首页|Serial Handling And Testing Of Electrical Components' in Patent Application Approval Process (USPTO 20230400529)

Serial Handling And Testing Of Electrical Components' in Patent Application Approval Process (USPTO 20230400529)

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The following quote was obtained by the news editors from the background information supplied by theinventors: “Current EV battery assembly includes taking a standard battery cell, and assembling it into(i.e. “populating”) a EV battery module, which is basically an inter-connection of multiple cells in order toachieve the overall voltage and energy requirements for the EV battery. It is common in the EV cell testingand assembly environment to employ robots to pick up and place a collection of EV battery cells from ashipping container to various adjacent stations, such as a testing station used to confirm that each EV cellmeets manufacturing standards (e.g. defined cell voltage, defined cell amperage, etc.). These pick up andplace operations on the individual battery cells are done prior to populating the battery module with thegathered and tested cells. As such, current techniques for picking up and placing cells (e.g. for transferringfrom one location to another, including testing/validating) can include testing/measuring cell voltage,reading of bar codes positioning on an exterior surface of each EV cell, and generally verifying individualEV cells prior to populating the battery module. It is recognised that current pick and place systemsutilize equipment to pick up multiple EV battery cells at the same time, which can be disadvantageousin programming of the robotic system in the event of changes to the dimensions of the EV battery cellitself (e.g. for different cell types, and different cell positions within the battery module). “Battery Cell”typically refers to the “cell” itself and not the completed battery with multiple cells which is known as the“cell module”.

Emerging TechnologiesMachine LearningPatent ApplicationRoboticsRobotsShipping ContainerTransportation

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Jan.1)