium-Ion Batteries

3.1 Voltage Grouping Method

The voltage grouping method can be divided into static voltage grouping and dynamic voltage grouping. Static voltage grouping, also known as open-circuit voltage grouping, is conducted without load, only considering the battery itself. It measures the self-discharge rate of the selected individual cells in a fully charged state after several days of idle storage, as well as the open-circuit voltage of the battery under different storage periods in a fully charged state. This method is the simplest to operate but lacks accuracy. Dynamic voltage grouping examines voltage under load conditions but does not account for factors like load variations, making it less accurate.

3.2 Static Capacity Grouping Method

Battery cells are charged and discharged under set conditions to calculate capacity based on discharge current and discharge time, and then cells are grouped by capacity size. This method is simple and feasible, but it only reflects that batteries have the same capacity under specific conditions and cannot fully illustrate the battery’s comprehensive operating characteristics, having certain limitations.

3.3 Internal Resistance Grouping Method

This method primarily considers the internal resistance of individual cells. It enables quick measurements but is challenged by the fact that internal resistance changes during the discharge process, making accurate measurement of internal resistance somewhat difficult.

3.4 Multi-Parameter Grouping Method

Multiple external conditions such as capacity, internal resistance, voltage, and self-discharge rate are simultaneously considered for a comprehensive evaluation of battery cells. This method can segregate batteries with better consistency. However, its prerequisite is accurate single-parameter segregation, which also results in longer processing times.

3.5 Dynamic Characteristics Grouping Method

The dynamic characteristics grouping method involves segregating battery cells based on their charge and discharge characteristic curves. These curves encapsulate a majority of the battery’s characteristics. Utilizing the dynamic characteristics grouping method ensures consistency in various performance indicators of the batteries. This method involves significant data and is often facilitated through computer programs. Furthermore, the utilization efficiency of battery grouping decreases, which hinders the reduction of battery pack costs. Determining standard curves or reference curves also poses a challenge in the implementation of this method.

4. Conclusion

(1) The main reasons for battery inconsistency primarily stem from both the manufacturing and usage aspects of the battery.(2) Measures to enhance battery consistency mainly encompass the following three areas: stringent control over the production process from both raw materials and manufacturing techniques; adoption of more scientifically grounded sorting methods to group batteries with similar initial performances; during battery use and maintenance, real-time monitoring is applied, an equilibrium management system is introduced, rational control strategies are employed, thermal management is conducted, and maintenance of battery packs is strengthened.(3) During battery grouping, the single-parameter grouping method holds limited practical value due to its limited considerations. Multi-parameter grouping and dynamic characteristic grouping methods are comparatively more comprehensive. Additionally, methods such as electrochemical impedance spectroscopy have also made certain progress.

Most Popular