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DoE 기반의 혁신적인 E-Drive 효율 자동화 시험 방법론
김용현(Yonghyun Kim),Markus Sulzer 한국자동차공학회 2022 한국자동차공학회 학술대회 및 전시회 Vol.2022 No.11
In this paper a Robust Neural Network (RNN) which is especially suited for EV test bench. The complex model algorithm can provide the superior model quality of result and simple optimization. The E-Drive test bench is consisted of real E-Drive test environment with the physical operation and optimized test/modeling methodology. The model and test are operated for best optimization during back-emf phase with managing the limit condition which must be avoided. Not only quality, but also the time efficiency, will be managed in the same process. When RNN model is used with battery test environment, uninterested areas of test will be ignored and during the test, DoE provides the fast way to anticipate the next nominated test point for the better model quality. Using RNN algorithm, this automatic test can provide the simple order to make a model prediction and the efficiency test using id and iq parameter.
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