Development Status of BMS Lithium Battery Development

The primary solution to BMS is security issues and needs to have:

1) Overcharge protection, that is, when charging, it must be terminated in time when the voltage exceeds.

2) Overdischarge protection, that is, termination of discharge when any single unit voltage in the group is below the over-discharge threshold.

3) Overcurrent and short-circuit protection, the main function is that when an accident causes an excessive discharge current or even a short circuit, the output can automatically close and enter the self-locking state.

At present, these basic protection functions can be implemented by professional lithium electric protection chips, such as special lithium electric protection ICs such as TI and Lingte. Balance is the core issue of battery management, and research at home and abroad is very active. The specific realization method of equilibrium can be divided into dissipation type and non-dissipation type according to the energy treatment method. The dissipation type equilibrium achieves equilibrium by consuming excess energy by shunting the resistors at both ends of the battery. This method has simple implementation. The advantages of low cost, However, there are thermal management problems. Non-dissipative equilibrium refers to the transfer of energy between the monomers in the battery to achieve equilibrium. There are many circuit topologies in this equilibrium method, but there are often problems such as complex circuits, low equilibrium efficiency, and slow equilibrium speed. It limits its use in large capacity areas such as electric vehicles and energy storage.

Due to the complexity of the structure and model, the SOC characteristics of lithium batteries are affected by many uncertain factors, such as charging and discharge ratio, temperature, and number of charged and discharged times. Therefore, how to accurately estimate the SOC based on measurable parameters is currently a problem that needs to be solved. At present, the commonly used SOC estimation methods in the industry include discharge method, time integral method, open circuit voltage method, and Qiaermanlvbofa. The discharge test method is to discharge the battery constant current and count the amount of electricity emitted until its end voltage reaches the discharge cut-off voltage. The method is reliable and suitable for different types of batteries. However, the disadvantage is that the test process is long and can not be estimated online in real time. Therefore, this method is generally used to determine the parameters of the battery model. The Anshi integral method calculates the SOC by calculating the capacity that flows in or out of the battery when charged and discharged over a period of time. After calculating the SOC value, it compensates it according to the environmental temperature and the charge and discharge ratio. This method has the problem of integral accumulation error and initial value prediction. Open circuit voltage method uses a certain curve correspondence between the open circuit voltage of the battery and the SOC to estimate the SOC. However, in order to measure the open-circuit voltage, the self-recovery effect of the battery needs to be eliminated and it takes a long time. Therefore, the open-circuit voltage method can not estimate the SOC in real time, but it can provide the initial SOC value for other algorithms. Kalman filter is a method to solve the filtering problem in discrete equations through recursive iteration. It can estimate the state value of the current moment by recursion based on the state of the previous moment. Therefore, we can use the previous state parameter of the battery to estimate the current state of operation at the current, that is, the current of the battery, the operating temperature, and other parameters as the input of the system, the SOC as the state parameter, the battery voltage as the output, and the Kalman filter as the Lithium battery SOC estimate. At present, Qiaermanlvbofa still stays in the theoretical simulation stage, and there are few reports on practical applications. The monitoring of temperature is mainly achieved by analog / digital temperature sensors. Thermistors can be used for cost-limited situations.

At present, the United States and Japan are at the forefront of the world in the research and production of BMS. The United States A123 System first developed the iron lithium energy storage system and built the world's largest 32MWh lithium energy storage power plant in 2011. At present, domestic research in the field of energy storage power station BMS has also begun. For example, the special BMS produced by Ligao Power Station adopts a three-level system architecture to achieve battery monitoring and can be used for large, medium and small energy storage power.

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