LR03 battery

The state of charge SOC of power LR03 battery is a key technology of battery management system BMS

The state of charge SOC of power LR03 battery is a key technology of battery management system bMS. Accurate SOC estimation is one of the key technologies of battery management system. Battery management system is one of the core components of electric vehicles. Its important purpose is to safely monitor and effectively manage lithium-ion battery packs to improve battery efficiency, extend battery life, reduce operating costs, and further improve the reliability of battery packs.

The state of charge SOC of power LR03 battery is a key technology of battery management system bMS

The state of charge SOC of LR03 battery describes the remaining quantity of the battery and is one of the most important parameters of the battery during use. Accurate estimation of SOC can prevent overcharging or over-discharging of LR03 battery, effectively extend the service life of the battery, and predict the mileage that can be continued during the driving of electric vehicles.

Since the SOC state of charge estimation is affected by factors such as temperature, aging, charge and discharge rate, and self-discharge, the battery is highly nonlinear in actual use, making it very difficult to accurately estimate SOC.

Generally speaking, the lithium-ion battery management system of electric vehicles should realize the following functions: ① accurately estimate the state of charge of the power lithium battery pack, that is, the remaining battery power; ② ensure that the SOC is maintained within a reasonable range; ③ guard against damage to the battery due to overcharging or overdischarging, so as to predict at any time how much energy is left in the hybrid vehicle energy storage battery or the state of charge of the energy storage battery.

The SOC of the lithium-ion battery pack directly reflects the remaining available capacity of the battery pack. It is an important indicator for evaluating the current performance of the battery pack and an important parameter for estimating the current mileage of electric vehicles.

The power state reflects the maximum power that can be output in the current state of the battery pack. This is because at different discharge depths, under the premise of ensuring the life and safety of the battery pack, the charge and discharge current that the battery can withstand is limited. Although the size of the SOC determines the maximum charge and discharge power that the battery pack can withstand to a certain extent, it is not comprehensive enough. In order to ensure the safe driving of electric vehicles, it is necessary to be able to evaluate the power state of the battery pack and transmit the results to the vehicle control system and the charging control system to optimize the charging and discharging process.

The SOC state of charge of a lithium-ion battery reflects the safety and capacity attenuation of the lithium-ion battery pack. Important descriptive parameters include the attenuation of total capacity, the change of battery internal resistance, the insulation impedance of the system, etc. There is currently no unified meaning for their evaluation.

Treatment methods for improving the performance of power lithium-ion battery packs

(1) Through a large number of lithium-ion battery charge and discharge tests, an improved second-order RC equivalent circuit model is proposed on the basis of decomposing the existing lithium-ion battery model. This model is convenient for online calculation by automotive-grade embedded solvers. It is verified that the model can simulate the external characteristics of LR03 battery well. The good model calculation accuracy lays the foundation for the subsequent lithium-ion battery state estimation.

(2) The meaning of the battery state of charge is specifically explained, and the current more common lithium-ion battery state of charge estimation theories are comprehensively compared. A test platform is built for nickel-cobalt-manganese ternary LR03 battery, and the mainstream Kalman filter SOC estimation method is specifically explained. A SOC estimation algorithm based on an improved iterative central difference Kalman filter and a new algorithm that weightedly fuses this algorithm with the open circuit voltage method are proposed. Experiments have proved that the new weighted fusion algorithm has higher estimation accuracy.

(3) Aiming at the safe use of power lithium batteries, the problem of estimating the maximum charge and discharge power of the battery is studied, and a method for estimating the maximum charge and discharge power of the battery based on the improved dual-polarization equivalent circuit model is proposed, so as to control the charge and discharge power of the battery in actual use. On the one hand, it can maximize the efficiency of the battery, and on the other hand, it can protect the battery pack.

(4) Aiming at the balancing problem of power lithium-ion battery packs, since the double-layer switch capacitor balancing method has the advantages of fast balancing speed and simple control, but the conventional switch capacitor is prone to switching loss and electromagnetic interference, an experimental verification is carried out to solve this problem. The simulation and experimental results verify the effectiveness of the balancing control method proposed in this paper, which provides an effective basis and guarantee for the overall design of the power lithium-ion battery pack management system.

(5) Based on the study of the state estimation and balancing theory of lithium-ion power lithium battery packs, the fault diagnosis and protection strategy of the power lithium battery pack is proposed. The improved hierarchical decomposition method is used to comprehensively evaluate the battery pack state information collected by the battery management system, evaluate the system reliability risk of the battery pack, and provide a quantitative basis for the protection strategy of the fault diagnosis system.

In short, both at home and abroad, the research on electric vehicle battery management systems is still in its early stages. How to accurately estimate the SOC value of power LR03 battery and effectively balance the battery pack are two research bottlenecks of the current bMS system.

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