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Response surface modelling and performance optimisation of energy harvester-powered sensor nodes

Response surface modelling and performance optimisation of energy harvester-powered sensor nodes
Response surface modelling and performance optimisation of energy harvester-powered sensor nodes
The emerging technologies of harvesting the energy from the environment surrounding the application have recently attracted intensive attention of design automation researchers.Due to the universal presence of vibrations on machines, among the different mechanisms available to obtain electrical power from ambient energy, the vibration basedharvesters have been the subject of particularly extensive development. A vibration-based (kinetic) harvester simply converts vibrations in the environment surrounding a wireless sensor node into electrical energy. This enables the wireless sensor node to be placed anywhere in the environment with no need for access to facilitate battery replacement. The basic structure of vibration-based energy harvester is composed of multi-domain components, it contains electrical, mechanical, and magnetic in the case of electromagnetic harvester. In addition, many design parameters from different domains need to be optimised in a holistic manner (i.e. treating all the system components as a connected unit); all these requirements besides the traditional approaches of optimisation, complicate the hardware description language for analog and mixed syste (HDL-AMS) simulation and makes central processor unit (CPU) takes prohibitive time, even with today's multi-physics simulation tools. This research develops, a novel optimisation technique, which enables effcient optimisation and design exploration for such a complex system and reduce CPU computation time for optimisation purposes. The proposed methodology accelerates the optimisation by approximately two orders of magnitude due to the utilisation of the design of experiment (DoE) approach and response surface modelling (RSM). The contributions of this research can be summarised as follows: Firstly, a novel, response surface based design space exploration approach to energy harvester powered systems has been developed. The proposed technique enables designers to gain insight into the details of design parameters trade-offs and quantifies each design parameter effect on performance indicators via the response surface mathematical model. The method has been applied to a linear micro-electromagnetic cantilevered harvester. Secondly, a novel, fast performance optimisation technique for a wireless sensor node powered by a tunable kinetic energy harvester has been developed. The result of applying this technique reduces the total CPU optimisation time by two orders of magnitude compared with the classical approach, i.e. through multiple full simulations. Thirdly, a software tool set has been created, based on MATLAB and VHDL-AMS, for fast, multi-dimensional design space exploration and optimisation of a kinetic harvester
Aloufi, Mansour
69c6a731-4daf-40d0-a403-59c5a3051ce5
Aloufi, Mansour
69c6a731-4daf-40d0-a403-59c5a3051ce5
Kazmierski, Tomasz
a97d7958-40c3-413f-924d-84545216092a

Aloufi, Mansour (2013) Response surface modelling and performance optimisation of energy harvester-powered sensor nodes. University of Southampton, Faculty of Physical Sciences and Engineering, Doctoral Thesis, 222pp.

Record type: Thesis (Doctoral)

Abstract

The emerging technologies of harvesting the energy from the environment surrounding the application have recently attracted intensive attention of design automation researchers.Due to the universal presence of vibrations on machines, among the different mechanisms available to obtain electrical power from ambient energy, the vibration basedharvesters have been the subject of particularly extensive development. A vibration-based (kinetic) harvester simply converts vibrations in the environment surrounding a wireless sensor node into electrical energy. This enables the wireless sensor node to be placed anywhere in the environment with no need for access to facilitate battery replacement. The basic structure of vibration-based energy harvester is composed of multi-domain components, it contains electrical, mechanical, and magnetic in the case of electromagnetic harvester. In addition, many design parameters from different domains need to be optimised in a holistic manner (i.e. treating all the system components as a connected unit); all these requirements besides the traditional approaches of optimisation, complicate the hardware description language for analog and mixed syste (HDL-AMS) simulation and makes central processor unit (CPU) takes prohibitive time, even with today's multi-physics simulation tools. This research develops, a novel optimisation technique, which enables effcient optimisation and design exploration for such a complex system and reduce CPU computation time for optimisation purposes. The proposed methodology accelerates the optimisation by approximately two orders of magnitude due to the utilisation of the design of experiment (DoE) approach and response surface modelling (RSM). The contributions of this research can be summarised as follows: Firstly, a novel, response surface based design space exploration approach to energy harvester powered systems has been developed. The proposed technique enables designers to gain insight into the details of design parameters trade-offs and quantifies each design parameter effect on performance indicators via the response surface mathematical model. The method has been applied to a linear micro-electromagnetic cantilevered harvester. Secondly, a novel, fast performance optimisation technique for a wireless sensor node powered by a tunable kinetic energy harvester has been developed. The result of applying this technique reduces the total CPU optimisation time by two orders of magnitude compared with the classical approach, i.e. through multiple full simulations. Thirdly, a software tool set has been created, based on MATLAB and VHDL-AMS, for fast, multi-dimensional design space exploration and optimisation of a kinetic harvester

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Published date: June 2013
Organisations: University of Southampton, Electronics & Computer Science

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Local EPrints ID: 355882
URI: https://eprints.soton.ac.uk/id/eprint/355882
PURE UUID: e46175d5-1003-4dbd-8f68-f93fae6f23c8

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Date deposited: 18 Nov 2013 11:39
Last modified: 18 Jul 2017 03:43

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