In this work, a two-step procedure to predict maximum (worst-case scenario) and minimum (best-case scenario) noise levels induced by bulk current injection (BCI) at the terminal sections of a wiring harness is presented. To this end, common mode (CM) and differential mode (DM) quantities are introduced by a suitable modal transformation, and equivalent modal circuits are derived, where CM (dominant mode) into DM (secondary mode) conversion is modelled by induced sources included into the DM circuit. The procedure initially foresees the solution of the CM circuit to provide input data for subsequent solution of the DM circuit. Such a two-step approach is then used to develop a probabilistic-possibilistic framework for computationally-efficient estimation of lower and upper boundaries to the variability of the noise voltages induced at the bundle terminations. To this end, random uncertainty affecting certain setup parameters is addressed through probability theory, whereas epistemic uncertainty is represented via possibility theory. Accuracy and computational efficiency of the proposed two-step method are assessed by examples involving seven and nineteen wire harnesses.

A Two-Step Approach for the Analysis of Bulk Current Injection Setups Involving Multiwire Bundles

Toscani, N;Wu, X;Grassi, F
2023-01-01

Abstract

In this work, a two-step procedure to predict maximum (worst-case scenario) and minimum (best-case scenario) noise levels induced by bulk current injection (BCI) at the terminal sections of a wiring harness is presented. To this end, common mode (CM) and differential mode (DM) quantities are introduced by a suitable modal transformation, and equivalent modal circuits are derived, where CM (dominant mode) into DM (secondary mode) conversion is modelled by induced sources included into the DM circuit. The procedure initially foresees the solution of the CM circuit to provide input data for subsequent solution of the DM circuit. Such a two-step approach is then used to develop a probabilistic-possibilistic framework for computationally-efficient estimation of lower and upper boundaries to the variability of the noise voltages induced at the bundle terminations. To this end, random uncertainty affecting certain setup parameters is addressed through probability theory, whereas epistemic uncertainty is represented via possibility theory. Accuracy and computational efficiency of the proposed two-step method are assessed by examples involving seven and nineteen wire harnesses.
2023
Bulk current injection (BCI), conducted susceptibility, epistemic uncertainty, hybrid probabilistic-possibilistic uncertainty quantification, modal analysis, multiconductor transmission lines
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1231004
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