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Explore IndustryDriving Battery Innovation with CAE
Driving Battery Innovation with CAE
Learn how CAE accelerates the battery design process
There is an ever-increasing demand for higher energy and power density battery cells, without compromising on weight, size, aging and safety of the battery pack. This makes the design of batteries a highly complex, multi-parameter challenge. In this webinar, we will demonstrate how Computer Aided Engineering (CAE) accelerates the battery design process at both the cell and pack level, helping you achieve your safety and performance goals while at the same time reducing your development costs.
Viewers of this webcast learn how CAE can be used to design better cells by optimizing the current collection and thickness of the electrode coatings and foils. In addition, CAE can help you determine the thickness, position, and number of tabs, as well as the dimensions of busbars. These cell models can be readily transferred to pack models.
For module design, we will discuss how CAE can optimize the thermal system to minimize temperature variations within and across cells. The behavior of both air and liquid coolants can be modeled with accuracy. We will conclude by showing how you can optimize the cooling performance of a pouch cells pack to obtain uniform cell temperature for the minimum pack weight.
Presenters:
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Learn how CAE accelerates the battery design process
There is an ever-increasing demand for higher energy and power density battery cells, without compromising on weight, size, aging and safety of the battery pack. This makes the design of batteries a highly complex, multi-parameter challenge. In this webinar, we will demonstrate how Computer Aided Engineering (CAE) accelerates the battery design process at both the cell and pack level, helping you achieve your safety and performance goals while at the same time reducing your development costs.
Viewers of this webcast learn how CAE can be used to design better cells by optimizing the current collection and thickness of the electrode coatings and foils. In addition, CAE can help you determine the thickness, position, and number of tabs, as well as the dimensions of busbars. These cell models can be readily transferred to pack models.
For module design, we will discuss how CAE can optimize the thermal system to minimize temperature variations within and across cells. The behavior of both air and liquid coolants can be modeled with accuracy. We will conclude by showing how you can optimize the cooling performance of a pouch cells pack to obtain uniform cell temperature for the minimum pack weight.
Presenters: