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Robust Estimation of State of Charge in Lithium Iron Phosphate Cells Enabled by Online Parameter Estimation and Deep Neural Networks

Shi, Junzhe
Kato, Dylan
Jiang, Shida
Dangwal, Chitra
Moura, Scott
2023

This paper addresses the state of charge estimation problem in lithium iron phosphate (LFP) battery cells. LFP cells are particularly challenging because their fat open circuit voltage (OCV) curve means OCV-based battery models are weakly observable. This means standard methods for SOC estimation don't easily converge to the true SOC. Additionally, in practice, estimates must be accurate in the face of biased noise on current input, as well as mean-zero noise on measurements. As such, we aim to create an estimator that is accurate when facing these types of noise. We accomplish this with a...

Integrating Physics-Based Modeling with Machine Learning for Lithium-Ion Batteries

Tu, Hao
Moura, Scott
Wang, Yebin
Fang, Huazhen
2023

Mathematical modeling of lithium-ion batteries (LiBs) is a primary challenge in advanced battery management. This paper proposes two new frameworks to integrate physics-based models with machine learning to achieve high-precision modeling for LiBs. The frameworks are characterized by informing the machine learning model of the state information of the physical model, enabling a deep integration between physics and machine learning. Based on the frameworks, a series of hybrid models are constructed, through combining an electrochemical model and an equivalent circuit model, respectively,...

Joint Mobility and Vehicle-to-Grid Coordination in Rebalancing Shared Mobility-on-Demand Systems

Zeng, Teng
Moura, Scott
Zhou, Zhe
2023

Vehicle-to-Grid (V2G) technology enables plug-in electric vehicles (PEVs) to act as controllable loads and distributed energy resources for power systems. However, these resources, under the context of Mobility-on-Demand (MoD) market, have yet to be fully exploited for the grid services. This paper investigates how providing energy service from the shared PEVs affects both the power and transportation systems. We consider a shared MoD platform where PEVs can choose to provide either the V2G service or the traveling service when they are rebalanced to future high demand areas. In this...

System and Methods for Efficient Parking and Charging of Electrified Vehicles

Borrelli, Francesco
Moura, Scott J.
Shen, Xu
Woo, Soomin
2022

A system can include: a detector configured to provide input information; an electric vehicle; an electric vehicle charger; and a cloud server configured to execute a Simultaneous Parking and Charging Management (SPCM) method based on the input information, and communicate with the electric vehicle to assign a time for a certain electric vehicle charger based on a result of the executed SPCM method.

Lane-Change in Dense Traffic With Model Predictive Control and Neural Networks

Bae, Sangjae
Isele, David
Nakhaei, Alireza
Xu, Peng
Añon, Alexandre Miranda
Choi, Chiho
Fujimura, Kikuo
Moura, Scott
2023

This article presents an online smooth-path lane-change control framework. We focus on dense traffic where intervehicle space gaps are narrow, and cooperation with surrounding drivers is essential to achieve the lane-change maneuver. We propose a two-stage control framework that harmonizes model predictive control (MPC) with generative adversarial networks (GANs) by utilizing driving intentions to generate smooth lane-change maneuvers. To improve performance in practice, the system is augmented with an adaptive safety boundary and a Kalman filter to mitigate sensor noise. Simulation...

Optimal Operation with Robo-chargers in Plug-in Electric Vehicle Charging Stations

Ju, Yi
Zeng, Teng
Allybokus, Zaid
Moura, Scott
2023

Plug-in electric vehicles have seen unprecedented market growth, while charging facility infrastructure is falling behind. Worse still, these limited charging resources are being utilized quite uneconomically - commonly occupied by fully-charged PEVs for a long time, known as overstay. In this paper, we propose a charging facility and operation innovation to tackle this challenge. We introduce the idea of Robo-chargers, an automated charger that can proactively rotate among PEVs for charging service. We develop an operation model for management in a mixed-type charger charging station,...

Optimal Dispatch and Routing of Electrified Heavy-Duty Truck Fleets: A Case Study with Fleet Data

Wang, Ruiting
Zeng, Teng
Keyantuo, Patrick
Sandoval, Jairo
Vishwanath, Aashrith
Borhan, Hoseinali
Moura, Scott
2023

Electrifying the trucking fleet has the potential to substantially reduce the carbon footprint of logistics. However, fleet electrification also poses significant operational challenges. This study provides an up-to-date, realistic case study on optimal dispatch and routing of a heterogeneous fleet of heavy-duty trucks with the goal to improve the economic and environmental benefits of electrification. A fleet management optimization model incorporating detailed energy consumption modeling was proposed, and applied to real-world fleet demand data for practical insights. The results from...

A Deep Learning-Based Predictive Controller for the Optimal Charging of a Lithium-Ion Cell with Non-Measurable States

Pozzi, Andrea
Moura, Scott
Toti, Daniele
2023

Battery charging is a complex task, which needs to be addressed by a proper control methodology to find the highest charging current while guaranteeing safety. Among the different approaches, model predictive control appears particularly suitable due to its ability in dealing with nonlinear systems and constraints. However, its use in a realistic scenario is limited due to the high computational burden required by the online solution of an optimal control problem. A neural network-based algorithm is here proposed to significantly reduce the real-time computational effort by approximating...

Intersense: An XGBoost Model for Traffic Regulator Identification at Intersections Through Crowdsourced GPS Data

Vlachogiannis, Dimitris
Moura, Scott
Macfarlane, Jane
2023

Digital maps of the transportation network are the foundation of future mobility solutions. Autonomous and connected vehicles rely on real-time, at-scale updating of the environment in which they operate. Successful operation in a hybrid environment, where human and machine intelligence coexist, requires explicit knowledge of the traffic regulator infrastructure. Future generation traffic management strategies and path planning systems must be tightly integrated with the regulator infrastructure in order to improve traffic dynamics and reduce congestion in urban environments. In this...

Electric Fleet Charging Management Considering Battery Degradation and Nonlinear Charging Profile

Shi, Junzhe
Zeng, Teng
Moura, Scott
2023

The populations of commercial electric vehicles (EVs) and electric robots (ERs) have been growing rapidly in recent years. Yet, the availabilities and incoordination of the charging infrastructure still constrain the operations of all EVs/ERs, resulting in wasted waiting time and, thus, decreased total profits. Coordinating these electric machines as a fleet and identifying the optimal operation and charging schedules to maximize total profit is essential. On the other hand, the charging process usually consists of two charging stages, constant current (CC) and constant voltage (CV), which...