Wholesale custom household energy storage battery power wall lithium battery
Does Lifepo4 battery wall need consistency
Time:Nov 09, 2022
Does the lifepo4 battery wall need consistency? The answer is yes. The consistency of individual SOC largely determines the discharge capacity of the battery pack. Balanced charging makes it possible to achieve similar initial SOC platforms for individual discharge, which can improve discharge capacity and discharge efficiency (discharge capacity/group capacity). The equalizing mode during charging refers to the equalizing of the power battery during charging. Generally, the equalizing starts when the single battery voltage reaches or is higher than the set voltage. Overcharging is prevented by reducing the charging current.
According to the different states of the single battery in the battery pack, through the 5kwh lithium battery pack equalizing charge control circuit model and the equalizing circuit to fine tune the charging current of the single battery, a equalizing charge control strategy that can not only realize the rapid charging of the battery pack, but also eliminate the impact of the inconsistency of the single battery on the cycle life of the battery pack is proposed. Specifically, through the switch signal, the overall energy of the lithium ion battery pack is supplemented to the single battery, or the energy of the single battery is converted to the overall battery pack. During the charging process of the battery pack, by detecting the voltage value of each single battery, when the voltage of the single battery reaches a certain value, the equalization module starts to work. Shunt the charging current in the single battery to reduce the charging voltage, and the separated current will feed back the home battery energy storage to the charging bus through module conversion to achieve the purpose of equalization
Good combination can not only improve the utilization rate of battery cells, but also control the consistency of individual cells. It is the basis for achieving good discharge capacity and cycle stability of battery packs. However, the dispersion of AC impedance of battery cell capacity with poor configuration will increase, which will weaken the cycle performance and usable capacity of battery pack. Someone proposed a method of battery grouping based on the characteristic vector of the battery. This eigenvector reflects the similarity between the charging and discharging voltage data of single battery and that of standard battery. The closer the charge discharge curve of the battery is to the standard curve, the higher its similarity, and the closer the correlation coefficient is to 1. This matching method is mainly based on the correlation coefficient of individual voltage, combined with other parameters for matching, which can obtain a better matching effect. The difficulty of this method lies in the need to provide standard battery eigenvectors. Due to the limitation of production level, there must be differences between each batch of batteries. It is very difficult to obtain a set of eigenvectors suitable for each batch of batteries.
The quantitative analysis method is used to analyze the difference evaluation method between single batteries. Firstly, the key points that affect the battery performance are extracted by mathematical methods, and then mathematical abstraction is carried out to realize the comprehensive evaluation and comparison of battery performance. The qualitative analysis of battery performance is transformed into quantitative analysis, and a simple method that can be operated practically is proposed for the optimal allocation of battery pack's comprehensive performance. A comprehensive performance evaluation system based on battery screening and matching is proposed. Combining subjective Delphi scoring with objective grey correlation degree calculation, a multi parameter grey correlation model of battery is established, which overcomes the unilateralism of taking a single index as the evaluation standard and realizes the performance evaluation of power type power battery. The correlation degree obtained from the evaluation results provides a reliable theoretical basis for the later screening and matching of battery.
The dynamic characteristic matching method is mainly used to realize the matching function according to the charging and discharging curve of the battery. Its specific implementation steps are to first extract the characteristic points on the curve to form a feature vector. The distance between the feature vectors of each curve is used as the matching index. The curve classification is achieved by selecting a suitable algorithm, and then the battery matching process is completed. This assembly method takes into account the performance changes of the lifepo4 powerwall battery during operation. On this basis, select other appropriate parameters for battery grouping, and then select the batteries with more consistent performance

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