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An important problem for the designers of complex heterogeneous circuits, combinating digital and analog parts, is to predict the perturbations coming from commutating logical gates, flowing through the substrate to reach some sensitive analog blocks. We present, in this paper, an application of a stochastic model based on Markovian processes; the digital switching activity is modelled as functions defined as Markov Chains. The final goal is to grasp the noise power density of such perturbations. Then formulas are derived for both the spectral lines—discrete part—and the continuous part of this spectral density. As an example, we extract an actual interference signal resulting from the modulation of parasitic-injected waveforms—for instance into some circuit supply—driven by the discrete stochastic process.

International audience; This paper deals with the implementation of control algorithms for alternative current (ac) motors using co-design methodology for hard or mixed hardware/software solutions. The authors focus on the design flow and experiments using FPGA / DSP platform. A full FPGA implementation of the well-known field oriented control strategy is presented. In a next step a mixed FPGA / DSP platform is presented associated with preliminary results concerning a mixed implementation of the scalar control algorithm.

Electrolytic filter capacitors are frequently responsible for static converter breakdowns. To predict these faults, a new method to set a predictive maintenance is presented and tested on two types of converters. The best indicator of fault of the output filter capacitors is the increase of ESR (equivalent series resistance). The output-voltage ripple /spl Delta/V/sub o/ of the converter increases with respect to ESR. In order to avoid errors due to load variations, /spl Delta/V/sub o/ is filtered at the switching frequency of the converter. The problem is that this filtered component is not only dependent on the aging of the capacitors, but also on the ambient temperature, output current, and input voltage of the converter. Thus, to predict the failure of the capacitors, this component is processed with these parameters and the remaining time before failure is deduced. Software was developed to establish predictive maintenance of the converter. The method developed is as follows. First, a reference system including all the converter parameters was built for the converter at its sound state, i.e., using sound electrolytic filter capacitors. Then, all these parameters were processed and compared on line to the reference system, thereby, the lifetime of these capacitors was computed.