Steady state physical modelling for optimizing capacitive tactile sensors thermal sensitivity

Hampson, Rory and Dobie, Gordon (2023) Steady state physical modelling for optimizing capacitive tactile sensors thermal sensitivity. IEEE Sensors Journal, 23 (21). pp. 26047-26054. ISSN 1530-437X (https://doi.org/10.1109/JSEN.2023.3315969)

[thumbnail of Hampson-Dobie-IEEE-SJ-Steady-state-physical-modelling-for-optimizing]
Preview
Text. Filename: Hampson_Dobie_IEEE_SJ_Steady_state_physical_modelling_for_optimizing.pdf
Accepted Author Manuscript
License: Strathprints license 1.0

Download (1MB)| Preview

Abstract

Capacitive tactile pressure sensors are increasingly used in ergonomic testing and medical devices, specifically for human body measurement and characterizing human interactions with their environment, where temperature coefficients are important considerations. New wearable and flexible sensor designs appear regularly in the literature, however, they rarely discuss why respective designs are improvements over predecessors, or any sensor performance optimizations for their intended applications. This lack of clear design rationale in the literature leads to inefficient design iterations and suboptimal sensor performance as designs are seemingly 'trial and errored.' This work analytically models the steady state mechanics of a simple commercial-off-the-shelf (COTS) capacitive tactile sensor, SingleTact S15-4.5 N , with nominal base temperature sensitivity of 0.2% full scale range (FSR)/°C, using multi-objective optimization on the critical factors to minimize the temperature coefficient. This work investigates the governing factors for the temperature coefficients via sensitivity analysis on the experimentally validated model, providing novel design insight. By optimizing the design parameters within practical bounds, improvements of 16.16%, 16.47%, and 14.74%, can be achieved for the baseline, sensitivity, and linearity (steady state) temperature coefficients, respectively. The model is shown to be useful in determining dominant factors controlling the steady state temperature coefficients as well as estimating sensitivity to manufacturing tolerances. This approach will be used on more complex designs in future to ensure optimal application performance, and assess the impact of manufacturing constraints on sensor performance to the benefit of manufacturers and end users alike.

ORCID iDs

Hampson, Rory ORCID logoORCID: https://orcid.org/0000-0001-7903-7460 and Dobie, Gordon ORCID logoORCID: https://orcid.org/0000-0003-3972-5917;