Rationale, study design, and analysis plan of the Alveolar Recruitment for ARDS Trial (ART): Study protocol for a randomized controlled trial

Background: Acute respiratory distress syndrome (ARDS) is associated with high in-hospital mortality. Alveolar recruitment followed by ventilation at optimal titrated PEEP may reduce ventilator-induced lung injury and improve oxygenation in patients with ARDS, but the effects on mortality and other clinical outcomes remain unknown. This article reports the rationale, study design, and analysis plan of the Alveolar Recruitment for ARDS Trial (ART). Methods/Design: ART is a pragmatic, multicenter, randomized (concealed), controlled trial, which aims to determine if maximum stepwise alveolar recruitment associated with PEEP titration is able to increase 28-day survival in patients with ARDS compared to conventional treatment (ARDSNet strategy). We will enroll adult patients with ARDS of less than 72 h duration. The intervention group will receive an alveolar recruitment maneuver, with stepwise increases of PEEP achieving 45 cmH(2)O and peak pressure of 60 cmH2O, followed by ventilation with optimal PEEP titrated according to the static compliance of the respiratory system. In the control group, mechanical ventilation will follow a conventional protocol (ARDSNet). In both groups, we will use controlled volume mode with low tidal volumes (4 to 6 mL/kg of predicted body weight) and targeting plateau pressure <= 30 cmH2O. The primary outcome is 28-day survival, and the secondary outcomes are: length of ICU stay; length of hospital stay; pneumothorax requiring chest tube during first 7 days; barotrauma during first 7 days; mechanical ventilation-free days from days 1 to 28; ICU, in-hospital, and 6-month survival. ART is an event-guided trial planned to last until 520 events (deaths within 28 days) are observed. These events allow detection of a hazard ratio of 0.75, with 90% power and two-tailed type I error of 5%. All analysis will follow the intention-to-treat principle. Discussion: If the ART strategy with maximum recruitment and PEEP titration improves 28-day survival, this will represent a notable advance to the care of ARDS patients. Conversely, if the ART strategy is similar or inferior to the current evidence-based strategy (ARDSNet), this should also change current practice as many institutions routinely employ recruitment maneuvers and set PEEP levels according to some titration method.Hospital do Coracao (HCor) as part of the Program 'Hospitais de Excelencia a Servico do SUS (PROADI-SUS)'Brazilian Ministry of Healt

Electrochemical Modeling, Supervision and Control of Lithium-Ion Batteries

This thesis develops an advanced battery monitoring and control system based on the electrochemical principles that govern lithium-ion battery dynamics. This work is motivated by the need of having safer and better energy storage systems for all kind of applications, from small scale portable electronics to large scale renewable energy storage. In this context, lithium-ion batteries have become the enabling technology for energy autonomy in appliances (e.g. mobile phone, electric vehicle) and energy self-consumption in households. However, batteries are oversized and pricey, might be unsafe, are slow to charge and may not equalize the lifetime of the application they are intended to power. This work tackles these different issues.This document first introduces the general context of the battery management problem, as well as the particular issues that arise when modeling, supervising and controlling the battery short-term and long-term operation. Different solutions coming from the literature are reviewed, and several standard tools borrowed from control theory are exposed. Then, starting by well-known contributions in electrochemical modeling, we proceed to develop reduced-order models for the battery operation including degradation mechanisms, that are highly descriptive of the real phenomena taking place. This modeling framework is the cornerstone of all the monitoring and control development that follows.Next, we derive a battery diagnosis system with a twofold objective. First, indicators for internal faults affecting the battery state-of-health are obtained. Secondly, detection and isolation of sensor faults is achieved. Both tasks rely on state observers designed from electrochemical models to perform state estimation and residual generation. Whereas the former solution resorts to system identification techniques for health monitoring, the latter solution exploits fault diagnosis for instrumentation assessment.We then develop a feedback battery charge strategy able to push in performance while accounting for constraints associated to battery degradation. The fast and safe charging capabilities of the proposed approach are ultimately validated through long-term cycling experiments. This approach outperforms widely used commercial charging strategies in terms of both charging speed and degradation.The main contribution of this thesis is the exploitation of first principles models to develop battery management strategies towards improving safety, charging time and lifetime of battery systems without jeopardizing performance. The obtained results show that system and control theory offer opportunities to improve battery operation, aside from the material sciences contributions to this field.Doctorat en Sciences de l'ingénieur et technologieinfo:eu-repo/semantics/nonPublishe

A new reference governor strategy for union of linear constraints

Classical scalar Reference Governor (RG) schemes require a convex admissible region. Recently, a novel scalar RG approach has been proposed for the case of nonconvex constraints that can be approximated as union of polyhedral sets. This new method, specifically developed for the charge control of lithium-ion batteries, shows good performance and the capability of handling these kind of constraints while keeping a very low computational footprint. However, this method can guarantee that the system will reach the desired set point only under very specific properties of the constraints. In this paper, we analyze these limitations and propose a solution that ensures convergence of the RG scheme under much milder conditions on the topology of the constraints.SCOPUS: cp.pDecretOANoAutActifinfo:eu-repo/semantics/publishe

Partition-based Unscented Kalman Filter for Reconfigurable Battery Pack State Estimation using an Electrochemical Model

info:eu-repo/semantics/publishe

Internal and sensor fault detection and isolation for lithium-ion batteries

info:eu-repo/semantics/publishe

Resolving Kirchhoff's Laws for Parallel Li-Ion Battery Pack State-Estimators

info:eu-repo/semantics/publishe

SOC and SOH estimation for Li-ion battery based on an equivalent hydraulic model. Part II: SOH power fade estimation

This paper aims at developing a management system for a lithium-ion battery in order to monitor its state-of-health. Based on the electrochemical processes within the battery, state-of-health indicators are deduced from the solid phase diffusion coefficients that describe the propagation of lithium in each electrode. Hence the estimation of these diffusion coefficients is the focus of the paper. The proposedmethod properly accounts for measurement noise and provides a confidence interval for the estimates. It relies on a three step procedure. A temporal transfer function is first highlighted from the partial differential equation describing the evolution of the lithium concentration inside the particles. Next a nonlinear parameter estimation problem for the transfer function identification is solved by resorting to the so-called simplified refined instrumental variable method. From this first estimation, the diffusion coefficients are then computed. A resampling schemeis used to estimate a confidence interval for the estimated parameters.info:eu-repo/semantics/publishe

A new reference governor strategy for Union of Linear Constraints

info:eu-repo/semantics/publishe

Electrode-Level State Estimation in Lithium-ion Batteries via Kalman Decomposition

Lithium-ion battery electrode-level online state estimation using high-fidelity nonlinear electrochemical models remains a key challenge. This is particularly due to weak observability inherited from the complex model structure, even for reduced-order electrochemical models. This manuscript presents a systematic and rigorous strategy to analyze the local observability of a single particle model (SPM) with both electrodes, which is commonly known to be locally unobservable from current-voltage measurements. Estimating the essential states, e.g. state of charge (SOC) and solid-phase lithium surface concentration, is crucial for battery charge and health monitoring since different degradation mechanisms affect each electrode individually. In this manuscript, the proposed observability analysis approach based on the Kalman decomposition enables provably convergent estimates. Ultimately, using the observability analysis, we propose a state estimator based on the nonlinear SPM dynamics and prove estimation error system stability. The observability analysis and state estimation scheme exploits the conservation of lithium property. Simulations demonstrate the effectiveness of the electrode-level state estimator as opposed to the cell-level estimator.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Robust observer design for discrete-time locally one-sided Lipschitz systems

The robust estimation of discrete-time one-sided Lipschitz systems is considered. A linear matrix inequality based approach is presented to design a nonlinear state observer such that the input-to-state stability of the estimation error is locally guaranteed while minimizing an upper-bound on the ℓ∞-induced system norm from the disturbance input to the error system performance output. The effectiveness of the approach is demonstrated in simulation for several numerical examples.SCOPUS: ar.jinfo:eu-repo/semantics/publishe