arXiv subjects

Hosam K. Fathy

Publications and source records attributed to Hosam K. Fathy.

7 recordsLinked to original sources

arXiv2026

Designing Barrier Functions for Graceful Safety Control

This paper examines the problem of achieving "grace" when controlling dynamical systems for safety, which is defined in terms of providing multi-layered safety assurances. Namely, two safety layers are created: a primary layer that represents a desirable degree of safety, and a secondary failsafe layer. Graceful control then involves ensuring that even if the primary layer is breached, the failsafe layer remains forward invariant. The paper pursues this goal by constructing a safety constraint that combines the concepts of zeroing and reciprocal control barrier functions with regard to the primary and secondary safe sets, respectively. This constraint is analogous to a stiffening spring, making it possible to construct energy-based analytical proofs of the resulting graceful safety guarantees. The proposed approach is developed for systems with a relative degree of either 1 or 2, the latter case being particularly useful for mechanical systems. We demonstrate the applicability of the method using a wall collision avoidance example. This demonstration highlights the benefits of the proposed approach compared to traditional benchmarks from the literature.

eess.SY↗

arXiv2021

Monitoring and Control System Development and Experimental Validation for a Novel Extrapulmonary Respiratory Support Setup

This paper presents a novel mechatronic setup intended for providing respiratory support to patients suffering from pulmonary failure. The setup relies upon the circulation of an oxygenated perfluorocarbon (PFC) through the abdominal cavity. Such circulation provides a potential pathway for the transport of oxygen to the bloodstream. However, the viability of this technology for $CO_2$ clearance has not been established. Moreover, there is a lack of experimental data enabling the modeling and identification of the underlying dynamics of this technology. To address these gaps, we develop a flexible experimental perfusion setup capable of monitoring and controlling key variables such as perfusate flowrate, temperature, pressure, and oxygenation. The paper (i) briefly summarizes the design of this setup; (ii) highlights the degree to which its data acquisition system enables the collection and cross-correlation of both perfusion-related and physiological variables; and (iii) discusses the development of flow, pressure, and temperature control algorithms for the setup. Experiments with large animals (swine) show that the setup is capable of successfully controlling the perfusion process, as well as gathering extensive data to support subsequent modeling and identification studies.

physics.med-ph↗

arXiv2021

Fisher Identifiability Analysis of Longitudinal Vehicle Dynamics

This paper investigates the theoretical Cramer-Rao bounds on estimation accuracy of longitudinal vehicle dynamics parameters. This analysis is motivated by the value of parameter estimation in various applications, including chassis model validation and active safety. Relevant literature addresses this demand through algorithms capable of estimating chassis parameters for diverse conditions. While the implementation of such algorithms has been studied, the question of fundamental limits on their accuracy remains largely unexplored. We address this question by presenting two contributions. First, this paper presents theoretical findings which reveal the prevailing effects underpinning vehicle chassis parameter identifiability. We then validate these findings with data from on-road experiments. Our results demonstrate, among a variety of effects, the strong relevance of road grade variability in determining parameter identifiability from a drive cycle. These findings can motivate improved experimental designs in the future.

eess.SY↗

arXiv2021

Parameter Identification and Sensitivity Analysis for Zero-dimensional Physics-based Lithium-Sulfur Battery Models

This paper examines the problem of estimating the parameters of a Lithium-Sulfur (LiS) battery from experimental cycling data. LiS batteries are attractive compared to traditional Lithium-Ion batteries, thanks largely to their potential to provide higher energy densities. The literature presents a number of different LiS battery models, with different fidelities and complexities. This includes both higher-fidelity diffusion-reaction models as well as "zero-dimensional" models that neglect diffusion dynamics while capturing the physics of the underlying reduction-oxidation reactions. The paper focuses on zero-dimensional LiS battery models, and develops four such models from the literature, reflecting different choices of which redox reactions to model. There is a growing need for using experimental cycling datasets to both parameterize these models and compare their fidelities. To address this need, we fabricated LiS coin cells and performed charge/discharge cycling tests on these cells. In parallel, we analyzed the sensitivity of simulated LiS battery charge/discharge characteristics to underlying model parameters. Using this sensitivity analysis, we selected a subset of model parameters for identification, and estimated these parameters for all four LiS battery models from cycling data, thereby arriving at a consistent experimental comparison and assessment of these models' respective fidelities.

eess.SY↗

arXiv2020

Pulse-and-Glide Driving with Drivability Constraints: A Pontryagin Approach

This paper uses Pontryagin methods to analyze pulse-and-glide driving for different nominal vehicle speeds. There is significant literature supporting the fact that pulse-and-glide has the potential to reduce fuel consumption compared to driving at a constant speed, but the benefits at a variety of nominal speeds remain relatively unexplored. Building on the literature, we formulate a speed trajectory optimization problem where the objective is a linearly-scalarized Pareto combination of fuel consumption and average vehicle speed, in addition to a quadratic penalty on jerk. By analyzing this optimization problem using Pontryagin methods, we show that (i) for each nominal speed, there is a critical penalty on jerk below which the optimal solution is pulse-and-glide, (ii) without any penalty on jerk, the optimal pulse-and-glide trajectory switches infinitely fast, and (iii) above a critical nominal velocity, the optimal solution is steady-speed driving rather than pulse-and-glide, regardless of the penalty on jerk.

math.OC↗

arXiv2020

Reducing Road Vehicle Fuel Consumption by Exploiting Connectivity and Automation: A Literature Survey

This paper examines the degree to which connectivity and automation can potentially reduce the overall fuel consumption of on-road vehicles. The paper begins with a simulation study highlighting the tradeoff between: (i) the fuel that a vehicle can save through speed trajectory shaping, versus (ii) the additional inter-vehicle spacing needed for this trajectory shaping to be feasible. This study shows that connectivity and automation are essential, rather than merely useful, for substantial reductions in the fuel consumed by fixed on-road vehicle powertrain/chassis configurations in traffic. Motivated by this insight, we survey the literature on the fuel savings achievable through different connected/automated vehicle technologies. This includes optimal vehicle routing, eco-arrival/departure at intersections, platooning, speed trajectory optimization, predictive driveline disengagement, predictive gear shifting, and predictive powertrain accessory control. This survey shows that the ability to shape vehicle speed trajectories collaboratively plays a dominant role in reducing urban/suburban fuel consumption, while platooning plays a dominant role in influencing the attainable fuel savings on the highway. Moreover, the survey shows that the degree to which connectivity/automation can reduce on-road vehicle fuel consumption, in both urban/suburban and highway settings, depends critically on the integration of powertrain- and chassis-level control.

eess.SY↗

arXiv2020

Online State Estimation for a Physics-Based Lithium-Sulfur Battery Model

This article examines the problem of Lithium-Sulfur (Li-S) battery state estimation. Such estimation is important for the online management of this energy-dense chemistry. The literature uses equivalent circuit models (ECMs) for Li-S state estimation. This article's main goal is to perform estimation using a physics-based model instead. This approach is attractive because it furnishes online estimates of the masses of individual species in a given Li-S cell. The estimation is performed using an experimentally-validated, computationally tractable zero-dimensional model. Reformulation converts this model from differential algebraic equations (DAEs) to ordinary differential equations (ODEs), simplifying the estimation problem. The article's first contribution is to show that this model has poor observability, especially in the low plateau region, where the low sensitivity of cell voltage to precipitated sulfur mass complicates the estimation of this mass. The second contribution is to exploit mass conservation to derive a reduced-order model with attractive observability properties in both high and low plateau regions. The final contribution is to use an unscented Kalman filter (UKF) for estimating internal Li-S battery states, while taking constraints on species masses into account. Consistent with the article's observability analysis, the UKF achieves better low-plateau estimation accuracy when the reduced-order model is used.

eess.SY↗