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Esteban R. Gelso

Bio: Esteban R. Gelso is an academic researcher from Volvo. The author has contributed to research in topics: Fault detection and isolation & Constraint satisfaction problem. The author has an hindex of 8, co-authored 31 publications receiving 363 citations. Previous affiliations of Esteban R. Gelso include University of Girona & Chalmers University of Technology.

Papers
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Journal ArticleDOI
TL;DR: In this paper, the authors present an on-line current monitoring system that uses both techniques for fault detection and diagnosis in the stator and in the rotor of three phase induction motors.

127 citations

Journal ArticleDOI
TL;DR: In this article, the issue of residual generation using structural analysis has been studied by several authors, and four recently proposed algorithms that solve this problem are presented and compared, and compared with each other.

60 citations

Journal ArticleDOI
TL;DR: In this paper, convex optimization and modelling for component sizing and optimal energy management control of hybrid electric vehicles is studied. But the authors focus on the modeling steps required to include a battery wear model into the convex optimisation problem.

37 citations

Journal ArticleDOI
Esteban R. Gelso1, Johan Dahl1
TL;DR: In this article, a model-based multi-variable control strategy is applied to the air-path control of a turbocharged Diesel engine, where an exhaust gas recirculation (EGR) valve, and a variable-geometry turbocharger (VGT), are controlled using a technique called Model Predictive Control (MPC).

21 citations

Journal ArticleDOI
01 Apr 2009
TL;DR: The modal interval analysis (MIA) is used because it provides powerful tools to extend the calculations over real functions to intervals and checks the consistency between the system's behavior, obtained from the measurements, and the model's behavior; if they are inconsistent, then there is a fault.
Abstract: One of the techniques used to detect faults in dynamic systems is analytical redundancy. An important difficulty in applying this technique to real systems is dealing with the uncertainties associated with the system itself and with the measurements. In this paper, this uncertainty is taken into account by the use of intervals for the parameters of the model and for the measurements. The method that is proposed in this paper checks the consistency between the system's behavior, obtained from the measurements, and the model's behavior; if they are inconsistent, then there is a fault. The problem of detecting faults is stated as a quantified real constraint satisfaction problem, which can be solved using the modal interval analysis (MIA). MIA is used because it provides powerful tools to extend the calculations over real functions to intervals. To improve the results of the detection of the faults, the simultaneous use of several sliding time windows is proposed. The result of implementing this method is semiqualitative tracking (SQualTrack), a fault-detection tool that is robust in the sense that it does not generate false alarms, i.e., if there are false alarms, they indicate either that the interval model does not represent the system adequately or that the interval measurements do not represent the true values of the variables adequately. SQualTrack is currently being used to detect faults in real processes. Some of these applications using real data have been developed within the European project advanced decision support system for chemical/petrochemical manufacturing processes and are also described in this paper.

14 citations


Cited by
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Book ChapterDOI
11 Dec 2012

1,704 citations

Journal ArticleDOI
TL;DR: In this article, the optimal HESS dimensioning and energy management of a fuel cell hybrid electric bus was discussed, where the authors used efficient convex programming to simultaneously optimize the HESS dimensions, including sizes of both the battery pack and the supercapacitor stack.

261 citations

Journal ArticleDOI
06 Jan 2012
TL;DR: In this article, a survey of model-based fault detection methods for aerospace systems is presented, focusing on those methods that are applicable to aerospace systems and highlighting the characteristics of aerospace models, generic non-linear dynamical modelling from flight mechanics is recalled and a unifying representation of sensor and actuator faults is presented.
Abstract: This survey of model-based fault diagnosis focuses on those methods that are applicable to aerospace systems. To highlight the characteristics of aerospace models, generic non-linear dynamical modelling from flight mechanics is recalled and a unifying representation of sensor and actuator faults is presented. An extensive bibliographical review supports a description of the key points of fault detection methods that rely on analytical redundancy. The approaches that best suit the constraints of the field are emphasized and recommendations for future developments in in-flight fault diagnosis are provided.

235 citations

Journal ArticleDOI
TL;DR: A model predictive control framework is established to minimize the total running cost of a fuel cell/battery hybrid electric bus, inclusive of hydrogen cost and costs caused by fuel cell and battery degradation.
Abstract: Energy management is an enabling technology for increasing the economy of fuel cell/battery hybrid electric vehicles. Existing efforts mostly focus on optimization of a certain control objective (e.g., hydrogen consumption), without sufficiently considering the implications for on-board power sources degradation. To address this deficiency, this article proposes a cost-optimal, predictive energy management strategy, with an explicit consciousness of degradation of both fuel cell and battery systems. Specifically, we contribute two main points to the relevant literature, with the purpose of distinguishing our study from existing ones. First, a model predictive control framework, for the first time, is established to minimize the total running cost of a fuel cell/battery hybrid electric bus, inclusive of hydrogen cost and costs caused by fuel cell and battery degradation. The efficacy of this framework is evaluated, accounting for various sizes of prediction horizon and prediction uncertainties. Second, the effects of driving and pricing scenarios on the optimized vehicular economy are explored.

223 citations

Journal ArticleDOI
TL;DR: Overall, this paper includes review of system signals, conventional and advance signal processing techniques; however, it mainly covers, the selection of effective statistical features, AI methods, and associated training and testing strategies for fault diagnostics of IMs.

220 citations