ETAS ASCMO is commonly used to optimize the prediction quality of ECU models in internal combustion engines, but it is also applicable for electric motors (e.g. charging strategy) and component development.
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ETAS ASCMO is commonly used to optimize the prediction quality of ECU models in internal combustion engines, but it is also applicable for electric motors (e.g. charging strategy) and component development.
When building data based models of e.g., a combustion engine or a similar technical system, it is essential to think about the range in which the model is able to predict results in good quality. But what is the difference between all the given possibilities and when to use what?
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