2 results about "Power capability" patented technology

The application discloses a kind of vehicle power battery power test method and system based on power MAP table, it is related to power battery power test technical field, comprising: according to the imported power MAP table, identify multiple temperature and SOC state test points in table, and determine the nature parameter of power test;Combining the selected set constant volume mode, the power of vehicle power battery to be measured is tested;Wherein, multiple temperature test points are tested in the order from high temperature to low temperature, and according to the difference of charge-discharge operation mode, multiple SOC state test points are tested in different order;Based on the data obtained by testing and power MAP table original data, the key data of each MAP test point, the capacity value under each temperature, the adjustment capacity value in each test step and the running capacity value are obtained.The application can effectively detect the power capability of power battery and its system, improve detection efficiency and precision.

This application provides a method, system, platform, storage medium, and device for parsing and scheduling of hybrid computing tasks based on quantum computing and power consumption. The method includes: acquiring dynamic computing power capability information of multiple computing nodes in a hybrid computing power network; performing a first-level parsing and adaptation process for the task to obtain a first parsing and adaptation result and a corresponding first information entropy; when the first information entropy does not meet a first preset condition, performing logical topology reconstruction on the hybrid computing power network and performing a second-level parsing and adaptation process within the reconstructed network area to obtain a second adaptation result and a corresponding second information entropy; when the second information entropy does not meet a second preset condition, performing an optimization search within the reconstructed network area and determining a target computing node based on the search result; and generating scheduling instructions based on the target computing node. This method can quickly achieve effective globally optimal task scheduling for complex and more challenging hybrid computing tasks.