Sathish Swaminathan
Indian Institute of Technology Madras
6 Papers
Sathish Swaminathan is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Chirp & Electrical impedance. The author has an hindex of 3, co-authored 4 publications.
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Papers
Rapid humidity regulation by mixing of dry and humid gases with feedback control for PEM fuel cells
Srinivasan Raman,Sathish Swaminathan,Sundaram Bhardwaj,Hemanth Kumar Tanneru,Brian Bullecks,Raghunathan Rengaswamy,Raghunathan Rengaswamy +6 more
TL;DR: In this paper, the authors demonstrate a rapid and nearly accurate humidity control by mixing of dry and humidified gas streams for tracking predefined relative humidity set points, which can track various relative humidity profiles when coupled with feedback to PI and PID control algorithms.
21
Rapid impedance spectroscopy using dual phase shifted chirp signals for electrochemical applications
TL;DR: In this article, a novel technique that makes use of two high bandwidth and short duration signals having dissimilar phases to estimate impedance is introduced, which can pave the way for a quick and cost effective alternative to EIS and allow for impedance measurement during operation.
15
Patent
Method for impedance measurement using multiple phase shifted chirp signals
Raghunathan Rengasamy,Resmi Suresh,Sathish Swaminathan +2 more
- 17 Sep 2020
TL;DR: In this article, the authors proposed a method for measuring the impedance of a system under test using multiple, high bandwidth, short duration chirp signals having dissimilar phase to estimate impedance.
Water induction studies in a hydrogen-diesel dual-fuel engine
TL;DR: In this paper, the results of an investigation on improving the knock limited power output when water is inducted with the intake charge of a hydrogen-diesel dual-fuel engine were presented.
Data science and IoT based mobile monitoring framework for hyper-local PM2.5 assessment in urban setting
TL;DR: In this article , the authors proposed a comprehensive framework for hyperlocal assessment of ambient air quality through a mobile monitoring approach, which is used to locate diurnal, spatio-temporal PM2.5 hotspots in an urban environment and then associated with daily anthropogenic activity.