Adaptive control for robust air flow management in an automotive fuel cell system

Han, Jae‐Young; Yu, Sangseok; Yi, Sun

doi:10.1016/j.apenergy.2016.12.115

Cited by 86 publications

(24 citation statements)

References 40 publications

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“…The velocity and turbulent kinetic energy fields obtained from the previous analysis, strengthen the hypothesis that negative pressure promotes even air flow across the stack. 42 As evidenced by Figure 9, the velocity, and thus the coolant mass flow rate, was nearly constant across all cooling channels within the stack. Furthermore, the presence of a streamline in each cooling channel demonstrates the existence of an even flow field across all cells in the stack.…”

Section: Baseline Simulationmentioning

confidence: 79%

“…41 A holistic approach to modelling facilitates optimisation of the cooling subsystem, which can help prolong the life of the FC system and improve performance. 42,43 The numerical approach is used to model a mixture of physical phenomena and their variation across the FC. Simulation domains generally range in size from a channel to an entire stack.…”

Section: Introductionmentioning

confidence: 99%

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Thermal characteristics of an air‐cooled open‐cathode proton exchange membrane fuel cell stack via numerical investigation

et al. 2020

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In light of stricter emissions regulations and depleting fossil fuel reserves, fuel cell vehicles (FCVs) are one of the leading alternatives for powering future vehicles. An open-cathode, air-cooled proton exchange membrane fuel cell (PEMFC) stack provides a relatively simple electric generation system for a vehicle in terms of system complexity and number of components. The temperature within a PEMFC stack is critical to its level of performance and the electrochemical efficiency. Previously created computational models to study and predict the stack temperature have been limited in their scale and the inaccurate assumption that temperature is uniform throughout. The present work details the creation of a numerical model to study the temperature distribution of an 80-cell Ballard 1020ACS stack by simulating the cooling airflow across the stack. Using computational fluid dynamics, a steady-state airflow simulation was performed using experimental data to form boundary conditions where possible. Additionally, a parametric study was performed to investigate the effect of the distance between the stack and cooling fan on stack performance. Model validation was performed against published results. The temperature distribution across the stack was identical for the central 70% of the cells, with eccentric temperatures observed at the stack extremities, while the difference between coolant and bipolar plate temperatures was approximately 10 C at the cooling channel outlets. The results of the parametric study showed that the fan-stack distance has a negligible effect on stack performance. The assumptions regarding stack temperature uniformity and measurement were challenged. Lastly, the hypothesis regarding the negligible effect of fan-stack distance on stack performance was confirmed.

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Section: Baseline Simulationmentioning

confidence: 79%

Section: Introductionmentioning

confidence: 99%

Thermal characteristics of an air‐cooled open‐cathode proton exchange membrane fuel cell stack via numerical investigation

et al. 2020

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“…For the PEMFC air feeding system, several control techniques have been investigated in the literature such as feedforward control [4][5][6][7], LQR/LQG control [8], feedforward plus PI feedback control [6], sliding mode control (SMC) [9], adaptive sliding mode observer based control [10], adaptive control [11], model predictive control (MPC) [12], time delay control (TDC) with static feedforward [13] and disturbance-observer-based control [2]. Recently, soft computing techniques gained a lot of interest for the control of the PEMFC air feeding system.…”

Section: Introductionmentioning

confidence: 99%

Fractional Order Fuzzy PID Control of Automotive PEM Fuel Cell Air Feed System Using Neural Network Optimization Algorithm

AbouOmar

Zhang

2019

Energies

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The air feeding system is one of the most important systems in the proton exchange membrane fuel cell (PEMFC) stack, which has a great impact on the stack performance. The main control objective is to design an optimal controller for the air feeding system to regulate oxygen excess at the required level to prevent oxygen starvation and obtain the maximum net power output from the PEMFC stack at different disturbance conditions. This paper proposes a fractional order fuzzy PID controller as an efficient controller for the PEMFC air feed system. The proposed controller was then employed to achieve maximum power point tracking for the PEMFC stack. The proposed controller was optimized using the neural network algorithm (NNA), which is a new metaheuristic optimization algorithm inspired by the structure and operations of the artificial neural networks (ANNs). This paper is the first application of the fractional order fuzzy PID controller to the PEMFC air feed system. The NNA algorithm was also applied for the first time for the optimization of the controllers tested in this paper. Simulation results showed the effectiveness of the proposed controller by improving the transient response providing a better set point tracking and disturbance rejection with better time domain performance indices. Sensitivity analyses were carried-out to test the robustness of the proposed controller under different uncertainty conditions. Simulation results showed that the proposed controller had good robustness against parameter uncertainty in the system.

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“…Han et al. established a two critical internal states model to study the surge phenomenon and designed the MRAC controller accordingly. In order to realize the control of a 150 KW fuel cell engine, Liu et al established a single state quantity air supply system model, and designed a feedback control strategy based on PI control theory.…”

Section: Introductionmentioning

confidence: 99%

Control‐oriented LPV Modeling for the Air Supply System of Proton Exchange Membrane Fuel Cells

Chen

Jiao

Liu³

et al. 2018

Fuel Cells

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Air supply system, as a crucial subsystem of proton exchange membrane fuel cells (PEMFC), plays a very significant role in the efficiency and the reliability of the system. In order to better control the air supply subsystem, an appropriate model needs to be established to describe the subsystem covering whole working conditions from PEMFC startup to shutdown. This paper propose a linearized parameter varying (LPV) model based on system identification. To describe the subsystem in different working conditions, the subsystem is identified near 7 equilibrium points. Identification results show that the subsystem can be described as several linear models near equilibrium points. Based on these linear models, a LPV model is proposed solving 2‐D interpolation problem. It is proved theoretically that LPV system has the same steady‐state character and linear model at equilibrium points with identification models. The simulation and experiments results also verify that the LPV model can cover the working conditions from PEMFC startup to shutdown with accuracy both in dynamic condition and steady state.

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Adaptive control for robust air flow management in an automotive fuel cell system

Cited by 86 publications

References 40 publications

Thermal characteristics of an air‐cooled open‐cathode proton exchange membrane fuel cell stack via numerical investigation

Thermal characteristics of an air‐cooled open‐cathode proton exchange membrane fuel cell stack via numerical investigation

Fractional Order Fuzzy PID Control of Automotive PEM Fuel Cell Air Feed System Using Neural Network Optimization Algorithm

Control‐oriented LPV Modeling for the Air Supply System of Proton Exchange Membrane Fuel Cells

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