24 citations · 48 across the 9 of their papers we have counts for
9 papers
Domain knowledge-guided machine learning framework for state of health estimation in Lithium-ion batteries
Andrea Lanubile, Pietro Bosoni, Gabriele Pozzato +3
Accurate estimation of battery state of health is crucial for effective electric vehicle battery management. Here, we propose five health indicators that can be extracted online fr…
Taking Second-life Batteries from Exhausted to Empowered using Experiments, Data Analysis, and Health Estimation
Xiaofan Cui, Muhammad Aadil Khan, Gabriele Pozzato +3
The reuse of retired electric vehicle batteries in grid energy storage offers environmental and economic benefits. This study concentrates on health monitoring algorithms for retir…
Combining physics-based and machine learning methods to accelerate innovation in sustainable transportation and beyond: a control perspective
Gabriele Pozzato, Simona Onori
Lithium-ion batteries are playing a key role in the sustainable energy transition. To fully exploit the potential of this technology, a variety of modeling, estimation, and predict…
Core-shell enhanced single particle model for lithium iron phosphate batteries: model formulation and analysis of numerical solutions
Gabriele Pozzato, Aki Takahashi, Xueyan Li +3
In this paper, a core-shell enhanced single particle model for iron-phosphate battery cells is formulated, implemented, and verified. Starting from the description of the positive…
Core-shell enhanced single particle model for LiFePO batteries
Aki Takahashi, Gabriele Pozzato, Anirudh Allam +5
In this paper, a novel electrochemical model for LiFePO battery cells that accounts for the positive particle lithium intercalation and deintercalation dynamics is proposed. St…
Sensitivity analysis of a mean-value exergy-based internal combustion engine model
Gabriele Pozzato, Denise Rizzo, Simona Onori
In this work, we conduct a sensitivity analysis of the mean-value internal combustion engine exergy-based model, recently developed by the authors, with respect to different drivin…
Mean-value exergy modeling of internal combustion engines: characterization of feasible operating regions
Gabriele Pozzato, Denise Rizzo, Simona Onori
In this paper, a novel mean-value exergy-based modeling framework for internal combustion engines is developed. The characterization of combustion irreversibilities, thermal exchan…
Exergy-based modeling framework for hybrid and electric ground vehicles
Federico Dettù, Gabriele Pozzato, Denise M. Rizzo +1
Exergy, or availability, is a thermodynamic concept representing the useful work that can be extracted from a system evolving from a given state to a reference state. It is also a…
Modeling Degradation for Second-life Battery: Preliminary Results
Gabriele Pozzato, Seong Beom Lee, Simona Onori
This paper presents a novel battery modeling framework based on the enhanced single particle model (ESPM) to account for degradation mechanisms of second-life batteries. While acco…