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Scalable Optimization for Mobility-Aware Coordinated Electric Vehicle Charging in Distribution Power Networks

Ju, Yi
Li, Lunlong
Wang, Jingchun
Scott Moura
2026

Rapid growth in electric-vehicle (EV) charging demand is placing increasing stress on distribution power networks (DPNs), whose hosting capacity is often limited and spatially uneven. Beyond demonstrating that coordination can help, this paper answers an open question that is central for planners: what is the maximal achievable benefit of EV demand flexibility in reducing overload-driven distribution upgrades at a regional scale? Establishing such an upper bound is computationally challenging, as it entails solving and certifying near-optimal solutions to population-scale optimization...

Model-Agnostic Energy Throughput Control for Range and Lifetime Extension of Electric Vehicles via Cell-Level Inverters

Jiang, Shida
Tao, Shengyu
Molina, Vincent
Shi, Junzhe
Scott Moura
2026

A conventional electric vehicle (EV) powertrain relies on a centralized high-voltage DC-AC inverter, thereby limiting cell-level control and potentially reducing overall driving range and battery lifetime. This paper studies an H-bridge-based cell-level inverter topology that performs power conversion at the cell level, enabling independent control of individual cells and expanding the design space for battery management. Leveraging these additional degrees of freedom, we propose a model-agnostic energy-throughput control strategy that extends EV range while improving battery-pack lifetime...

Design Guidelines for Nonlinear Kalman Filters via Covariance Compensation

Jiang, Shida
Lee, Jaewoong
Tao, Shengyu
Scott Moura
2026

Nonlinear extensions of the Kalman filter (KF), such as the extended Kalman filter (EKF) and the unscented Kalman filter (UKF), are indispensable for state estimation in complex dynamical systems, yet the conditions for a nonlinear KF to provide robust and accurate estimations remain poorly understood. This work proposes a theoretical framework that identifies the causes of failure and success in certain nonlinear KFs and establishes guidelines for their improvement. Central to our framework is the concept of covariance compensation: the deviation between the covariance predicted by a...

The Cell Transmission Model. Part I: A Simple Dynamic Representation of Highway Traffic

Carlos Daganzo
1993

This paper presents a simple representation of traffic on a highway with a single entrance and exit. The representation can be used to predict traffic's evolution over time and space, including transient phenomena such as the building, propagation and dissipation of queues. The easy-to-solve difference equations used to predict traffic's evolution are shown to be the discrete analog of the differential equations arising from a special case of the hydrodynamic model of traffic flow. The proposed method automatically generates appropriate changes in density at locations where the...

The Cell Transmission Model: Network Traffic

Carlos Daganzo
1994

This paper shows how the evolution of multicommodity traffic flows over complex networks can be predicted over time, based on a simple macroscopic computer representation of traffic flow that is consistent with the kinematic wave theory under all traffic conditions. After a brief review of the basic model for one link, the paper describes how three-legged junctions can be modeled. It then introduces a numerical procedure for networks, assuming that a time-varying origin-destination table is given and that the proportion of turns at every junction is known. These assumptions are reasonable...

Predictability of Time-Dependent Traffic Backups and Other Reproducible Traits in Experimental Highway Data

Smilowitz, Karen
Carlos Daganzo
1999

Traffic data from a 4-mile long congested rural road in Orinda, California, are used to show that traffic delays and vehicle accumulations between any two generic observers located inside a road section can be predicted from the traffic counts measured at the extremes of the section. The traffic model does not require "recalibration" on the day of the experiment, and works well despite what appears to be location-specific driver behavior.

Fault Diagnosis for Intra-platoon Communications

Simsek, Hidayet Tunc
Raja Sengupta
Yovine, Sergio
Eskafi, Farokh
1999

We are interested in studying the fault diagnostics of platooning vehicles. It is understood that a platoon is a string of vehicles with distributed control strategies. Vehicles rely on real-time control data from other vehicles for correct execution of their control laws. A time-driven system is responsible for delivering the control data.

Estimating ATIS Benefits for the Smart Corridor

Raja Sengupta
Hongola, Bruce
1998

This report studies the effects of Advanced Traveler Information Systems (ATIS) on traffic congestion in the Smart Corridor of the Santa Monica Freeway. Simulation modeling is used to estimate the potential travel time savings to divert traffic from the Smart Corridor to arterial roads when incidents occur. The study attempts to establish relationships between traffic management variables, such as incident detection time, incident duration, capacity reduction, percentage of traffic diversion, and duration of traffic diversion.

Diagnosis and Communication in Distributed Systems

Raja Sengupta
1999

This paper discusses diagnosis problems in distributed systems within the context of a language- theoretic discrete event formalism. A distributed system is seen as a system with multiple spatially separated sites with each site having a diagnoser that observes some of the events generated by the system and diagnoses the faults associated with the site. We allow the diagnosers to share information by sending messages to each other. Distributed systems are classified as being centrally, decentrally, and independently diagnosable. We characterize the class of distributed systems for which...

Safety and Capacity Analysis of Automated and Manual Highway Systems

Carbaugh, Jason
Godbole, Datta N.
Raja Sengupta
1999

This paper compares safety of automated and manual highway systems with respect to result- ing rear-end collision frequency and severity. The results show that automated driving is safer than the most alert manual drivers, at similar speeds and capacities. We also present a detailed safety-capacity tradeo study for four di erent Automated Highway System concepts that di er in their information structure and separation policy.