An automated design flow for MEMS accelerometers with Sigma-Delta control
An automated design flow for MEMS accelerometers with Sigma-Delta control
This contribution presents a novel methodology for automated optimal design of MEMS accelerometers embedded in electronic control circuitry from user defined high-level performance specifications and design constraints. The proposed approach is based on simulation-based optimisation where automated configuration selection for electronic blocks and synthesis of mechanical layouts are coupled with calculations of optimal design parameters. The underlying dedicated MEMS simulator supports distributed mechanical dynamics to enable accurate performance prediction of critical mechanical components, such as acceleration sensing elements which form an essential part of the mixed-technology control loop.
Zhao, Chenxu
87d1aa10-ef41-44bc-8969-82626aa1dd92
Kazmierski, Tom
a97d7958-40c3-413f-924d-84545216092a
June 2010
Zhao, Chenxu
87d1aa10-ef41-44bc-8969-82626aa1dd92
Kazmierski, Tom
a97d7958-40c3-413f-924d-84545216092a
Zhao, Chenxu and Kazmierski, Tom
(2010)
An automated design flow for MEMS accelerometers with Sigma-Delta control.
ICIA 2010.
Record type:
Conference or Workshop Item
(Other)
Abstract
This contribution presents a novel methodology for automated optimal design of MEMS accelerometers embedded in electronic control circuitry from user defined high-level performance specifications and design constraints. The proposed approach is based on simulation-based optimisation where automated configuration selection for electronic blocks and synthesis of mechanical layouts are coupled with calculations of optimal design parameters. The underlying dedicated MEMS simulator supports distributed mechanical dynamics to enable accurate performance prediction of critical mechanical components, such as acceleration sensing elements which form an essential part of the mixed-technology control loop.
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Published date: June 2010
Venue - Dates:
ICIA 2010, 2010-05-31
Organisations:
EEE
Identifiers
Local EPrints ID: 271341
URI: http://eprints.soton.ac.uk/id/eprint/271341
PURE UUID: bcadf76f-93d0-4f3e-8213-35a0bbbb40b1
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Date deposited: 05 Jul 2010 10:31
Last modified: 07 Jan 2022 21:17
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Contributors
Author:
Chenxu Zhao
Author:
Tom Kazmierski
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