Automotive electronics is a fast growing market. In a field primarily dominated by mechanical or hydraulic systems, over the past few decades there has been exponential growth in the number of electronic components incorporated into automobiles. Partly thanks to the advance in high voltage smart power processes in nowadays cars is possible to integrate both power/high voltage electronics and analog/digital signal processing circuitry thus allowing to replace a lot of mechanical systems with electro-mechanical or fully electronic ones. High level modeling of complex electronic systems is gaining importance relatively to design space exploration, enabling shorter design and verification cycles, allowing reduced time-to-market. A high level model of a resistor string DAC to evaluate nonlinearities has been developed in MATLAB environment. As a test case for the model, a 10 bit resistive DAC in 0.18um is designed and the results were compared with the traditional transistor level approach. Then we face the analysis and design of a fundamental block: the bandgap voltage reference. Automotive requirements are tough, so the design of the voltage reference includes a pre-regulation part of the battery voltage that allows to enhance overall performances. Moreover an analog integrated driver for an automotive application whose architecture exploits today’s trends of analog-digital integration allowing a greater range of flexibility allowing high configurability and fast prototipization is presented. We covered also the mixed-signal verification approach. In fact, as complexity increases and mixed-signal systems become more and more pervasive, test and verification often tend to be the bottleneck in terms of time effort. A complete flow for mixed-signal verification using VHDL-AMS modeling and Python scripting is presented as an alternative to complex transistor level simulations. Finally conclusions are drawn.

Mixed-signal integrated circuits design and validation for automotive electronics applications

2012

Abstract

Automotive electronics is a fast growing market. In a field primarily dominated by mechanical or hydraulic systems, over the past few decades there has been exponential growth in the number of electronic components incorporated into automobiles. Partly thanks to the advance in high voltage smart power processes in nowadays cars is possible to integrate both power/high voltage electronics and analog/digital signal processing circuitry thus allowing to replace a lot of mechanical systems with electro-mechanical or fully electronic ones. High level modeling of complex electronic systems is gaining importance relatively to design space exploration, enabling shorter design and verification cycles, allowing reduced time-to-market. A high level model of a resistor string DAC to evaluate nonlinearities has been developed in MATLAB environment. As a test case for the model, a 10 bit resistive DAC in 0.18um is designed and the results were compared with the traditional transistor level approach. Then we face the analysis and design of a fundamental block: the bandgap voltage reference. Automotive requirements are tough, so the design of the voltage reference includes a pre-regulation part of the battery voltage that allows to enhance overall performances. Moreover an analog integrated driver for an automotive application whose architecture exploits today’s trends of analog-digital integration allowing a greater range of flexibility allowing high configurability and fast prototipization is presented. We covered also the mixed-signal verification approach. In fact, as complexity increases and mixed-signal systems become more and more pervasive, test and verification often tend to be the bottleneck in terms of time effort. A complete flow for mixed-signal verification using VHDL-AMS modeling and Python scripting is presented as an alternative to complex transistor level simulations. Finally conclusions are drawn.
28-apr-2012
Italiano
Fanucci, Luca
Saletti, Roberto
Saponara, Sergio
Università degli Studi di Pisa
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14242/132581
Il codice NBN di questa tesi è URN:NBN:IT:UNIPI-132581