Temperature Control for Proton Exchange Membrane Fuel Cell based on Current Constraint with Consideration of Limited Cooling Capacity

Chen, F.; Yu, Yang; Gao, Yuan

doi:10.1002/fuce.201700001

Cited by 29 publications

(11 citation statements)

References 32 publications

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“…Ref. [97] designed an MPC controller that minimizes the temperature deviation from the reference while constraining the radiator fan control and current load. As demonstrated in simulations, the MPC limited the current load when the thermal management system reached its maximal cooling capacity, guaranteeing the lifetime and performance of the fuel cell.…”

Section: Temperature Controlmentioning

confidence: 99%

Challenges and developments of automotive fuel cell hybrid power system and control

Gao

et al. 2019

Sci. China Inf. Sci.

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Fuel cells are emerging as promising power sources and have attracted increasing attention from industries and academics worldwide. In particular, automotive manufacturers are replacing internal combustion engines in vehicles with fuel cell systems, which are advantaged by zero emissions, high efficiency, and various clean routes that generate pure hydrogen. However, current fuel cell systems are costly, and their corresponding infrastructures are not fully qualified to meet current market demand. This paper reviews the challenges and developments of automotive fuel cell hybrid power systems and their controls. It briefly summarizes the model, control, and optimization issue associated with the research and application of fuel cells in hybrid power systems. After presenting the basic knowledge and discussing the trending size and structure of fuel cells for automotive usage, the review describes models of automotive fuel cell systems, focusing on the electrochemical reaction dynamics and the key parameters influencing their efficiency and lifetime. The control problems associated with automotive fuel cell systems as well as the optimization issue associated with hybrid energy systems (comprising fuel cells, batteries, and ultra-capacitors) are elaborately analyzed. The review concludes with current problems and challenges faced by the energy control systems of fuel cell vehicles.

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Section: Temperature Controlmentioning

confidence: 99%

Challenges and developments of automotive fuel cell hybrid power system and control

Gao

et al. 2019

Sci. China Inf. Sci.

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“…has a unique maximum efficiency point (MEP) and other local peaks on the plateau around the MEP position, and all peaks varies with operating conditions , , . The Fuel_LF‐RTO strategy proposed herein can accurately locate the MEP, but also local peaks if this is imposed and the starting point is set appropriately in the searching range .…”

Section: Fuel_lf‐rto Strategymentioning

confidence: 99%

“…Regarding the DC voltage regulation, this can be performed as correction of the reference current on the control side of the PEMFC system, the battery, or the power storage device (UC). The DC voltage regulation was studied at both FC control and UC control sides in different papers . The DC voltage regulation was implemented here on the control side of the UC stack because the optimization loop was implemented on the control side of the PEMFC stack and the battery is connected directly to DC bus.…”

Section: Fuel_lf‐rto Strategymentioning

confidence: 99%

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

et al. 2018

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The Fuel_LF‐RTO strategy is real‐time optimization (RTO) strategy proposed here to find the optimal values of fueling for the polymer electrolyte membrane fuel cell hybrid power sources under unknown load profile, which is the case of fuel cell vehicle. The proposed optimization strategy is based on global extremum seeking (GES) algorithm and load‐following (LF) control for air and fuel flows. The results show the performance obtained with Fuel_LF‐RTO strategy in comparison with the Static Feed‐Forward strategy. The performance was estimated for constant and variable load. The FC system efficiency and the fuel consumption efficiency for maximum load of 8 kW can increase with up to 1.88% and 11.26 W lpm−1 in comparison with the sFF RTO strategy. Also, the fuel economy is 27.36 L during the 8 kW/12 s constant load cycle, which means an economy of 136.8 lpm. This performance is highlighted for constant load in range 2 to 8 kW, which represents 0.33% and 1.25% from nominal power of the 6 kW FC stack used in this study. Also, the performance was estimate for variable load considering the fuel economy, which can be up to 21.86 l during the 6.25 kW/12 s pulsed load cycle.

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“…Mathematical modelling is popularly used as a reasonable cost and an effective solution to experimental studies. Nonetheless, its efficacy is typically influenced by an inappropriate configuration of the parameters, such as stack temperature, the humidity of anode and cathode, gas pressure, and so on [10]. Recently, the most effective techniques are developing mathematical models [11] based on analytical models [12], empirical models [13] or semi-empirical models [14], and mechanistic models, and then the approximation of unidentified voltage-current (V-I) and power-voltage (P-I) curves through optimization techniques [15].…”

Section: Introductionmentioning

confidence: 99%

Fuel Cell Characteristic Curve Approximation Using the Bézier Curve Technique

2020

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Accurate modelling of the fuel cell characteristics curve is essential for the simulation analysis, control management, performance evaluation, and fault detection of fuel cell power systems. However, the big challenge in fuel cell modelling is the multi-variable complexity of the characteristic curves. In this paper, we propose the implementation of a computer graphic technique called Bézier curve to approximate the characteristics curves of the fuel cell. Four different case studies are examined as follows: Ballard Systems, Horizon H-12 W stack, NedStackPS6, and 250 W proton exchange membrane fuel cells (PEMFC). The main objective is to minimize the absolute errors between experimental and calculated data by using the control points of the Bernstein–Bézier function and de Casteljau’s algorithm. The application of this technique entails subdividing the fuel cell curve to some segments, where each segment is approximated by a Bézier curve so that the approximation error is minimized. Further, the performance and accuracy of the proposed techniques are compared with recent results obtained by different metaheuristic algorithms and analytical methods. The comparison is carried out in terms of various statistical error indicators, such as Individual Absolute Error (IAE), Relative Error (RE), Root Mean Square Error (RMSE), Mean Bias Errors (MBE), and Autocorrelation Function (ACF). The results obtained by the Bézier curve technique show an excellent agreement with experimental data and are more accurate than those obtained by other comparative techniques.

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Temperature Control for Proton Exchange Membrane Fuel Cell based on Current Constraint with Consideration of Limited Cooling Capacity

Cited by 29 publications

References 32 publications

Challenges and developments of automotive fuel cell hybrid power system and control

Challenges and developments of automotive fuel cell hybrid power system and control

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

Fuel Cell Characteristic Curve Approximation Using the Bézier Curve Technique

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