The application of lithium-ion batteries in new energy vehicles, smart grids and other fields is increasing year by year. However, the inconsistency of battery parameters is a key factor affecting the lifespan of battery packs. Although the improvement of thermal management has ensured the safe operation of battery packs to some extent, improving the consistency of batteries is still an important technical factor affecting the large-scale use of lithium-ion batteries.
Through simulation of a 10-in-10 parallel battery pack, we elucidate the impact of temperature distribution within the battery pack on its performance and cycle life.
The lower the average temperature, the greater the temperature non-uniformity, and the greater the inconsistency in the depth of discharge of individual cells within the battery pack; conversely, the higher the average temperature, the greater the temperature non-uniformity, and the shorter the cycle life of the battery pack. It is worth noting that uneven temperature distribution can lead to uneven current distribution among parallel branches, thereby worsening the consistency of individual cell aging rates.
Lithium-ion battery consistency refers to the consistency of initial performance indicators of individual cells used in battery packs, including capacity, impedance, electrode electrical characteristics, electrical connections, temperature characteristics, and decay rate. Inconsistencies in these factors will directly affect the differences in output electrical parameters during operation.
The inconsistency or discreteness of lithium-ion battery packs refers to the fact that when individual batteries of the same specification and model are combined into a battery pack, their voltage, charge, capacity, degradation rate, internal resistance and its rate of change over time, lifespan, temperature effect, self-discharge rate and its rate of change over time will vary.
Individual battery cells inherently exhibit performance variations after manufacturing. These initial inconsistencies accumulate with continuous charge-discharge cycles during use, leading to greater differences in the state of charge (SOC), voltage, etc., among individual cells. Furthermore, the operating environment within the battery pack varies for each individual cell. This results in a gradual amplification of individual cell inconsistencies during use, which in some cases accelerates the performance degradation of certain cells and ultimately causes premature battery pack failure.
From a chronological perspective, the inconsistencies in individual cells within a battery pack can be attributed to two main factors: Firstly, manufacturing process issues and material inhomogeneity result in minute differences in the activation level and thickness of the active materials on the battery plates, microporosity, interconnections, and separators, leading to incomplete inconsistencies in internal structure and materials. Secondly, differences in electrolyte density, temperature, ventilation conditions, self-discharge levels, and charging/discharging processes among the individual cells within the battery pack during vehicle installation can also contribute to inconsistencies.
Regarding the causes of these inconsistencies, is it possible to completely eliminate inconsistencies within the battery pack through certain measures? Many people believe that battery inconsistencies are a problem with the manufacturing process, while others believe that they are a problem with the packing process. They think that process control measures such as SPC can completely eliminate battery inconsistencies.
However, practice has shown that even with strict control over processes such as ingredient preparation, pulping, coating, cutting, and rolling, only the standard deviation between batches of products can be reduced, but inconsistencies cannot be eliminated.
If a random variable is affected by many random factors, and the influence of each factor alone cannot play a decisive role, and the influence of these factors can be superimposed, then the random variable follows a normal distribution, and the characteristic parameters are the standard deviation σ and the mean μ.
The voltage value of a battery during charging and discharging is a comprehensive reflection of the battery's thermodynamic and kinetic state. It is affected by the process conditions of each step in the battery production process, as well as by the current, temperature, time, and accidental factors during the charging and discharging process. Therefore, the voltage values of each battery in a battery pack cannot be exactly the same.
Improvement measures
1
The battery company implements the following production process measures: ensuring consistency of all raw materials; monitoring the rheological properties of the slurry to prevent prolonged storage and ensure consistent rheology during coating; monitoring coating parameters, especially for lithium iron phosphate slurry, as the fine particles and poor processing performance of the slurry necessitate slowing down the coating machine speed during coating; proper detection of slurry viscosity; visual inspection of the electrodes; removal of defective electrodes; electrode weighing; comparison of battery quality before and after electrolyte injection; formation temperature; humidity control; establishing standards for all raw materials and strictly adhering to these standards for inspection and storage; consistent control of the production process; precise control of the consistency of the production process; strict statistical process control (SPC) of the process; ensuring each process operates within specified tolerances; and ensuring the process capability index follows the normal distribution of production parameters.
2
The battery pack matching process ensures that the battery packs use batteries of uniform specifications and models, guaranteeing the consistency of battery quality, especially initial voltage. Screening criteria include: voltage; internal resistance; battery formation data. There are many consistency evaluation methods, with the range coefficient method, standard deviation coefficient method, and threshold method being the most commonly used. Cluster analysis is combined with scientific classification based on the shape, distance, and area of the battery charge-discharge curves formed by various detection points within a time interval, thereby determining battery consistency. Based on capacity or voltage thresholds, calculations are performed on the shape of the charge-discharge curves, the distance between curves, and the area enclosed by the curves, selecting parameters that reflect curve consistency for judgment. Cells with curves that are close during charge-discharge, have small relative distances, small enclosed areas, and minimal inter-group differences are selected for matching, thus achieving optimal consistency matching.
3
Battery balancing management, from the perspective of the battery management system, monitors the parameters of individual cells during battery pack use, especially the voltage distribution when the electric vehicle is parked or driving. It helps to understand the development pattern of inconsistencies among individual cells in the battery pack and to adjust or replace cells with extreme parameters in a timely manner to ensure that the inconsistencies in battery pack parameters do not increase over time.
Prevent battery overcharging and minimize deep discharge. Ensure a good operating environment for the battery pack, maintaining a constant temperature, minimizing vibration, and preventing water, dust, and other contaminants from the battery terminals. Simultaneously, in terms of energy management and strategy, introduce practical battery pack energy management and balancing systems, formulate reasonable battery balancing strategies, and proactively intervene to reduce battery inconsistencies.
4
Battery thermal management: During battery use, differences in factors such as internal resistance and battery arrangement will cause differences in the battery's own temperature and ambient temperature during charging and discharging, which will directly lead to differences in its output performance.
The purpose of battery thermal management is to maintain the operating temperature of the battery pack within the optimal operating temperature range. Ensuring consistent temperature conditions between batteries guarantees consistent battery performance parameters. (Battery lifespan varies at different temperatures; the rate of degradation doubles for every 10°C increase in temperature.)
5
In terms of energy management, the control strategy aims to minimize the depth of battery discharge, provided the output power allows. Deep discharge of lithium-ion batteries leads to decreased consistency and reduced battery pack lifespan. Therefore, it's crucial to prevent both deep discharge and overcharging. Integrating a balancing circuit within the system can prevent overcharging of individual cells, and appropriately lowering the charging termination voltage can extend the battery pack's cycle life.
6
During other usage and routine maintenance, batteries with low measured capacity should be individually charged for maintenance to restore their performance. At regular intervals, the battery pack should be charged with a small current to promote its own balancing and performance recovery.
Regarding the operating environment, it's crucial to ensure a consistent and optimal environment for the battery pack, minimizing vibration and preventing contamination of the battery terminals by water, dust, or other contaminants. This aspect is generally difficult to implement in vehicles; it requires the battery system and vehicle controller to achieve.
