1. Introduction
Lithium iron battery (LiFePO4 battery) have become widely used in photovoltaic power systems due to their advantages such as small volume, large capacity, high energy density, long service life, and controllable pollution. However, in practical applications, LiFePO4 battery may not effectively adapt to the long-term floating charge work of DC power supplies. In power system applications, the power supply mode of LiFePO4 battery is that the battery pack is connected in parallel with an uninterruptible power supply to the load, and it needs to bear the power supply of the load, which may lead to abnormal output current. The abnormal state of the output current of the LiFePO4 battery pack is directly related to the stability and safety of the power system operation. Therefore, real-time and effective monitoring of its output current abnormal state has become an important part of the power system. This article proposes a monitoring method for the abnormal state of the output current of LiFePO4 battery in power system applications.
2. Lithium Iron Phosphate Battery Output Current Signal Collection
The current sensor collects analog signals. Therefore, the collected output current signal of the LiFePO4 battery needs to be converted from an analog signal to a digital signal. The conversion formula is , where is the converted output current signal of the LiFePO4 battery, is the output current signal of the LiFePO4 battery collected by the current sensor, and is a conversion parameter, usually taken as 1000. The collected monitoring samples are converted into data information by this formula and then stored for subsequent extraction and identification of abnormal characteristics of the output current of the LiFePO4 battery in power system applications.
3. Output Current Abnormal Feature Extraction
3.1 Noise Reduction Using Extended Kalman Filtering Technology
The wireless sensor used to collect the output current signal of the LiFePO4 battery is easily affected by factors such as wire electromagnetic waves, resulting in noise in the collected current signal. To ensure the accuracy of extracting abnormal characteristics of the output current, the extended Kalman filtering technology is used to process the current signal for noise reduction. Under the extended Kalman filtering theory, the output current signal of the LiFePO4 battery can be represented by a nonlinear dynamic equation:
where is the state equation of the output current of the LiFePO4 battery, is a nonlinear function, is the true state of the output current of the LiFePO4 battery in the power system, is the noise drive matrix, is the power system noise, is the monitoring equation of the output current state of the LiFePO4 battery, and is the monitoring noise, which is manifested as the current sensor error.
After obtaining the above equation, it is linearized according to the extended Kalman filtering idea. The first-order Taylor expansion of is used to obtain the linear state equation of the output current of the LiFePO4 battery. Then, the equation is extended to a multidimensional space to obtain the covariance corresponding to the noise in the equation. The obtained covariance is substituted into to eliminate the monitoring noise in , thus achieving the purpose of noise reduction.
3.2 Normalization to Correct Signal Errors
Considering that the output current characteristics of the LiFePO4 battery are affected by the incident angle of sunlight, temperature, and the distance between the Earth and the Sun, resulting in sampling residuals, the filtered current signal is normalized to correct the collected current signal values.
- Normalization of the influence of the incident angle of sunlight on the output current signal value of the LiFePO4 battery: The corrected output current value of the LiFePO4 battery is , where is the corrected output current signal value of the LiFePO4 battery, and is the incident angle of sunlight.
- Normalization of the influence of temperature on the output current signal value of the LiFePO4 battery: The corrected output current value of the LiFePO4 battery is , where is the output current signal value of the LiFePO4 battery corrected by the temperature factor, and is the temperature correction factor.
- Normalization of the influence of the distance between the Earth and the Sun on the output current signal value of the LiFePO4 battery: The corrected output current value of the LiFePO4 battery is , where is the output current signal value of the LiFePO4 battery corrected by the distance factor between the Earth and the Sun, and is the distance correction factor between the Earth and the Sun.
Through the above calculations, the monitoring signal residuals of the output current of the LiFePO4 battery are corrected, and the characteristic values of the output current state of the LiFePO4 battery are obtained.
4. Output Current Abnormal State Identification and Monitoring
Taking time as the abscissa and the extracted output current characteristic value as the ordinate, the waveform diagram and state diagram of the output current of the LiFePO4 battery are drawn. According to the constraint range of the output current, the output current error of the LiFePO4 battery is calculated as , where is the output current error of the LiFePO4 battery, is the maximum limit value of the output current of the LiFePO4 battery, and is the minimum limit value of the output current of the LiFePO4 battery.
According to the calculated output current error of the LiFePO4 battery, the abnormal state of the battery output current can be identified. If the calculated output current error of the LiFePO4 battery is greater than zero, the current battery output current exceeds the limit value, and lithium iron battery output current state is abnormal; if the calculated output current error of the LiFePO4 battery is less than zero, the current battery output current does not exceed the limit value, and the battery output current state is normal.
5. Experimental Demonstration
5.1 Experimental Preparation and Design
The designed method is set as the experimental group, and two commonly used methods, namely the DC ammeter method and the voltage integration method, are selected as the control groups, denoted as control group 1 and control group 2, respectively. Taking a certain power system as the experimental environment, this power system uses LiFePO4 batteries to build a power storage system, which contains 20 LiFePO4 batteries. The net weight of lithium iron battery is 85000g, the internal resistance is 175.45 mΩ, the charging current is 60A, lithium iron battery capacity is 200Ah, and the load voltage is 50.25V. According to the actual situation of this power system, 3 current sensors are prepared to collect the output current signals of the LiFePO4 batteries, and a total of 10000 monitoring samples are collected. The waveform of the output current of the monitored power system is basically consistent with the actual situation.
5.2 Experimental Results and Discussion
For the monitoring accuracy of the abnormal state of the output current, the undetected rate is selected as the evaluation index in the experiment. The higher the undetected rate, the lower the accuracy of monitoring the abnormal state of the output current. In this experiment, the number of monitoring samples is used as a variable, and the undetected rates of the three methods under different numbers of monitoring samples are calculated using a formula. The specific results are shown in the following table:
| Sample Number/Portion | Experimental Group Undetected Rate/% | Control Group 1 Undetected Rate/% | Control Group 2 Undetected Rate/% |
|---|---|---|---|
| 1000 | 0.53 | 6.52 | 10.26 |
| 2000 | 0.54 | 6.86 | 10.24 |
| 3000 | 0.55 | 6.94 | 10.35 |
| 1000 | 0.54 | 6.87 | 10.25 |
| 5000 | 0.56 | 6.85 | 10.42 |
| 6000 | 0.53 | 6.89 | 10.35 |
| 7000 | 0.54 | 6.75 | 10.64 |
| 8000 | 0.52 | 6.84 | 10.75 |
| 9000 | 0.55 | 6.88 | 10.86 |
| 10000 | 0.56 | 6.89 | 10.75 |
It can be seen from the table that in this experiment, the highest undetected rate of the experimental group is 0.56%, which is less than 1%, indicating that there is basically no problem of undetected abnormal states of the output current of the LiFePO4 battery in the experimental group; the highest undetected rate of control group 1 is 6.94%; the highest undetected rate of control group 2 is 10.86%. It can be seen that the experimental group has better monitoring accuracy.
6. Conclusion
This article combines the output current characteristics of LiFePO4 batteries and designs a new monitoring method in view of the shortcomings and defects of the current monitoring methods for abnormal output current states. This method effectively reduces the undetected rate of abnormal output current states and provides theoretical support for monitoring the abnormal output current states of power systems based on LiFePO4 batteries, which has certain practical and theoretical values.
In addition to the above core content, we can also further discuss some related aspects of LiFePO4 batteries to enrich the article.
6.1 Structure and Working Principle of LiFePO4 Batteries
LiFePO4 batteries are a type of lithium ion battery. The cathode material is lithium iron phosphate (LiFePO4), and the anode material is usually graphite. During the charging process, lithium ions move from the cathode to the anode through the electrolyte, and during the discharging process, lithium ions move from the anode to the cathode. The overall chemical reaction formula is:
This chemical reaction process enables LiFePO4 batteries to store and release electrical energy. The structure of LiFePO4 batteries usually includes a cathode, an anode, an electrolyte, a separator, and a casing. The cathode and anode are responsible for the storage and release of lithium ions, the electrolyte provides a medium for the movement of lithium ions, the separator prevents the short circuit between the cathode and the anode, and the casing protects the internal components of lithium iron battery.
6.2 Advantages and Disadvantages of LiFePO4 Batteries
- Advantages:
- High safety: The chemical structure of LiFePO4 batteries is relatively stable, and the oxygen release temperature is high, which reduces the risk of thermal runaway and explosion.
- Long cycle life: LiFePO4 batteries can maintain a relatively high capacity retention rate after multiple charge and discharge cycles, usually up to thousands of cycles.
- Good environmental compatibility: The materials used in LiFePO4 batteries are relatively environmentally friendly, and the production and use processes have less impact on the environment.
- High energy density: Although the energy density of LiFePO4 batteries is not as high as some other lithium-ion batteries, it is still sufficient for many applications.
- Disadvantages:
- Low conductivity: The conductivity of LiFePO4 itself is relatively low, which may affect the charge and discharge rate of lithium iron battery.
- Voltage plateau: The discharge voltage of LiFePO4 batteries has a relatively flat plateau, which may make it difficult to accurately estimate the state of charge of the battery.
6.3 Applications of LiFePO4 Batteries
LiFePO4 batteries have a wide range of applications due to their advantages. Some of the main applications are as follows:
- Electric vehicles: LiFePO4 batteries are used in some electric vehicles as power sources due to their high safety and long cycle life.
- Energy storage systems: In energy storage systems, LiFePO4 batteries can store electrical energy generated by renewable energy sources such as solar and wind power and release it when needed.
- Portable electronics: LiFePO4 batteries are also used in some portable electronics such as laptops and mobile phones due to their relatively small size and high energy density.
6.4 Future Development Trends of LiFePO4 Batteries
- Improvement of conductivity: Researchers are constantly exploring ways to improve the conductivity of LiFePO4, such as doping with other elements or using nanostructured materials. This will help to increase the charge and discharge rate of lithium iron battery.
- Enhancement of energy density: Efforts are being made to increase the energy density of LiFePO4 batteries to meet the increasing energy requirements of various applications. This may involve the development of new electrode materials or the optimization of battery structures.
- Intelligent monitoring and management: With the development of the Internet of Things and artificial intelligence, intelligent Intelligent monitoring and management.
With the development of the Internet of Things and artificial intelligence, intelligent monitoring and management of LiFePO4 batteries will become more important. This includes real – time monitoring of battery parameters such as voltage, current, and temperature, as well as intelligent control of the charge and discharge process to ensure the safety and efficiency of lithium iron battery.
In addition to the above aspects, there are also some other trends worthy of attention. For example, the development of recycling technologies for LiFePO4 batteries is crucial for environmental protection and resource conservation. As the number of LiFePO4 batteries in use increases, proper recycling methods need to be established to recover valuable materials and reduce waste.
Another trend is the integration of LiFePO4 batteries with other energy storage technologies or power generation systems. For instance, combining LiFePO4 batteries with supercapacitors can take advantage of the high power density of supercapacitors and the high energy density of LiFePO4 batteries, providing a more efficient energy storage solution. In the context of renewable energy systems, better integration with solar panels or wind turbines can improve the overall performance and stability of the power generation and storage system.
Moreover, research on the performance of LiFePO4 batteries under different environmental conditions is also being continuously carried out. Understanding how temperature, humidity, and other factors affect lithium iron battery’s performance can help in developing better battery management strategies and improving the reliability of battery applications in various environments.
In conclusion, the future development of LiFePO4 batteries is expected to focus on multiple aspects such as conductivity improvement, energy density enhancement, intelligent monitoring and management, recycling, integration with other technologies, and performance research under different conditions. These developments will not only contribute to the better performance and wider application of LiFePO4 batteries but also have a significant impact on the development of the energy industry as a whole.