September/October 2021 | Vol. 26 No. 5
by Mike Leibowitz, Senior Program Manager, NEMA
One of the most important aspects of designing new products is ensuring the actual performance matches the predicted performance. With end-users requesting specialized designs for their applications becoming more common, finding an accepted and reiable means to predict performance for end-user and manufacturer is a growing need.
Twenty years ago, the motor industry struggled with a similar situation: the US Department of Energy passed a series of regulations that encompassed hundreds of basic ratings that required efficiency testing. Over time the number has grown to well over 100,000 models and continues to grow with custom variations and regulatory expansion. Given it can can take more than a day to complete setup and testing, there aren’t enough test facilities in the world to evaluate all the necessary motors using the traditional direct-testing methods.
Clearly an alternative method was needed: Enter an Alternative Energy Determination Method. Using Industry’s input, the Department of Energy documented an approach combines rigous testing requirements with satistisical sampling to validate whether manufacturers’ design programs and processes can be relied on for accuracy. The result: instead of having to test (literally) thousands of products, the verification testing can be reduced to a total of 25 samples without losing confidence on the accuracy of results.
While this approach was documented within the Federal Regulations and has benefited motor manufacturers seeking to meet the US Department of Energy regulations, no industry standard with a similar approach was available.
Seeing there might be an opportunity to help other industries, the NEMA Motor and Generator Section undertook the effort to extract the relevant parts to create a new Standard MG G2-2021, Guide for Validating an Alternative Efficiency Determination Method (AEDM). The hope is that by providing this template, other industries can determine if their predictive models are sufficiently robust and would benefit from reduced testing using this approach.
“While this Standard addresses reduced samples for efficiency testing, industry hopes this could be used to reduce sample requirements for other testing as well, potentially saving thousands of laboratory hours each year,” said Kirk Anderson, Industry Director of Industrial Systems at NEMA. “Industry has talked about ‘digital twins’ for years; finally we have a standard that provides tangible benefits of developing predictive modeling programs.”
NEMA MG G2-2021 Guide for Validating an Alternative Efficiency Determination Method (AEDM) is due to be available later this month. For questions related to this standard and predictive modeling, please contact Mike Leibowitz. ei