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• A robust H ∞ control-based input voltage feed-forward compensation framework is proposed for multi-phase DC-DC converters. • An iterative convex-concave optimization procedure is presented for the design of the feedback and feed-forward controllers. • To improve the disturbance rejection, two sensitivity functions are integrated into the H ∞ controller design problem. • The proposed approach is experimentally verified on a 2-leg interleaved boost converter. Generated DC voltages of batteries, fuel cells, or supercapacitors as power sources connected in series with DC-DC converters change according to operating conditions. In such cases, the output voltage stability of the multi-phase DC-DC converters is an issue, particularly being subject to noises in the input voltage and load current disturbances. Input voltage feed-forward (IVFF) compensation approaches can improve the output voltage stability of the DC-DC converters in such scenarios. This paper proposes a robust fixed-order H ∞ based IVFF control framework by considering sensor noise, input voltage, and load current disturbances to improve output voltage stability and reference tracking performance. The mismatched disturbance transfer functions depending on parasitic resistances are derived to include in the controller synthesis process. An iterative convex-concave optimization-based robust fixed-order controller design algorithm is proposed to optimize the feedback and feed-forward controllers under the stability and performance constraints. This algorithm allows the designing of the controllers simultaneously. The feed-forward controller, whose structure is independent of the system transfer functions, is optimized without any model inversion or extra design steps. The performance of the proposed controller is compared with an integral linear quadratic regulator controller, a sliding mode PID controller augmented with a nonlinear disturbance observer, and a fixed-order robust controller designed with non-smooth techniques. Real-time implementation of the fixed-order control systems is performed on a 2-leg 200 W interleaved boost converter. The performances are discussed under external disturbance effects to show the validity of the proposed control approach. [ABSTRACT FROM AUTHOR]

This paper presents a control strategy for hybrid power source based on fuel cell (FC) as the main power source and battery/supercapacitor (SC) as auxiliary power sources for electric vehicle application. In this study, a Battery and SC are auxiliary devices associated with the FC to ensure the power reversibility in the drive train. The FC, Battery, and SC are connected to the DC bus throughout an interleaved boost converter (IBC) and two interleaved bidirectional converters (IBDC) respectively. The paper proposes the control strategy based on power frequency splitting to avoid FC starvation problem, reduce the battery stress and improve the fuel economy of FC. The detail of the control strategy is presented and an Energetic Macroscopic Representation (EMR) is used to develop the whole system. The simulation results are presented to validate the proposed method in the hybrid system. [ABSTRACT FROM AUTHOR]

Fuel cells/electrolyzers are efficient and clean electrochemical devices that convert chemical energy directly into electricity and vice versa. They have attracted sustainable attention over the past decade from multiple experimental and numerical studies. However, detailed experimental investigations are typically expensive and challenging for providing a number of operating conditions and designs. Computational analysis offers an alternative approach for these studies. With the steadily increasing high-performance computing resources available, the limitations of numerical simulations have substantially decreased. This contribution details the design choice and code structure of modern electrochemical devices, which have been implemented as a versatile C++ library named openFuelCell2 within the open-source platform OpenFOAM, allowing for large-scale parallel calculations to be performed. The solver considers the major transport phenomena in a typical electrochemical device, including fluid flow, heat and mass transfer, species and charge transfer, and electrochemical reaction. This enables numerical simulations on popular electrochemical devices, such as fuel cells and electrolyzers, to be conducted. The paper also describes the domain decomposition, and parallel performance issues, as well as future applications. Program Title: openFuelCell2 CPC Library link to program files: https://doi.org/10.17632/cvmb5xgy7h.1 Developer's repository link: https://github.com/openFuelCell2/openFuelCell2 Licensing provisions: GPLv3 Programming language: C++ Journal reference of previous version: S.B. Beale, H.-W. Choi, J.G. Pharoah, H.K. Roth, H. Jasak, D.H. Jeon, Open-source computational model of a solid oxide fuel cell, Computer Physics Communications 200 (2016) 15–26. Does the new version supersede the previous version?: No Reasons for new version: This new version aims to account for additional electrochemical applications. Summary of revisions: The new version employs new code structure designs and is capable of considering two different electric potential fields and two-phase flows. Nature of problem: This software library provides a set of models for simulating electrochemical devices, such as fuel cells and electrolyzers, as well as other similar devices. These systems consist of multiple components with distinct features but are coupled through properties such as temperature, species concentrations, and electric current/potentials. This software utilizes a computational fluid dynamics (CFD) approach to enable the simulation of multiregion and multiphysics problems, accounting for heat and mass transfer, single and two-phase flow, multicomponent diffusion, electron and ion transfer, and electrochemical reactions. This toolbox provides researchers with a powerful tool for studying electrochemical devices in a comprehensive and efficient manner. Solution method: This software utilizes the finite volume method (FVM) to discretize and solve all conserved variables governed by partial differential equations. It employs a variant of the SIMPLE and PISO algorithms, known as PIMPLE, to solve the pressure-velocity coupling. All of the transport equations are solved sequentially, except for the enthalpy equation which is solved in an implicitly coupled manner within the global domain. Additional comments including restrictions and unusual features: • The two-phase flow consists of continuous and dispersed phases, without resolving the phase interfaces. • The two-phase flow is solved with an Eulerian-Eulerian approach. • A local-time-stepping method was typically used in the two-phase solution. • The electrochemical reactions take place in volumetric regions. • Species diffusion is described by Fick's law. [ABSTRACT FROM AUTHOR]

In this paper, an interval arithmetic-based method for parameters identification of a fuel cell equivalent circuit is presented. The fuel cell experimental impedance spectrum, acquired through the electrochemical impedance spectroscopy (EIS), is identified using interval-valued parameters of the fuel cell Fouquet model. The method is based on a branch-and-bound technique, further enhanced using the sensitivity in the segmentation steps. The proposed algorithm is optimised to reduce computational burden and storage memory demand to speed up the computation time and enable onboard applications on fuel cells through embedded system. The result naturally takes into account the uncertainties and noise affecting the impedance measurements. This method easily allows to define a safe operating area for the fuel cell, based on the parameter intervals identified in normal operating conditions. Hence, it is easy to compare the parameter intervals associated to a newly acquired spectrum and check whether they fall out from the safe operating area. This might be considered as a symptom of abnormal operating condition, enabling fuel cell diagnosis, more detailed analyses, and the activation of mitigation and protection strategies. [ABSTRACT FROM AUTHOR]

Fuel cell electric vehicles (FCEVs) are a contemporary technology that is making headway in the expanding automotive industry. To promote FCEV effectiveness, environmentally acceptable limits need to be considered during their whole life cycle. End-of-life automotive fuel cells (AFCs) are one of the major contemporary challenges facing the sustainable business of transportation companies. The paper introduces a hybrid q-rung orthopair fuzzy (q-ROF)-based methodology to handle uncertainties and vagueness. It couples and extends the criteria importance through intercriteria correlation (CRITIC) and evaluation based on distance from average solution (EDAS) methods with q-ROF sets. This research aims to provide essential methodological and practical frameworks, as well as guidelines for improving the effectiveness of engaged FCEVs in transportation companies. The q-ROF CRITIC-EDAS methodology provides a systematic method for prioritizing sustainable approaches for smart waste management of AFCs of road freight vehicles. The incorporation of the real-life case study demonstrates its practical applicability and validity. The introduced q-ROF CRITIC-EDAS model could be extensively applied to the AFC waste management in order to assist stakeholders in making decisions consistent with the sustainability objectives. • Practical and methodological frameworks for smart waste management of EOL AFCs. • The advanced hybrid q-ROF CRITIC-EDAS-based methodology is introduced. • The proposed MCGDM tool can determine the most suitable treatment of EOL AFCs. • Recommendations for solving implementation problems for end-of-life AFCs of FCEVs. • Guidelines for improving the effectiveness of FCEVs in transportation companies. [ABSTRACT FROM AUTHOR]

Abstract: A control-oriented dynamic model of proton exchange membrane fuel cells (PEMFCs) has been developed in this paper. It aims to generate system dynamics with real-time performance for the micro-chip controller design. A unified bond graph approach was employed that integrates physical and chemical domains in the fuel cell operation, including fluid dynamics, heat transfer, and electrochemistry effects. In this paper, two major bond graphs, one for thermofluids, the other for the electrochemical system, were constructed. They are inter-connected to interpret the highly nonlinear transport and reaction system dynamics. The nonlinear simulation on a personal computer (PC) is about four times faster than the realistic operation. A step response test shows that the start-up time of an example PEMFC is about 5s from ambient conditions. Further frequency-response test in the operation region shows that the bandwidth is near 2rad/s. [Copyright &y& Elsevier]

The optimal design of multisource systems, hybrid systems in particular, requires an adequate choice of the energy management strategy. This latter usually impacts source sizing and lifetime. The present paper deals with an energy management approach based on a frequency sharing of the mission. Firstly, the limits of a symmetric frequency energy management are presented in the case of a hybrid system associating a fuel cell with a Li-Ion battery. Subsequently, an original energy “asymmetric” management strategy for the optimal sizing of this association is presented. This strategy is then tested on the “Hydrogen” platform at the LAPLACE research laboratory. Finally, the two energy management strategies are compared in the context of an integrated design by optimization; the asymmetric strategy offers significant gains in terms of system weight, which is important for embedded applications. [ABSTRACT FROM AUTHOR]

The paper deals with controlling an autonomous electric power system that comprises of a primary source of power supply, Proton Exchange Membrane fuel cell (PEMFC), DC–DC boost power converter as a power conditioner, and the ultracapacitor for an auxiliary power supply. Relative degree approach is applied for direct control of the output load voltage as well as the fuel cell and ultracapacitor current in the presence of the model uncertainties. The zero dynamics of the studied electric power system is analyzed and appeared to be stable. The non-minimum phase property of the DC–DC boost converter is eliminated by controlling the fuel cell current based on the power balance. The adaptive super-twisting sliding mode observer is employed for identification of the load resistance, which estimated value is used for generating the fuel cell current command profile. The adaptive gain second order (2-SM) super-twisting sliding mode controller is proposed for controlling the current in PEMFC. The conventional Sliding Mode Controllers (SMC) is designed for controlling the output voltage of the converter and the load current of the ultracapacitor. The efficacy and robustness of the proposed decentralized three-fold electric power system controller that consists of two SMCs and one 2-SM adaptive-gain controller are confirmed via computer simulations. [ABSTRACT FROM AUTHOR]

Abstract: This paper deals with the problem of controlling energy generation systems including fuel cells (FCs) and interleaved boost power converters. The proposed nonlinear adaptive controller is designed using sliding mode control (SMC) technique based on the system nonlinear model. The latter accounts for the boost converter large-signal dynamics as well as for the fuel-cell nonlinear characteristics. The adaptive nonlinear controller involves online estimation of the DC bus impedance ‘seen’ by the converter. The control objective is threefold: (i) asymptotic stability of the closed loop system, (ii) output voltage regulation under bus impedance uncertainties and (iii) equal current sharing between modules. It is formally shown, using theoretical analysis and simulations, that the developed adaptive controller actually meets its control objectives. [Copyright &y& Elsevier]

Abstract: Hybrid electrical vehicles combine two or more energy sources (at least one electrical) to benefit from their different characteristics regarding autonomy, reversibility and dynamic response. Energy management consists in discovering an energy distribution between the different energy sources whilst meeting different design requirements such as comfort or energy consumption minimization. This paper aims to design a fuzzy logic controller to manage the energy in a hybrid electrical vehicle equipped with three different energy sources: batteries, a supercapacitors system and a fuel cell system. We use human expertise to design the fuzzy logic controller. A survey using linguistic labels was conducted among experts in hybrid electrical vehicles. As each expert has defined different fuzzy sets and rules we use type-2 fuzzy sets, that permit to combine the knowledge from the experts handling the uncertainty associated with the meaning of the words. The proposed fuzzy logic controller is evaluated by computer simulation. [Copyright &y& Elsevier]

Abstract: Proton Exchange Membrane Fuel Cell (PEMFC) systems are more and more presented as a good alternative to current energy converters such as internal combustion engines. They suffer however from insufficient reliability and durability for stationary and transport applications. Reliability and lifetime may be improved by suitable fault detection and localization. Traditionally, fault diagnosis in fuel cell systems needs the knowledge of number of parameters, which might require a special inner parameter monitoring setup. This is difficult, even impossible with respect to fuel cell stacks geometry. Moreover, with respect to the transportation application that aims at minimizing the embedded instrumentation, simple diagnosis methods involving non-intrusive and easy-to-monitor parameters are highly desired in PEMFC systems. We present in this paper a flooding diagnosis procedure based on black-box model. This diagnosis method allows automating the flooding diagnosis and the parameters used are minimal, low-cost and simple to monitor. The model inputs are some variables that are critical for water management in the PEMFC and consequently for fuel cell performances while the output is a variable that can be monitored in a non-intrusive way and can be used to detect flooding (namely pressure drop through the cathode). The flooding diagnosis procedure is based on the analysis of a residual obtained from the comparison between an experimental and an estimated pressure drop. The estimation of this latter is ensured by an artificial Neural Network that has been trained with flooding-free data. Fault detection is obtained by means of a residual analysis. It has been successfully tested under different experimental conditions including non-flooding and deliberately induced flooding as well as a succession of the two states of health. A proposition to include drying out problems is given as perspective to this work. [ABSTRACT FROM AUTHOR]