The role of battery impedance in battery management systems
- The principle of battery impedance
- Model of battery impedance
- Acquisition of battery impedance
- Application of impedance
- Problems faced by studying battery impedance
As an important characteristic parameter of an electrochemical system, battery impedance has long been considered as one of the most powerful electrochemical analysis tools.
The battery impedance reflects the resistance to the movement of charged particles within the battery. Using battery impedance can provide a more comprehensive grasp of the state of the battery, thereby providing support for battery management.
The principle of battery impedance
Battery impedance is an important characteristic of linear two-port networks. As a strongly nonlinear and time-varying system, the battery impedance needs to be obtained under the conditions of causality, stability, and linearity, otherwise the obtained battery impedance is difficult to analyze or loses physical meaning.
Therefore, in general, after the battery is fully static, a weak disturbance without bias is applied to the positive and negative electrodes (such as the applied disturbance voltage or response voltage is about 10mV) to obtain the battery impedance.
Lithium-ion battery is a very complex electrochemical system, which includes many electrochemical and physical processes, mainly including solid-liquid phase diffusion process, solid-liquid phase conductance process and interface process.
Charged particles, including lithium ions, participate in these processes. These processes have different time constants and thus dominate the battery impedance in different frequency intervals on the battery impedance spectrum.
In the low-frequency region, it is dominated by the slowest ion diffusion process. The mid-high frequency impedance is dominated by the electrochemical reaction process of ion intercalation. In the high-frequency region, it is mainly dominated by the SEI impedance.
The charge transfer of the solid-liquid phase determines the ohmic resistance. Frequency is dominated by parasitic inductance such as wires and current collectors. The corresponding relationship between EIS and different processes enables it to characterize the characteristics of different processes, so EIS has rich information content.
The difference from internal resistance
As another important characteristic parameter of batteries, the internal resistance of a battery is also often measured in tests. The definitions of internal resistance and impedance are different, and they are two different test methods.
Model of battery impedance
Electrochemical impedance model
Based on the porous electrode theory, the simplified P2D model and SPM model are widely used to describe the main physical and chemical processes inside the battery.
In the P2D model, the positive and negative solid phase particles are equivalent to spherical particles, and the electrode process of the main solid-liquid phase and its interface is included in the electrode thickness direction and particle radius direction, which can accurately simulate the battery characteristics.
Compared with the P2D model, the SP model is simpler, and the positive and negative electrodes are equivalent to a spherical particle, which often ignores the solid-liquid phase conduction and liquid phase diffusion process of the battery. The effect of the neglected process on the potential is described by the resistance of the lumped parameter.
Equivalent circuit model
The equivalent circuit model uses a combination of resistance-capacitance elements and constant-phase angle elements to obtain the broadband battery impedance. These components generally correspond to the electrode process inside the battery and are used to equivalent the battery impedance of this part.
The equivalent capacitance of the membrane is generally described by an ideal capacitance or a constant phase angle element (CPE) that considers the diffusion effect of a porous electrode. The literature also reported two methods of defining CPE (Pauliukaite et al. 2010).
The Weber elements describing the diffusion process also have three different forms according to the boundary conditions of the mechanistic process.
So far, a lot of battery equivalent circuit models have been proposed to describe the battery impedance. Compared with the electrochemical impedance model, the equivalent circuit model is simpler and more suitable for control-oriented applications. However, due to the lack of physical meaning, the components are equivalent, resulting in insufficient accuracy and universality of the model.
Different equivalent elements have obvious battery impedance characteristics, so it is easy to choose which equivalent element. The key is to determine the number of R-C or R-CPE parallel links. Links with different time constants are considered to correspond to different processes inside the battery.
The DRT analysis method can determine the number of parallel links to be selected by judging the time constant distribution in the battery impedance spectrum, thereby helping to determine the equivalent circuit model for analyzing battery impedance.
Acquisition of battery impedance
The battery impedance can be obtained by estimating the parameters of the equivalent circuit model under dynamic conditions.
At the same time, in order to obtain the broadband battery impedance, the identification method in the broadband range has also been studied and reported.
In the estimation of SOC, SOH, etc. of the battery, the integer-order equivalent circuit model obtained from the resistance-capacitance element is often used.
However, a large number of studies have found that the integer-order equivalent circuit model is difficult to accurately describe the battery voltage such as lithium ion battery voltage and current characteristics, especially in the frequency domain.
For example, such models are difficult to describe the low-frequency diffusion impedance where the battery impedance spectrum approximates a straight line. Moreover, due to the dispersion effect, the ideal R-C link is often a good description of the battery impedance characteristics of the middle and high frequency regions.
Some studies have used many RC parallel links to describe these characteristics. However, this increases the complexity of the model and the number of parameters to be identified, which makes parameter identification difficult.
Due to the time-varying and nonlinear nature of battery impedance, the fractional order model parameters are not static.
In particular, the change of the fractional order with the operating conditions and states will lead to changes in the structure of the time domain model converted from the fractional order, which is also a major challenge for the application of the fractional order in complex operating conditions.
Measurement is a more direct method of obtaining battery impedance. When the electric vehicle is running, the working condition and state of the battery are changing all the time, and it is difficult to guarantee the linearity, stability and causality conditions of impedance measurement at this time.
Most of the battery impedance measurements reported in the literature are done during parking. At this time, the uneven temperature distribution in the battery pack, the balanced current of the battery cells, and the ripple of the converter are all controllable or even negligible.
To measure battery impedance, a system with excitation generation, voltage and current signal measurement, and battery impedance calculation is required.
Application of impedance
Temperature has a great influence on the performance of the battery. Working at an unsuitable temperature, the battery will face life and safety issues. Therefore, for BMS, real-time monitoring of battery temperature is crucial for efficient management.
Temperature measurement is most straightforward with sensors. Most of this method can only realize the temperature measurement of the tab or the surface. However, during high-rate charging and discharging, the surface temperature is very different from the internal temperature of the battery.
Relying on surface temperature monitoring still faces safety concerns due to excessive internal temperatures. Therefore, internal temperature estimation is widely studied. Temperature estimation based on battery impedance is an important technical route.
Most of the existing research is to obtain battery impedance under quasi-steady-state conditions for temperature estimation. However, the temperature change is often more severe under dynamic conditions.
The influence of dynamic working conditions on temperature characterization of battery impedance angle and the applicability of this method in dynamic working conditions are still lack of sufficient research.
State of charge estimation
Accurate estimation of SOC is of great significance to prevent battery overcharging and over-discharging. For the model-based SOC estimation method, its estimation accuracy is often affected by the model accuracy and parameter identification algorithm.
In particular, for lithium iron phosphate batteries, for example, it has a very flat SOC-OCV curve, which brings greater challenges to model-based SOC estimation. Lithium iron phosphate battery is very common in China and there is a top 10 lithium iron phosphate power battery manufacturers in China article for you to help know more about this industry.
Battery impedance, as a quantity closely related to the overcharge of the internal electrodes of the battery, is also very closely related to SOC. Many impedance-based SOC estimation methods have been proposed.
Aging state estimation
Estimation of battery aging state is of great significance to battery online management and decommissioning residual value evaluation. Battery aging is a complex phenomenon involving many processes.
Battery impedance can reflect the internal electrode process characteristics, and the use of battery impedance for SOH estimation has been widely reported. Using ECM to analyze battery EIS at different aging stages to estimate SOH is a common technical route.
Overcharge and overdischarge diagnosis.
By using ECM to fit the EIS in the case of overdischarge, it can be found that the ohmic resistance, load transfer resistance, SEI resistance and Warburg resistance have all changed greatly. Further through the three-electrode experiment, it is found that although the negative electrode contributes little to the battery impedance, it has a great influence on the battery impedance in the case of over-discharge.
It is also found in the literature that when the battery is overcharged, the positive electrode impedance and the high-frequency negative electrode impedance have changed significantly.
Diagnosis of lithium analysis.
Lithium precipitation is easily induced during high-rate charging or low-temperature charging, which is an important reason for the deterioration of battery safety and life. It is of great significance to realize the online detection of lithium analysis.
The study found that the decrease in battery impedance after high-rate charging is related to lithium precipitation. And the change of the trend of the 3s DC resistance with the change of SOC during the charging process is also related to the lithium analysis.
Internal short circuit diagnosis.
Internal short circuit is one of the important reasons for battery thermal runaway. The study found that the greater the leakage current, the impedance of the low-frequency diffusion section of the battery will bend to the real axis and the impact will be more obvious, which provides an idea for the diagnosis of internal short circuit.
Problems faced by studying battery impedance
Through the review of the progress in battery impedance modeling, acquisition and application, it can be seen that battery impedance has broad application prospects in battery management research, but there are still many engineering and scientific problems to be solved, as follows:
The electrochemical impedance model is complex and has many parameters, and the equivalent circuit model is more suitable for control-oriented applications.
However, the form of the equivalent circuit model is ever-changing, and it is necessary to choose a reasonable battery impedance model with clear physical meaning and precision and propose a control-oriented parameter identification method to realize the analysis of the obtained battery impedance.
The battery impedance can be obtained by estimation and measurement. The former is challenged by model accuracy, harmonic abundance of operating conditions, and multi-time scale identification.
The latter is a more direct and effective method, but it still needs to overcome technical problems such as high-precision, high-speed analog front-end and low-cost, high-compatibility system implementation.
The battery impedance is very sensitive to battery status and faults, which also makes the battery impedance have a wide range of application scenarios. A lot of research has been carried out so far.
However, it is still necessary to further reveal and remove the influence of other factors on the characteristic impedance in state estimation or fault diagnosis to improve the applicability to complex vehicle conditions.