The University of Southampton
University of Southampton Institutional Repository

Mixed technology modelling and optimisation for automotive, energy harvesting and MEMS applications using VHDL-AMS

Wang, Leran (2009) Mixed technology modelling and optimisation for automotive, energy harvesting and MEMS applications using VHDL-AMS University of Southampton, School of Electronics and Computer Science, Doctoral Thesis , 225pp.

Record type: Thesis (Doctoral)

Abstract

This research work investigates methodologies for VHDL-AMS based mixed technology modelling and optimisation, specifically with automotive, energy harvesting and MEMS applications in mind. The contributions are summarised as follows: Firstly, methodologies that support modelling and simulation of mixed-domain automotive systems have been developed. VHDL-AMS and its standard packages have been used to generate efficient models of complex automotive systems.
Secondly, a novel, VHDL-AMS based optimisation of fuzzy logic controllers has been developed. The idea is to optimise the shapes of fuzzy logic membership functions using a genetic algorithm. Since the system to be optimised is also implemented in VHDLAMS, this methodology has resulted in an integrated performance optimisation system that is wholly implemented in a hardware description language.
Thirdly, the first complete VHDL-AMS modelling approach has been presented for the DATE’99 benchmark to model a portal crane and embedded control. The model was proposed for a DATE’99 technical panel discussion to compare different languages for system level specification. The obtained new benchmark results have proved the suitability of VHDL-AMS for creating executable specifications of heterogeneous embedded systems.
Fourthly, an automated energy harvester design flow which is based on a single HDL software platform that can be used to model, simulate, configure and optimise energy harvester systems has been proposed. VHDL-AMS has been used to incorporate various parts of the energy harvester (micro-generator, voltage booster, etc) into a single model. The salient feature of an integrated model is that it allows optimisation based on system performance, which is not possible in conventional modelling approaches.
Fifthly, to enhance the modelling capability of VHDL-AMS for systems with MEMS structures where distributed behaviour is essential, language extensions have been proposed to efficiently implement general partial differential equations. The extended language has been named VHDL-AMSP. A suitable preprocessor has been developed to automatically convert VHDL-AMSP into the existing VHDL-AMS 1076.1 standard, so that models with partial differential equations can be simulated using currently available simulators.
Finally, case studies have been presented to validate the developed methodologies. These case studies include: a portal crane and its embedded control, an automotive vibration isolation seating system, a fuzzy logic controller for automotive active suspension systems, a vibration-based electromagnetic energy harvester, and a MEMS accelerometer in high-order sigma-delta-modulator loops.

PDF PhD_Thesis_LWang.pdf - Other
Restricted to Repository staff only
Download (8MB)

More information

Published date: January 2009
Organisations: University of Southampton

Identifiers

Local EPrints ID: 65104
URI: http://eprints.soton.ac.uk/id/eprint/65104
PURE UUID: 8d9a6b93-214f-497d-8af0-7e79af56ad1b

Catalogue record

Date deposited: 04 Feb 2009
Last modified: 17 Jul 2017 14:10

Export record

Contributors

Author: Leran Wang
Thesis advisor: Tomasz Kazmierski

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×