Behavioural Performance and Variation Modelling for Hierarchical-based Analogue IC Design

Ali, S. M.; Wilcock, Reuben; Wilson, Peter

doi:10.1109/bmas.2008.4751253

Cited by 2 publications

(2 citation statements)

References 15 publications

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“…A critical aspect of modeling is being to use these models to predict the performance of the design and also to optimize the overall system in terms of specific characteristics. This requires the use of system level optimization techniques such as Pareto fronts and evolutionary algorithms, which are also only practical where the models are efficient and fast as described in [25]- [27].…”

Section: Electrical Network Modelingmentioning

confidence: 99%

Advanced avionics applications simulation platform (AAASP) for accurate aircraft systems simulation

Wilson

Storey

2016

2016 IEEE Aerospace Conference

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A persistent problem for Aircraft Manufacturers has been the difficulty in carrying out accurate and robust simulations of the complete aircraft power network, while including numerous models from a variety of individual equipment suppliers. Often the models are of variable or low quality, with ill-defined parameters or behavior, and in many cases of the wrong level of abstraction to be appropriate for large scale network simulations. In addition, individual equipment suppliers often provide poor models for network integration, with a common issue being low robustness of models leading to lack of convergence, excessive simulation times and delays in development due to the need for rework and extensive testing of these models. In order to address this specific issue a complete library of power electronic system models for Aerospace applications has been developed that encompasses the range of functions from elementary components (passives, devices, switches and magnetic components), intermediate building blocks (rectifiers, inverters, motors, protection devices) and finally complete system models (variable frequency starter generators, power converters, battery and storage elements, transformers). These models have been developed in partnership with several key aircraft equipment suppliers and in partnership with Airbus to ensure that the resulting models are complete and robust. Specific equipment models were also developed in this library including permanent magnet generators, synchronous machines, environmental control systems, wing ice protection systems, power electronic modules and advanced power protection systems. The specific models have been validated against reference and measured data to ensure that they are consistent and accurate. This paper will describe the techniques used to achieve more robust models, using model based engineering, the integration of specific equipment models into the complete aircraft network and the validation of the behavior against measured results. The paper will provide the results of a complete aircraft power network highlighting how the individual models are integrated into the overall network model and the inherent robustness ensure effective, accurate and robust simulations.

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Section: Electrical Network Modelingmentioning

confidence: 99%

Advanced avionics applications simulation platform (AAASP) for accurate aircraft systems simulation

Wilson

Storey

2016

2016 IEEE Aerospace Conference

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“…In this paper, a novel approach is proposed that develops a combined performance and statistical variation behavioural model for analogue circuits. This approach is an improvement over the work presented in [10] in the way the variation model being used at the system level optimisation. On top of that the example demonstrated the impact of the methodology with higher number of variables, performance functions and complex spice simulation.…”

Section: Figure 1 a Typical System Design Hierarchymentioning

confidence: 99%

Improved performance and variation modelling for hierarchical-based optimisation of analogue integrated circuits

Ali¹,

Li²,

Wilcock³

et al. 2009

2009 Design, Automation &Amp; Test in Europe Conference &Amp; Exhibition

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A new approach in hierarchical optimisation is presented which is capable of optimising both the performance and yield of an analogue design. Performance and yield trade offs are analysed using a combination of multi-objective evolutionary algorithms and Monte Carlo simulations. A behavioural model that combines the performance and variation for a given circuit topology is developed which can be used to optimise the system level structure. The approach enables top-down system optimisation, not only for performance but also for yield. The model has been developed in Verilog-A and tested extensively with practical designs using the Spectre simulator. A performance and variation model of a 5 stage voltage controlled ring oscillator has been developed and a PLL design is used to demonstrate hierarchical optimisation at the system level. The results have been verified with transistor level simulations and suggest that an accurate performance and yield prediction can be achieved with the proposed algorithm.

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Behavioural Performance and Variation Modelling for Hierarchical-based Analogue IC Design

Cited by 2 publications

References 15 publications

Advanced avionics applications simulation platform (AAASP) for accurate aircraft systems simulation

Advanced avionics applications simulation platform (AAASP) for accurate aircraft systems simulation

Improved performance and variation modelling for hierarchical-based optimisation of analogue integrated circuits

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