Zobrazeno 1 - 10
of 164
pro vyhledávání: '"Moura, Scott J."'
Publikováno v:
Nature Energy 3, 484-493 (2018)
The rising adoption of plug-in electric vehicles (PEVs) leads to the alignment of their electricity and their mobility demands. Therefore, transportation and power infrastructures are becoming increasingly interdependent. In this work, we uncover pat
Externí odkaz:
http://arxiv.org/abs/2303.15578
Autor:
Vijay, Upadhi, Woo, Soomin, Moura, Scott J., Jain, Akshat, Rodriguez, David, Gambacorta, Sergio, Ferrara, Giuseppe, Lanuzza, Luigi, Zulberti, Christian, Mellekas, Erika, Papa, Carlo
This research provides a novel framework to estimate the economic, environmental, and social values of electrifying public transit buses, for cities across the world, based on open-source data. Electric buses are a compelling candidate to replace die
Externí odkaz:
http://arxiv.org/abs/2209.12107
Publikováno v:
In Transportation Research Part E September 2024 189
Autor:
Badoual, Mathilde D., Moura, Scott J.
Load serving entities with storage units reach sizes and performances that can significantly impact clearing prices in electricity markets. Nevertheless, price endogeneity is rarely considered in storage bidding strategies and modeling the electricit
Externí odkaz:
http://arxiv.org/abs/2106.02396
This paper proposes a discretionary lane selection algorithm. In particular, highway driving is considered as a targeted scenario, where each lane has a different level of traffic flow. When lane-changing is discretionary, it is advised not to change
Externí odkaz:
http://arxiv.org/abs/2104.04105
Lithium-sulfur (Li-S) batteries have become one of the most attractive alternatives over conventional Li-ion batteries due to their high theoretical specific energy density (2500 Wh/kg for Li-S vs. $\sim$250 Wh/kg for Li-ion). Accurate state estimati
Externí odkaz:
http://arxiv.org/abs/2101.10436
Autor:
Kandel, Aaron, Moura, Scott J.
This paper presents an end-to-end framework for safe learning-based control (LbC) using nonlinear stochastic MPC and distributionally robust optimization (DRO). This work is motivated by several open challenges in LbC literature. In particular, many
Externí odkaz:
http://arxiv.org/abs/2004.00759
Autor:
Zhang, Dong, Couto, Luis D., Benjamin, Sebastien, Zeng, Wente, Coutinho, Daniel F., Moura, Scott J.
This manuscript presents an algorithm for individual Lithium-ion (Li-ion) battery cell state of charge (SOC) estimation when multiple cells are connected in parallel, using only terminal voltage and total current measurements. For battery packs consi
Externí odkaz:
http://arxiv.org/abs/2003.07972
Autor:
Kandel, Aaron, Moura, Scott J.
This paper presents a distributionally robust Q-Learning algorithm (DrQ) which leverages Wasserstein ambiguity sets to provide idealistic probabilistic out-of-sample safety guarantees during online learning. First, we follow past work by separating t
Externí odkaz:
http://arxiv.org/abs/2002.03016
Failure probabilities for grid components are often estimated using parametric models which can capitalize on operational grid data. This work formulates a Bayesian hierarchical framework designed to integrate data and domain expertise to understand
Externí odkaz:
http://arxiv.org/abs/2001.07597