iPower enables optimisation of system architecture design
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A new technique that allows designing system architectures with optimised power consumption, area and cost has been unveiled by imec and the Holst Centre.
According to the research teams, the iPower method enables 'truly optimised' performances which are achieved by combining the centres' experience in energy harvesting, low power electronics and application level optimisation techniques. Potential applications include healthcare, automotive and smart buildings.
iPower has been developed to enable system architectures to be designed while taking into account power, area and cost. According to the researchers it can be used in autonomous systems in domains such as heart and brain monitoring systems, automotive engine monitoring / intelligent tyres and smart metering / light control.
The iPower method is based on parameters such as system area and cost, radio transmission time periods and a/d converter sampling intervals. The researchers believe these parameters enable system power, area and cost diagnosis and optimisation to be carried out. Design and testing of the system can be performed to validate and improve the method's accuracy, while the obtained information can be used to continuously steer the research and development cycle.
The system, when used to help doctors monitor patients suffering from arrhythmia, took the electronics dimensions and price as input for the area and cost estimation. The application conditions for energy harvesting and electronics were the inputs for the power consumption optimisation. For these input parameters, iPower selected the lowest in power consumption components from an existing database and the power modes for each electronic component – such as the radio or mcu – so that the overall power consumption at the architectural level was minimised. The researchers claim that this way the power consumption of the initial arrhythmia monitoring system could be 'significantly' reduced.
Future research will focus on extending the applicability of the technique towards new system architectures and broader applications, as well as targeting more power consumption / generation, volume and cost reduction optimisation techniques.
