Abstract
Underground coal mines form single-headed tunnels during mining and excavation, necessitating the use of local ventilators to exhaust harmful gases such as methane, ensuring production safety. Therefore, the reliability of power supply for underground local ventilators is extremely demanding. This paper focuses on improving the reliability of power supply to underground local ventilation fans by configuring emergency energy storage power supplies, with a particular emphasis on researching the battery management system (BMS) of the emergency energy storage power supply unit.
Keywords: emergency energy storage power supply unit; underground local ventilation fan; battery management system; balanced control; equivalent circuit model
1. Introduction
The reliability of the power supply system for underground local ventilators is crucial for ensuring the continuity and safety of mining operations. Traditional power supply methods, such as the “three special-purpose devices and two lockups” approach, have certain limitations. Therefore, this paper proposes incorporating emergency energy storage power supply units to enhance the reliability of power supply to underground local ventilators. The research in this paper primarily focuses on the BMS of these emergency energy storage power supply units.
Table 1: Research Background and Significance
| Research Background | Significance |
|---|---|
| High reliability requirements for ventilators | Ensuring mining safety and production continuity |
| Limitations of traditional power supply | Improving power supply reliability through emergency storage |
| Research focus on BMS | Enhancing battery performance and management |
2. Overview of Emergency Energy Storage Power Supply Unit
2.1 Functional Design
The emergency energy storage power supply unit is designed based on the requirements of the power supply for underground local ventilators. It primarily includes a power conversion system (PCS) and a battery management system (BMS). The PCS is responsible for converting the energy from the storage battery to the required power form for the ventilator, while the BMS monitors and manages the battery’s state.
Table 2: Components and Functions of the Emergency Energy Storage Power Supply Unit
| Component | Function |
|---|---|
| PCS | Energy conversion between storage battery and ventilator |
| BMS | Battery state monitoring, protection, and management |
2.2 Connection Methods
There are two main connection methods for the emergency energy storage power supply unit: series connection and parallel connection. The parallel connection method is selected due to its higher reliability. In parallel connection, the storage device is connected in parallel with the local ventilator, allowing it to continue supplying power to the ventilator even if the main power source fails.
3. Battery Management System (BMS)
3.1 Monitoring and Protection
The BMS monitors the battery’s voltage, current, temperature, and other parameters to estimate parameters such as the state of charge (SOC) and detect potential faults. This information is crucial for protecting the battery from overcharging, over-discharging, and excessive temperatures.
Table 3: BMS Monitoring and Protection Functions
| Function | Description |
|---|---|
| Voltage monitoring | Ensures batteries are within safe voltage ranges |
| Current monitoring | Prevents overcurrent and short circuits |
| Temperature monitoring | Maintains optimal battery operating temperatures |
| SOC estimation | Provides accurate battery charge status |
3.2 Charge and Discharge Management
Appropriate charge and discharge strategies are implemented to control the battery’s state, enhancing its performance and lifespan. These strategies are based on real-time monitoring data and are designed to avoid overcharging and over-discharging.
3.3 Balanced Control
Due to inconsistencies among individual battery cells, balanced control is crucial for ensuring the overall performance and reliability of the battery pack. This paper proposes a grouped hierarchical active balancing control strategy based on the traditional Buck-Boost chopper circuit.
Table 4: Comparison of Balancing Methods
| Balancing Method | Description | Advantages | Disadvantages |
|---|---|---|---|
| Passive Balancing | Uses resistive elements to dissipate excess energy | Simple control | High energy loss |
| Active Balancing | Uses DC/DC converters to redistribute energy among cells | High efficiency, low energy loss | Complex control |
4. Equivalent Circuit Model for Battery
To accurately simulate the electrical characteristics of the battery, an equivalent circuit model is developed. The second-order RC equivalent circuit model is chosen based on its accuracy and simplicity. This model is validated using mixed pulse power characteristic (MPPC) tests and real-world driving cycles.
Table 5: Model Parameters and Identification Methods
| Parameter | Description | Identification Method |
|---|---|---|
| R0 (Ohmic resistance) | Internal resistance of the battery | MPPC test and parameter fitting |
| R1, C1 (Polarization resistance and capacitance) | Polarization effects | MPPC test and parameter fitting |
| R2, C2 (Diffusion resistance and capacitance) | Diffusion effects within the battery | MPPC test and parameter fitting |
5. SOC Estimation Algorithms
Accurate SOC estimation is essential for battery management. This paper investigates several commonly used SOC estimation methods, including the coulomb counting method, open-circuit voltage (OCV) method, and Kalman filter-based methods.
Table 6: Comparison of SOC Estimation Methods
| Method | Description | Advantages | Disadvantages |
|---|---|---|---|
| Coulomb Counting | Integrates current over time to estimate SOC | Simple and reliable | Depends on initial SOC and accumulates errors |
| OCV Method | Uses the relationship between OCV and SOC | Accurate at rest | Not suitable for dynamic conditions |
| Kalman Filter-based | Uses statistical models to estimate SOC | High accuracy and robustness | Computationally intensive |
6. Conclusion and Outlook
This paper proposes incorporating emergency energy storage power supply units to enhance the reliability of power supply to underground local ventilators. By researching the BMS of these units, we have developed a grouped hierarchical active balancing control strategy and a second-order RC equivalent circuit model for battery simulation. These contributions have significant implications for improving the reliability and safety of underground mining operations.
Future research can further optimize the BMS, explore advanced battery technologies, and investigate integration with renewable energy sources to create a more sustainable and reliable power supply system for underground local ventilators.