Prediction Method for Automobile EMI Test Result in AM Frequency Band

Event
WCX™ 17: SAE World Congress Experience
Authors Abstract
Content
The EMI, electromagnetic interference, is tested for automobiles and components by the method defined in the international standard, CISPR 25. Regarding the automobile test, the EMI from the component installed in the automobile is measured by the antenna of an automobile. On the other hand on the component test, the EMI from the component is measured by a mono-pole antenna set forward of the component. However, components sometimes fail the automobile test even if its passed the component test due to the difference of the method. In this case, the component has to be designed again to pass the automobile test. Therefore, the prediction method of the automobile test result is required. In this paper, we tried to modify the standard component test configuration to predict the automobile test result for a fuel pump system in AM frequency band. At first, to show the noise propagation mechanism of the automobile test, the mechanism was modeled by an electrical circuit by focusing on the parasitic capacitances between the fuel pump system, the antenna and the chassis. Next, to realize the same electrical circuit as the automobile, the standard component test configuration was modified. For example, in the standard component test, the fuel pump should be set on the grounded ground plane. On the other hand, in the modified component test, the fuel pump was set between the floor and floating ground plane. As the result, the modified component test result agreed with the automobile test result, meaning automobile test result could be predicted.
Meta TagsDetails
DOI
https://doi.org/10.4271/2017-01-0014
Pages
8
Citation
Nomura, T., and Kawai, K., "Prediction Method for Automobile EMI Test Result in AM Frequency Band," Passenger Cars - Electronic and Electrical Systems 10(1):136-143, 2017, https://doi.org/10.4271/2017-01-0014.
Additional Details
Publisher
Published
Mar 28, 2017
Product Code
2017-01-0014
Content Type
Journal Article
Language
English