a study of the influence of measurement timescale on internal resistance characterisation methodologies for lithium-ion cells - lifepo4 battery pack

The power capability of the lithium ion battery is determined by its resistance, which varies with the state of the battery (such as temperature, charging state and health state.
Therefore, it is essential to characterize the resistance when defining the operating boundary of the battery, estimating its performance, and tracking its health status.
There are many techniques used to estimate battery resistance, including the use of DC pulse current signals such as pulse power testing or hybrid pulse power representation (HPPC)tests;
I. using AC current signalse.
Electrical impedance spectrum (EIS)
Use Pulse
Multi-sine measurement.
According to the existing literature, these techniques are considered to produce different resistance values.
In this work, we apply these techniques to 20ah ah LiFePO/C6 bag batteries and compare them using the results.
The results show that the calculated resistance strongly depends on the time scale of the technology adopted, and when the time scale matches, the resistance obtained through different technologies will be aligned.
Furthermore, given that EIS is a perturbation representation technique utilizing the perturbation frequency spectrum, we show that the resistance estimated by any technique can be identified from EIS by matching the schedule of EIS, high credibility is achieved.
From consumer goods to electric vehicles and renewable energy storage systems, batteries play an important role in powering modern technology.
It is important that the battery is able to provide and receive power safely, reliably and efficiently and store energy as needed.
The performance and efficiency of lithium-ion batteries depend largely on the resistance of the electro-chemical system.
With the aging of cells, this efficiency becomes worse and worse by storage and circulation.
Therefore, understanding and understanding of battery resistance is critical to defining battery performance under different battery states and operating conditions.
Internal resistance is also a key indicator for defining health status (SoH)
For lithium ion batteries.
Battery resistance also affects the performance of the entire battery system.
Battery system in electric vehicles and other applications (EVs)
Use a large number of units connected in series and in parallel.
The unbalanced system with different unit resistors limits the power transmission capability in series.
In parallel arrangement, significant differences in cell resistance lead to non-
The uniform current load in the package results in a temperature gradient, resulting in different degrees of battery degradation.
In addition to the thermal gradient in the battery pack, due to uneven local current distribution under operating conditions, the thermal gradient can also be developed along the electrode stack and the normal electrode stack, or internal manufacturing defects.
This non-uniformity leads to local heating, resulting in the local battery temperature "hot spot" approaching the value that the separator can melt, resulting in heat out of control.
The internal defects that cause this local hot spot are related to the formation of local films (SEI layer)
Therefore, there are local differences in resistance.
Traditionally, the measurement technology is either DC (DC)
Or AC (AC)
Calculate the load of DC resistance (
Large current resistance)
Or AC resistance (
Small signal resistancerespectively.
In complex electro-chemical systems such as Li-
Ion batteries, the process of electrochemistry, the microscopic structure of the electrodes and the complex transmission phenomena all help to improve the internal resistance of the batteries.
In addition, the state of the battery, that is, the charging state of the battery (SoC)
Temperature and SoH affect the resistance of the measurement.
Performance of a given Li-
The ion battery depends on SoC, temperature and SoH, and the test used to derive the resistance is designed to keep the SoC, temperature and SoH constant during the test.
Therefore, the measured resistance value will depend on the remaining degrees of freedom: the duration of the measurement (timescale)
Measurement, which is related to the potential electrochemical processes involved.
The pulse power test usually has a pulse length of 1-30 seconds;
Electron transfer, ion transfer, and ion diffusion will help the resistance on this time scale.
On the other hand, historically, the AC resistor measures the resistor using a 1 khz sine AC signal.
According to specific battery technology, at such a large frequency, the battery will be dominated by inductive or conductive behavior.
Electrical impedance spectrum (EIS)
It is a disturbance representation technique using the perturbation frequency spectrum, which reveals the potential electro-chemical process in a wide frequency range.
Compared to DC pulses, the signal amplitude used in EIS is relatively low, so the resistance measured with this technique is sometimes called a small signal resistor.
Omar's recent work
Indicates that in addition to SoC and temperature, the current amplitude also affects the battery resistance.
In order to consider the current correlation, the pulse power representation method uses a series of discharge and charge current pulses that increase C-
For pre-
Define SoC and temperature.
In order to better represent the frequency bandwidth in the application, vidanag.
A new signal design technique is proposed to generate pulse.
Compared to the standard pulse power test, multiple sine signals are more dynamic in magnitude and frequency, and have been shown to better predict battery performance when subsequently applied to battery models running using real-world duty cycles.
Although it is naively believed that the internal resistance of the battery is the same no matter what technology is adopted, some authors have found that in practice, the resistance changes with the measurement technology used. Schweiger .
Trying to classify this in their study based on 2 Ah cells.
They use pulse power method, EIS technology and joules heating (
Heat loss method.
In the latter case, the heat measured using the Heat Meter-Under circulation-is fully attributed to the Joules heating;
The resistance is then calculated by equating the heat generated to iR.
In this technique, reversible entropy heat, side reaction and mixed heat are ignored, which proves important at low SoC.
In addition, the technology is complex and costly to use in applications such as thermal management system design, and subsequent results have great uncertainty.
This limits its widespread use in estimating internal resistance.
More importantly, schwegg.
The conclusion is that due to the complex electrical properties of the battery, the AC impedance measured from the EIS test cannot be directly compared with the pulse power test, without providing a further analysis of the root cause.
This may not necessarily work;
Differences between these technologies may have different potential mechanisms, which have been studied as part of this study.
Recent work at Waag.
, EIS technology and resistance measurement using a single charge-
Application of discharge pulse pairs to study the change of resistance in battery life with SoC, temperature and current.
The resistance calculated by these two techniques highlights the difference, and the author attributes the difference to the non-
Linearity of electrolytic devices based on theoretical understanding developed for leadacid batteries.
Except for Schweig's work. and Waag .
Many other published works use more than one technique for measuring resistance.
For example, aging research uses a variety of techniques to measure resistance rise.
Given that battery testing is costly, time-consuming, and can lead to unnecessary aging, feature testing should be minimized to the point where technology that does not provide unique data becomes redundant.
Since Schweig's work
The existing resistance measurement technology has been updated, new technologies such as pulse
A multi-sine method is proposed. Any up-to-
Therefore, the rigorous analysis of these methods is also of great value to the research community.
The consistency of technology is crucial for future aging research;
Given that EIS and pulse current testing are often used together, it is important to be able to compare these complementary technologies accurately.
The main purpose of the above study has nothing to do with the technique of measuring the resistance of the battery, so no differences or similarities are considered, between the technique itself and the physical meaning of the resulting resistance measurement.
Therefore, in this work, a subset of established technologies is proposed.
Each technique derives and explains in detail the various processes that lead to cell resistance.
Each technique is then applied to 20 ah LiFePO/C bag cells and the results are used as a basis for comparison between different techniques.
The results show that the time scale of the measurement technique determines the resistance estimation resulting from it.
Therefore, the resistance generated by any technology can be estimated purely from EIS data.
Given that EIS technology can easily attribute time scales to physical processes, it has been suggested that EIS technology may be sufficient testing to determine battery resistance without further testing.
The next section outlines the theoretical background of different methods of resistance measurement.
Subsequently, a test matrix was proposed to measure the resistance of the cell by using all the identified techniques and the results were given in the discussion.
Finally, the overall contribution of this study is summarized.