Storage battery capacity online dynamic estimation method based on impact load response characteristics

Abstract

The invention discloses a storage battery capacity online dynamic estimation method based on impact load response characteristics. The storage battery capacity online dynamic estimation method comprises the steps of: keeping carrying out online real-time monitoring on a voltage, a current and a temperature of a battery; and when an impact load occurs, i.e., when an instantaneous increase amplitudeof a current of the storage battery is greater than a preset value, transmitting storage voltage, current and temperature data acquired during the load sudden change to an online estimator, by a storage battery capacity online estimation algorithm fusing wavelet analysis with a cerebellar model neural network, estimating surplus capacity of the storage battery in real time. According to the invention, the storage battery does not need to be subjected to long-time full charge and full discharge; other harmonic signals also do not need to be actively injected into the storage battery; by directly utilizing the voltage, current and temperature data of the battery, which is monitored in real time under the action of the impact load, the capacity of the storage battery can be rapidly and accurately estimated in real time; the storage battery capacity online dynamic estimation method is suitable for an uninterrupted power system; battery maintenance cost is reduced; a problem of reduction or failure of the capacity of the storage battery is found timely; and reliability of the system is improved.

Description

Technical field [0001] The invention relates to the field of battery detection, in particular to an online dynamic estimation method of battery capacity based on impact load response characteristics. Background technique [0002] As the energy storage unit of the uninterruptible power supply system, the battery becomes the only provider of electric energy during the power failure of the grid, and its reliability is very important to the system. However, with the increase in the number of cycles and long-term aging, the available capacity of the battery gradually decreases, or even completely fails. Therefore, regular inspection of the actual state of the battery including the available capacity is a necessary part of battery maintenance. There are mainly two existing battery state detection technical methods: one is to use regular charging and discharging methods to verify the remaining capacity of the battery. This method is reliable and effective, but it has the disadvantages ...

AI Technical Summary

Problems solved by technology

There are two main methods of existing storage battery state detection technology: one is to use regular charging and discharging to verify the remaining capacity of the battery. When the power is low, if there is a power outage in the power grid, there is a risk that there will not be enough power to support the load; the second is to use the internal resistance detection method to judge the state of the battery. Among them, the offline type still requires a lot of manual regular testing, which is time-consuming and labor-intensive. At the same time, there are two The risk of battery failure not being discovered in time during the first inspection; although the online internal resistance test method overcomes the defect of offline method that consumes a lot of labor, it actively injects harmonics, which may cause adverse effects on system loads and other equipment.

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