Experimental Evaluation of a Control Strategy for Real-Time Optimization of Low Temperature PEM Fuel Cell Stack

2009 ◽  
Author(s):  
Panini Kolavennu ◽  
Susanta K. Das ◽  
K. Joel Berry
Keyword(s):  
Fuel Cell ◽  
Real Time ◽  
Control Strategy ◽  
Pem Fuel Cell ◽  
Effective Control ◽  
Feed Forward ◽  
Fuel Cell Stack ◽  
Feed Forward Control ◽  
Time Optimization ◽  
Real Time Optimization

A robust control strategy which ensures optimum performance is crucial to proton exchange membrane (PEM) fuel cell development. In a PEM fuel cell stack, the primary control variables are the reactant’s stochiometric ratio, membrane’s relative humidity and operating pressure of the anode and cathode. In this study, a 5 kW (25-cell) PEM fuel cell stack is experimentally evaluated under various operating conditions. Using the extensive experimental data of voltage-current characteristics, a feed forward control strategy based on a 3D surface map of cathode pressure, current density and membrane humidity at different operating voltages is developed. The effectiveness of the feed forward control strategy is tested on the Green-light testing facility. To reduce the dependence on predetermined system parameters, real-time optimization based on extremum seeking algorithm is proposed to control the air flow rate into the cathode of the PEM fuel cell stack. The quantitative results obtained from the experiments show good potential towards achieving effective control of PEM fuel cell stack.

scholarly journals Experimental real-time optimization of a solid oxide fuel cell stack via constraint adaptation

Energy ◽  
2012 ◽  
Vol 39 (1) ◽  
pp. 54-62 ◽  
Author(s):  
Gene A. Bunin ◽  
Zacharie Wuillemin ◽  
Grégory François ◽  
Arata Nakajo ◽  
Leonidas Tsikonis ◽  
...  
Keyword(s):  
Fuel Cell ◽  
Solid Oxide Fuel Cell ◽  
Real Time ◽  
Solid Oxide ◽  
Oxide Fuel ◽  
Fuel Cell Stack ◽  
Time Optimization ◽  
Real Time Optimization

scholarly journals Two-Layered Real-Time Optimization of a Solid Oxide Fuel Cell Stack

2010 ◽  
Vol 43 (5) ◽  
pp. 847-852 ◽  
Author(s):  
Gene A. Bunin ◽  
Grégory François ◽  
Dominique Bonvin
Keyword(s):  
Fuel Cell ◽  
Solid Oxide Fuel Cell ◽  
Real Time ◽  
Solid Oxide ◽  
Oxide Fuel ◽  
Fuel Cell Stack ◽  
Time Optimization ◽  
Real Time Optimization

Air Flow Real-time Optimization Strategy for Fuel Cell Hybrid Power Sources with Fuel Flow Based on Load-following

Fuel Cells ◽  
2018 ◽  
Vol 18 (6) ◽  
pp. 809-823 ◽  
Author(s):  
N. Bizon ◽  
G. Iana ◽  
E. Kurt ◽  
P. Thounthong ◽  
M. Oproescu ◽  
...  
Keyword(s):  
Fuel Cell ◽  
Real Time ◽  
Cell Hybrid ◽  
Optimization Strategy ◽  
Power Sources ◽  
Hybrid Power ◽  
Load Following ◽  
Fuel Flow ◽  
Time Optimization ◽  
Real Time Optimization

Robust Real-Time Optimization of a Solid Oxide Fuel Cell Stack

2011 ◽  
Vol 8 (5) ◽  
Author(s):  
A. Marchetti ◽  
A. Gopalakrishnan ◽  
B. Chachuat ◽  
D. Bonvin ◽  
L. Tsikonis ◽  
...  
Keyword(s):  
Fuel Cell ◽  
Solid Oxide Fuel Cell ◽  
Real Time ◽  
Optimization Problem ◽  
Solid Oxide ◽  
Step Response ◽  
Oxide Fuel ◽  
Power Demand ◽  
Time Optimization ◽  
Real Time Optimization

On-line control and optimization can improve the efficiency of fuel cell systems, whilst simultaneously ensuring that the operation remains within a safe region. Also, fuel cells are subject to frequent variations in their power demand. This paper investigates the real-time optimization (RTO) of a solid oxide fuel cell (SOFC) stack. An optimization problem maximizing the efficiency subject to operating constraints is defined. Due to inevitable model inaccuracies, the open-loop implementation of optimal inputs evaluated off-line may be suboptimal, or worse, infeasible. Infeasibility can be avoided by controlling the constrained quantities. However, the constraints that determine optimal operation might switch with varying power demand, thus requiring a change in the regulator structure. In this paper, a control strategy that can handle plant-model mismatch and changing constraints in the face of varying power demand is presented and illustrated. The strategy consists in the integration of RTO and model predictive control (MPC). A lumped model of the SOFC is utilized at the RTO level. The measurements are not used to re-estimate the parameters of the SOFC model at different operating points, but to simply adapt the constraints in the optimization problem. The optimal solution generated by RTO is implemented using MPC that uses a step-response model in this case. Simulation results show that near-optimality can be obtained, and constraints are respected despite model inaccuracies and large variations in the power demand.

Real-Time Implementation of Optimal Energy Management in Hybrid Electric Vehicles: Globally Optimal Control of Acceleration Events

2020 ◽  
Vol 142 (8) ◽  
Author(s):  
Zachary D. Asher ◽  
David A. Trinko ◽  
Joshua D. Payne ◽  
Benjamin M. Geller ◽  
Thomas H. Bradley
Keyword(s):  
Optimal Control ◽  
Real Time ◽  
Fuel Economy ◽  
Control Strategy ◽  
Limited Information ◽  
Optimal Control Strategy ◽  
Time Optimization ◽  
Vehicle Operation ◽  
Operation Knowledge ◽  
Real Time Optimization

Abstract Widely published research shows that significant fuel economy improvements through optimal control of a vehicle powertrain are possible if the future vehicle velocity is known and real-time optimization calculations can be performed. In this research, however, we seek to advance the field of optimal powertrain control by limiting future vehicle operation knowledge and using no real-time optimization calculations. We have realized optimal control of acceleration events (AEs) in real-time by studying optimal control trends across 384 real world drive cycles and deriving an optimal control strategy for specific acceleration event categories using dynamic programming (DP). This optimal control strategy is then applied to all other acceleration events in its category, as well as separate standard and custom drive cycles using a look-up table. Fuel economy improvements of 2% average for acceleration events and 3.9% for an independent drive cycle were observed when compared to our rigorously validated 2010 Toyota Prius model. Our conclusion is that optimal control can be implemented in real-time using standard vehicle controllers assuming extremely limited information about future vehicle operation is known such as an approximate starting and ending velocity for an acceleration event.

Real-time optimization of net power in a fuel cell system

2009 ◽  
Vol 187 (2) ◽  
pp. 422-430 ◽  
Author(s):  
Judith O’Rourke ◽  
Murat Arcak ◽  
Manikandan Ramani
Keyword(s):  
Fuel Cell ◽  
Real Time ◽  
Cell System ◽  
Fuel Cell System ◽  
Time Optimization ◽  
Real Time Optimization
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