Dynamic modeling, simulation, and MIMO predictive control of a tubular solid oxide fuel cell

Spivey, Benjamin J.; Edgar, Thomas F.

doi:10.1016/j.jprocont.2012.01.015

Cited by 63 publications

(31 citation statements)

References 26 publications

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“…Combination of the limitations Fig. 6 gives an overview of the authorized domain for the actuating variables if one considers the three constraints (16), (18), and (19). To introduce Fig.…”

Section: Limitation Due To the Stack Fuel Utilizationmentioning

confidence: 99%

See 1 more Smart Citation

Feed-forward control of a solid oxide fuel cell system with anode offgas recycle

Carré¹,

Brandenburger²,

Friede³

et al. 2015

Journal of Power Sources

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“…Combination of the limitations Fig. 6 gives an overview of the authorized domain for the actuating variables if one considers the three constraints (16), (18), and (19). To introduce Fig.…”

Section: Limitation Due To the Stack Fuel Utilizationmentioning

confidence: 99%

“…Further MPC under constraints applied to SOFC-systems are presented in Refs. [16,17]. MPC under constraints appears to be a meaningful complementary control algorithm to replace or extend any existing low-level control strategy, e.g.…”

Section: Comparison With the State Of The Artmentioning

confidence: 99%

Feed-forward control of a solid oxide fuel cell system with anode offgas recycle

Carré¹,

Brandenburger²,

Friede³

et al. 2015

Journal of Power Sources

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“…In 2009, Mueller demonstrated improved control of voltage and cell temperature variation along with faster load following using a Multiple Input Multiple Output (MIMO) Linear Quadratic Regulator (LQR) controller compared to a multi-loop SISO controller; results showed further work was needed to control mean temperature [11]. In 2011, Spivey developed a dynamic, first-principles tubular SOFC model and implemented linear MIMO Model Predictive Control (MPC) to control power output, fuel utilization, steam-to-carbon ratio, minimum cell temperature, and maximum radial thermal gradient [12]. The absolute and delta temperatures which are critical for extending SOFC lifetime along with steam to carbon ratio, fuel utilization, air utilization were held within tight constraints while power loads were met.…”

Section: B Model Predictive Control Of Sofc Systemsmentioning

confidence: 99%

Model predictive control with a rigorous model of a Solid Oxide Fuel Cell

Jacobsen

Spivey

Hedengren

2013

2013 American Control Conference

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by maintaining reliability parameters during load changes. These reliability parameters are critical to maintain power generation efficiency over an extended life of the SOFC. For SOFCs to be commercially viable, the life must exceed 20,000 hours for load following applications. This is not yet achieved because transient stresses damage the fuel cell and degrade the performance over time. This study relates the development of a dynamic model for SOFC systems in order to predict optimal manipulated variable moves along a prediction horizon. The model consists of hundreds of states and parameters that permit tracking of a realistic response. Previously, this detailed model was too computationally intensive to run in parallel with the SOFC process. The contribution of this paper is an application study to enable a large-scale simulation model to be used in Model Predictive Control (MPC) without simplification. Such a technology permits real time calculation of controller moves while loads are followed during operation. The contribution demonstrates the assumptions and approach necessary to provide real-time calculations for optimal predictive control operations using a rigorous model of the SOFC process. Large-scale process models are rarely employed in real-time control because of the prohibitive computational expense necessary to complete the calculations within the specified cycle time. An efficient model based predictive controller reduces operational fluctuations related to the startup and shutdown conditions, without exceeding reliability limits in the cells.

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“…The SOFC dynamic models range from zero-dimensional (0-D) to three-dimensional (3-D). Both 2-D and 3-D models can be used for the cell geometrical design and thermal stress analysis [13][14][15]. These models are able to accurately represent the behavior of the FC at the expense of a heavy computational burden and are not suitable for power system studies.…”

Section: Introductionmentioning

confidence: 99%

Hierarchical Load Tracking Control of a Grid-Connected Solid Oxide Fuel Cell for Maximum Electrical Efficiency Operation

Zhu³

2015

Energies

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Based on the benchmark solid oxide fuel cell (SOFC) dynamic model for power system studies and the analysis of the SOFC operating conditions, the nonlinear programming (NLP) optimization method was used to determine the maximum electrical efficiency of the grid-connected SOFC subject to the constraints of fuel utilization factor, stack temperature and output active power. The optimal operating conditions of the grid-connected SOFC were obtained by solving the NLP problem considering the power consumed by the air compressor. With the optimal operating conditions of the SOFC for the maximum efficiency operation obtained at different active power output levels, a hierarchical load tracking control scheme for the grid-connected SOFC was proposed to realize the maximum electrical efficiency operation with the stack temperature bounded. The hierarchical control scheme consists of a fast active power control and a slower stack temperature control. The active power control was developed by using a decentralized control method. The efficiency of the proposed hierarchical control scheme was demonstrated by case studies using the benchmark SOFC dynamic model.

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Dynamic modeling, simulation, and MIMO predictive control of a tubular solid oxide fuel cell

Cited by 63 publications

References 26 publications

Feed-forward control of a solid oxide fuel cell system with anode offgas recycle

Feed-forward control of a solid oxide fuel cell system with anode offgas recycle

Model predictive control with a rigorous model of a Solid Oxide Fuel Cell

Hierarchical Load Tracking Control of a Grid-Connected Solid Oxide Fuel Cell for Maximum Electrical Efficiency Operation

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