Diego A. Acevedo-Bueno
Université du Québec à Trois-Rivières, Innovation and Economic Development Trois Rivières
Papers
2
Total Citations
15
H-Index
2
About
Diego A. Acevedo-Bueno is a researcher at the forefront of energy management for agricultural robotics, specializing in battery state-of-charge (SoC) estimation. His work addresses a critical bottleneck in the adoption of autonomous farming machines: reliable battery monitoring under real-world, low-cost constraints. Acevedo-Bueno’s major contributions include pioneering the validation of equivalent circuit models (ECMs) and Kalman filters for SoC estimation in agricultural robots, a domain where traditional methods often fail due to variable loads and harsh operating conditions. His 2023 paper, *"Assessing the Limits of Equivalent Circuit Models and Kalman Filters for Estimating the State of Charge: Case of Agricultural Robots,"* has garnered 11 citations, establishing a benchmark for understanding model limitations. Building on this, his 2024 work, *"An Improved ECM-Based State-of-Charge Estimation for SLA and LFP Batteries Used in Low-Cost Agricultural Mobile Robots,"* introduces tailored solutions for lead-acid and lithium iron phosphate chemistries, achieving 4 citations in its first year. By bridging battery science with practical agricultural engineering, Acevedo-Bueno’s research directly supports the transition to clean-powered, autonomous farming, offering cost-effective strategies to extend robot operation time and reliability—a vital step toward sustainable precision agriculture.
Research Focus
Key Achievements
Top Papers
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- 2