Battery pack status monitoring principle
Voltage monitoring
The primary task of a Battery Management System (BMS) is to accurately monitor the voltage of each individual cell in the battery pack. This is because a battery pack consists of multiple cells connected in series or parallel, and the voltage characteristics of each cell can vary due to factors such as manufacturing processes and operating environments. If the voltage of a cell is too high or too low, it may indicate problems such as overcharging, over-discharging, or internal malfunctions. The BMS uses a high-precision voltage acquisition circuit to collect the voltage data of each cell in real time and transmits this data to the central control unit. For example, in common lithium iron phosphate battery packs, the normal operating voltage range of a single cell is generally between 2.5V and 3.65V. Once the BMS detects that the voltage of a single cell exceeds this range, it will immediately issue a warning signal and take corresponding measures, such as adjusting the charging or discharging strategy, to prevent battery performance degradation.
Current monitoring
Accurate monitoring of battery pack charging and discharging current is crucial for a Battery Management System (BMS). The magnitude of the current directly affects the battery's charging and discharging rate, energy conversion efficiency, and battery life. BMS typically uses Hall effect current sensors or high-precision shunts to measure the battery pack current. During charging, monitoring the current ensures that the charger's output current matches the battery's charging characteristics, preventing damage from excessive current. During discharging, monitoring the current allows for real-time calculation of the battery's remaining capacity and enables the BMS to adjust the battery's discharge power according to the vehicle's driving needs. For example, when an electric vehicle accelerates, the BMS quickly adjusts the battery output based on the instantaneous high current demanded by the motor, ensuring a stable power supply to the vehicle while preventing battery damage due to overcurrent.
Temperature monitoring
Battery performance is closely related to temperature; excessively high or low temperatures can severely impact charging and discharging efficiency, lifespan, and safety. The Battery Management System (BMS) monitors the temperature at different locations within the battery pack in real time by evenly distributing multiple temperature sensors. Generally, the optimal operating temperature range for lithium batteries is between 20°C and 40°C. When the temperature exceeds this range, the BMS activates the appropriate thermal management system. In high-temperature environments, the thermal management system may lower the battery temperature through cooling fans or coolant circulation; in low-temperature environments, it may use heating wires or heat pumps to raise the battery temperature, ensuring the battery always operates within a suitable temperature range, extending battery life, and improving battery performance.
Battery state estimation principle
Remaining battery capacity (SOC) estimation
Accurately estimating the remaining battery capacity (State of Charge, SOC) is one of the core functions of a Battery Management System (BMS). SOC is similar to the fuel gauge in a gasoline car, providing the driver with information about the remaining battery energy to help plan their trips. There are several methods for BMS to estimate SOC, including the ampere-hour integration method, the open-circuit voltage method, and the neural network method. The ampere-hour integration method calculates the change in SOC by integrating the battery's charging and discharging current, but this method has accumulated errors and requires periodic calibration. The open-circuit voltage method estimates SOC based on the correlation between the battery's open-circuit voltage and SOC, offering high accuracy, but requires the battery to be idle for extended periods, limiting its application in actual vehicle operation. The neural network method uses a large amount of battery charging and discharging data to train a neural network and build a battery model to estimate SOC. It has high accuracy and adaptability, and can comprehensively consider the influence of multiple factors on SOC, and is currently widely used in advanced BMS systems.
State of Health (SOH) Assessment
Battery State of Health (SOH) reflects the degree of performance degradation of a battery compared to its initial condition, and is an important indicator of its remaining lifespan. The Battery Management System (BMS) assesses SOH by monitoring parameters such as internal resistance, capacity, and charge/discharge efficiency, and comparing these parameters with those in the battery's initial state. For example, as the number of battery cycles increases, internal resistance gradually increases, and capacity gradually decreases. The BMS monitors these changes in real time and uses mathematical models to calculate the battery's SOH value. When the SOH value falls below a certain threshold, the BMS will remind the user to replace the battery promptly to ensure normal vehicle operation and safety.
in conclusion
The Battery Management System (BMS) for pure electric vehicles achieves refined management of the power battery through a series of control principles, including precise monitoring of the battery pack's state, accurate estimation of battery status, and comprehensive safety protection. It not only ensures the safe and reliable operation of the battery and extends its lifespan but also improves the performance and user experience of pure electric vehicles. With the continuous development of battery technology and automotive electronics technology, the control principles of the BMS will be continuously optimized and improved, providing solid technical support for the vigorous development of the pure electric vehicle industry. In the future, the BMS is expected to achieve more intelligent and efficient management, further propelling pure electric vehicles to a new stage of development and playing a more important role in the global green mobility sector.
