The core function of a Battery Management System (BMS) is to ensure battery safety, extend lifespan, and optimize performance. Its working logic is neither completely dependent on current calculation nor solely based on voltage calculation, but achieves precise management through the collaborative monitoring and comprehensive analysis of the two. The following is the specific logical relationship:
1、 The core application of current calculation
State of Charge (SOC) estimation
BMS calculates the remaining battery capacity by integrating the charging and discharging currents of the battery through real-time monitoring of current (Coulomb counting method). However, the small errors of the current sensor will accumulate over time and need to be corrected in conjunction with parameters such as voltage and temperature.
Battery Health Status (SOH) Assessment
Long term current charging and discharging cycles can cause battery capacity degradation. By comparing the difference between the nominal capacity and the actual charge and discharge current, the degree of battery aging can be indirectly evaluated.
Overcurrent protection
Monitor the peak instantaneous current (such as short circuit, abnormal load) and cut off the circuit to prevent thermal runaway.
2、 The core application of voltage calculation
Balanced management of individual battery cells
BMS monitors the voltage differences of each individual cell, identifies imbalances (such as overcharging/overdischarging of a certain cell), triggers active or passive balancing circuits, and ensures the consistency of the battery pack.
Security threshold control
Batteries with different chemical systems (such as lithium-ion and lithium iron phosphate) have strict voltage operating ranges (such as 3.04.2V). BMS triggers charging and discharging termination based on voltage threshold to avoid battery damage caused by overvoltage or undervoltage.
Open circuit voltage (OCV) calibration SOC
In the static state of the battery, there is a corresponding relationship between voltage and SOC (such as a lithium battery SOC of 50% corresponding to about 3.7V). BMS utilizes this feature to periodically calibrate the cumulative error of Coulomb counting method.
3、 The collaborative logic of current and voltage
Complementarity under dynamic operating conditions
During high rate discharge, a sudden increase in current may cause a voltage drop (polarization effect), and BMS needs to comprehensively determine whether to trigger protection.
In low-temperature environments, the internal resistance of the battery increases, and voltage fluctuations become more significant at the same current. Therefore, the SOC algorithm weight needs to be adjusted.
Multi parameter fusion algorithm
Modern BMS adopts algorithms such as Extended Kalman Filter (EKF) and neural networks to input parameters such as current, voltage, temperature, and internal resistance into dynamic models, achieving higher accuracy in state estimation.
4、 Comparison of actual application scenarios
|Scenario | Current dominant | Voltage dominant|
|Electric vehicle acceleration/braking | Monitoring instantaneous current to control output power | Monitoring voltage drop to prevent single unit over discharge|
|Static balancing of energy storage system | Current used for balancing energy transfer between modules | Voltage used to determine balancing trigger conditions|
|Fast charging process | Real time regulation of charging current to avoid thermal accumulation | Determine charging cut-off point based on voltage slope (dV/dt)|
The essence of BMS is a multidimensional data fusion system:
Current reflects the real-time dynamics of energy flow and is a "process type" parameter;
Voltage represents the instantaneous energy state of a battery and is a "result type" parameter;
Only by combining temperature, internal resistance, and other data can a complete battery management model be constructed. Relying solely on a single parameter can lead to functional failure (such as the inability to distinguish between static SOC and load fluctuations based solely on voltage, and the inability to correct cumulative errors based solely on current). Therefore, the design of BMS needs to follow the core principles of "monitoring dual parameters, cross validation, and dynamic correction".