Nonlinear predictive control for durability enhancement and efficiency improvement in a fuel cell power system

© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/In this work, a nonlinear model predictive control (NMPC) strategy is proposed to improve the efficiency and enhance the durability of a proton exchange membrane fuel cell (PEMFC) power system. The PEMFC controller is based on a distributed parameters model that describes the nonlinear dynamics of the system, considering spatial variations along the gas channels. Parasitic power from different system auxiliaries is considered, including the main parasitic losses which are those of the compressor. A nonlinear observer is implemented, based on the discretised model of the PEMFC, to estimate the internal states. This information is included in the cost function of the controller to enhance the durability of the system by means of avoiding local starvation and inappropriate water vapour concentrations. Simulation results are presented to show the performance of the proposed controller over a given case study in an automotive application (New European Driving Cycle). With the aim of representing the most relevant phenomena that affects the PEMFC voltage, the simulation model includes a two-phase water model and the effects of liquid water on the catalyst active area. The control model is a simplified version that does not consider two-phase water dynamics.Peer ReviewedPostprint (author's final draft

Effect of curing conditions and harvesting stage of maturity on Ethiopian onion bulb drying properties

The study was conducted to investigate the impact of curing conditions and harvesting stageson the drying quality of onion bulbs. The onion bulbs (Bombay Red cultivar) were harvested at three harvesting stages (early, optimum, and late maturity) and cured at three different temperatures (30, 40 and 50 oC) and relative humidity (30, 50 and 70%). The results revealed that curing temperature, RH, and maturity stage had significant effects on all measuredattributesexcept total soluble solids

Computer-aided modeling for efficient and innovative product-process engineering

Model baserede computer understøttet produkt process engineering har opnået øget betydning i forskelligste industrielle brancher som for eksampel farmaceutisk produktion, petrokemi, finkemikalier, polymerer, bioteknologi, fødevarer, energi og vand. Denne trend er forventet at fortsætte på grund af substantielle fordele, hvilke computer understøttede metoder medfører. Den primære forudsætning af computer understøttet produkt process engineering erselvfølgelig den tilgængelighed af modeller af forskellige typer, former og anvendelser. Udviklingen af den påkrævet modellen for de undersøgte systemer er normalt en tidskrævende udfordring og derfor mest også dyrt. Den involverer forskelligste trin, fagekspert viden og dygtighed og forskellige modellerings værktøjer. Formålet af dette projekt er at systematisere den model udviklings proces og anvendelse og dermed øge effektiviteten af modeller såvel somkvaliteten. Den væsentlige bidrag af denne PhD afhandling er en generisk metodologi for proces model udviklingen og anvendelse i kombination med grundige algoritmiske arbejdes diagrammer for de forskellige involverede modeller opgaver og udviklingen af computer understøttede modeller rammer hvilke er strukturbaseret på den generiske metodologi, delvis automatiseret i de forskellige arbejdstrin og kombinerer alle påkrævet værktøjer, understøttelseog vejledning for de forskellige arbejdstrin. Understøttede modelleringsopgaver er etableringen af modeller mål, indsamling af de nødvendige informationer, model formulering inklusive numeriske analyser, etablering af løsningsstrategier og forbinding med den passende løsningsmodul, model identificering og sondering såvel som model anvendelse for simulation og optimering. Den computer understøttede modeller ramme blev implementeret i en brugervenlig software. En række forskellige demonstrationseksempler fra forskellige områder i kemisk ogbiokemiske engineering blev løst for udvikling og validering af den generiske modellerings metodologi og den computer understøttet modeller ramme anvendt på den udviklet software værktøj.Model-based computer aided product-process engineering has attained increased importance in a number of industries, including pharmaceuticals, petrochemicals, fine chemicals, polymers, biotechnology, food, energy and water. This trend is set to continue due to the substantial benefits computer-aided methods provide. The key prerequisite of computer-aided productprocess engineering is however the availability of models of different types, forms andapplication modes. The development of the models required for the systems under investigation tends to be a challenging, time-consuming and therefore cost-intensive task involving numerous steps, expert skills and different modelling tools. The objective of this project is to systematize the process of model development and application thereby increasing the efficiency of the modeller as well as model quality.The main contributions of this thesis are a generic methodology for the process of model development and application, combining in-depth algorithmic work-flows for the different modelling tasks involved and the development of a computer-aided modelling framework. This framework is structured, is based on the generic modelling methodology, partially automates the involved work-flows by integrating the required tools and, supports and guides the userthrough the different work-flow steps. Supported modelling tasks are the establishment of the modelling objective, the collection of the required system information, model construction including numerical analysis, derivation of solution strategy and connection to appropriate solvers, model identification/ discrimination as well as model application for simulation and optimization. The computer-aided modelling framework has been implemented into an userfriendlysoftware.A variety of case studies from different areas in chemical and biochemical engineering have been solved to illustrate the application of the generic modelling methodology, the computeraided modelling framework and the developed software tool

Development of an automated aircraft subsystem architecture generation and analysis tool

Purpose – The purpose of this paper is to present a new computational framework to address future preliminary design needs for aircraft subsystems. The ability to investigate multiple candidate technologies forming subsystem architectures is enabled with the provision of automated architecture generation, analysis and optimization. Main focus lies with a demonstration of the frameworks workings, as well as the optimizers performance with a typical form of application problem. Design/methodology/approach – The core aspects involve a functional decomposition, coupled with a synergistic mission performance analysis on the aircraft, architecture and component levels. This may be followed by a complete enumeration of architectures, combined with a user defined technology filtering and concept ranking procedure. In addition, a hybrid heuristic optimizer, based on ant systems optimization and a genetic algorithm, is employed to produce optimal architectures in both component composition and design parameters. The optimizer is tested on a generic architecture design problem combined with modified Griewank and parabolic functions for the continuous space. Findings – Insights from the generalized application problem show consistent rediscovery of the optimal architectures with the optimizer, as compared to a full problem enumeration. In addition multi-objective optimization reveals a Pareto front with differences in component composition as well as continuous parameters. Research limitations/implications – This paper demonstrates the frameworks application on a generalized test problem only. Further publication will consider real engineering design problems. Originality/value – The paper addresses the need for future conceptual design methods of complex systems to consider a mixed concept space of both discrete and continuous nature via automated methods

Calibratin Of St.Johns River Watershed Hydrology Models for the Water Supply Impact Study

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv

Report on Dynamic Data Reconciliation of Large-Scale Processes

Producción CientíficaAvailability of reliable process information in real time is key in any decision-making procedure. Thus, good industrial decision-support implementations require dealing with gross errors and consideration of process transients in order to get a set of measurements which will be coherent with the basic underlying process dynamics. This report presents dynamic data reconciliation methods and tools adapted to the requirements of industrial environments (large-scale systems and noisy/faulty data). Moreover, basic concepts in literature are extended to artificially increase system redundancy as well as to cope with time-varying parameter estimation. The procedure summarized in this report has been tested in the Lenzing case study.Ingeniería de Sistemas y AutomáticaEuropean Union Horizon 2020 program (grant nº 723575