Using estimation to optimize electric pump flow rates for spraying applications

Raveen Appuhamy; Alex McCafferty-Leroux; Brett Sicard; S. Andrew Gadsden

doi:10.1117/12.3013959

7 June 2024 Using estimation to optimize electric pump flow rates for spraying applications

Raveen Appuhamy, Alex McCafferty-Leroux, Brett Sicard, S. Andrew Gadsden

Proceedings Volume 13057, Signal Processing, Sensor/Information Fusion, and Target Recognition XXXIII; 1305703 (2024) https://doi.org/10.1117/12.3013959
Event: SPIE Defense + Commercial Sensing, 2024, National Harbor, Maryland, United States

Abstract

Electric pumps are widely used in applications such as sanitation, manufacturing and agriculture. Electric current is supplied to the pumps, which translates into a corresponding flow rate and therefore output pressure. This relationship between a pump’s pressure and flow rate is described as its performance curve. This conference paper uses estimation theory and cognitive system techniques to improve the efficiency of electric pumps. Specifically, using the perception-action cycle to observe the states, predict the system behaviour and then optimize it. The system states are estimated using sensor measurements and system dynamics, where the control system uses the states to find the optimal flow rate based on the performance curve and adjust the system accordingly. This methodology is validated using simulations. The simulation models a sprayer that is powered by a DC motor where the ideal spray angle is maintained based on the distance to the surface. Optimizing the electric pump performance, reduces energy consumption and optimizes fluid usage, which can provide savings in many industries and systems.

Conference Presentation

Citation Download Citation

Raveen Appuhamy, Alex McCafferty-Leroux, Brett Sicard, and S. Andrew Gadsden "Using estimation to optimize electric pump flow rates for spraying applications", Proc. SPIE 13057, Signal Processing, Sensor/Information Fusion, and Target Recognition XXXIII, 1305703 (7 June 2024); https://doi.org/10.1117/12.3013959

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