Air supply regulation for PEMFC systems based on uncertainty and disturbance estimation

Liu, Zhiyang; Chen, Jian; Chen, Hao; Yan, Chizhou

doi:10.1016/j.ijhydene.2018.01.189

Cited by 44 publications

(25 citation statements)

References 23 publications

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“…A common way of controlling the fuel cell system is by setting reference values for the cathode/anode pressure, hydrogen/oxygen stoichiometries, voltage, etc. as seen in [4,9,10].…”

Section: Introductionmentioning

confidence: 83%

Safe and Efficient Polymer Electrolyte Membrane Fuel Cell Control Using Successive Linearization Based Model Predictive Control Validated on Real Vehicle Data

2020

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In this paper, a polymer electrolyte membrane fuel cell (PEMFC) stack control study is presented. The goal is to track the transient power demand of a real fuel cell (FC) vehicle while ensuring safe and efficient operation. Due to the dynamically changing power demand, fast transients occur in the internal states of the fuel cell (e.g., pressure, humidity, reactant mass) leading to degradation effects (e.g., high/low membrane overpressure, reactants starvation) which are avoided by imposing safety constraints. Efficiency is considered in terms of internal voltage losses minimization as well as minimization of the power of the compressor used to pressurize the cathode. For solving the optimization problem of power demand tracking, adhering to safety constraints, and maximizing efficiency, model predictive control (MPC) has been chosen. Due to the nonlinearity of the FC system, a successive linearization based MPC (SLMPC) is used to control the FC throughout its operating region. Simulation results show that the power demand can be fulfilled while at the same time ensuring safe operation in terms of adhering to constraints and that the minimization of internal voltage losses and compressor power lead to an approximate 9.5% less hydrogen consumption than in the actual reference vehicle.

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“…A common way of controlling the fuel cell system is by setting reference values for the cathode/anode pressure, hydrogen/oxygen stoichiometries, voltage, etc. as seen in [4,9,10].…”

Section: Introductionmentioning

confidence: 83%

Safe and Efficient Polymer Electrolyte Membrane Fuel Cell Control Using Successive Linearization Based Model Predictive Control Validated on Real Vehicle Data

2020

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“…To deal with unknown nonlinearities, an adaptive backstepping control approach was proposed for uncertain nonlinear PEMFC systems where neural networks were employed to estimate completely unknown nonlinearities [21]. Recently, an estimation-based robust control approach was presented for PEMFC systems with unknown nonlinearities [22]. However, the previous control results [16]- [22] for nonlinear air supply systems involve the following restrictions.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, an estimation-based robust control approach was presented for PEMFC systems with unknown nonlinearities [22]. However, the previous control results [16]- [22] for nonlinear air supply systems involve the following restrictions.…”

Section: Introductionmentioning

confidence: 99%

“…R1) In [16]- [22], the constraint problem of OER to avoid oxygen starvation and parasitic loss was not considered for the OER control design of nonlinear air supply systems of PEMFCs. To the best of our knowledge, the oxygen starvation and parasitic loss prevention problem for OER control of uncertain nonlinear air supply systems is still unresolved.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive Control of Proton Exchange Membrane Fuel Cell Air Supply Systems With Asymmetric Oxygen Excess Ratio Constraints

2020

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This paper investigates the oxygen starvation and parasitic loss prevention problem of the adaptive oxygen excess ratio (OER) control system of nonlinear proton exchange membrane fuel cells (PEMFCs). Asymmetric OER constraints are considered to avoid oxygen starvation and parasitic loss in the air supply system of PEMFCs. An approximation-based adaptive control strategy is established to ensure robust regulation of the OER while not violating the OER constraints, regardless of unknown system parameters, nonlinearities, and the abrupt changes of the load current. A dynamic surface design technique using an asymmetric barrier Lyapunov function is employed for a recursive control design. Compared with existing control approaches for uncertain nonlinear air supply systems of PEMFCs, this paper first considers the oxygen starvation and parasitic loss prevention problem for the regulation of optimal OER in the control field of nonlinear PEMFCs. Using the Lyapunov stability theorem, the boundedness of all closed-loop signals and the convergence of the output tracking error to the vicinity of zero are proved. INDEX TERMSAdaptive control, oxygen excess ratio (OER) constraints, neural networks, proton exchange membrane fuel cells (PEMFCs).

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“…Fuzzy logic control techniques like hybrid fuzzy PID controller 6 and interval type 2 fuzzy PID 7 have been proposed to regulate the air supply pressure. Ratio control, cascade control, and adaptive neural network techniques have been implemented to prevent this oxygen starvation 8–10 …”

Section: Introductionmentioning

confidence: 99%

Robust analytical proportional‐integral‐derivative tuning rules for regulation of air pressure in supply manifold of proton exchange membrane fuel cell

Begum

Ganesan

2020

Asia-Pacific J Chem Eng

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The core aim of this manuscript is to recommend analytical tuning rules to regulate and control the air supply pressure moving from the supply manifold (SM) to the electrode (cathode) of proton exchange membrane fuel cell (PEMFC). This is done to have an optimal oxygen excess ratio in the fuel cell for enhanced energy generation. The higher order dynamics of PEMFC is approximated to be non‐integer first‐order stable plus time delay model. A simple proportional ‐integral/proportional‐integral‐derivative (PI/PID) control scheme is designed for a specific maximum sensitivity (Ms) using analytical tuning rules. This, in turn, enhances its dynamic performance by regulating the SM pressure. The proposed integer order PI/PID control technique is compared with the other fractional order IMC‐PI control techniques that are recently published. The simulation results obtained prove that the proposed tuning rules provide a good response compared with fractional order controllers and thereby maintaining the SM pressure. The robustness of the novel controller is analyzed by introducing perturbations and noise to the dynamic model. The tuning rules proposed are applicable for two maximum sensitivity values of 1.4 and 2 as a measure of robustness. To measure system performance, few time domain metrics and integral absolute error (IAE), integral square error (ISE), and TV metrics are used. For both the Ms values, the proposed techniques provide stable and improved responses.

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Air supply regulation for PEMFC systems based on uncertainty and disturbance estimation

Cited by 44 publications

References 23 publications

Safe and Efficient Polymer Electrolyte Membrane Fuel Cell Control Using Successive Linearization Based Model Predictive Control Validated on Real Vehicle Data

Safe and Efficient Polymer Electrolyte Membrane Fuel Cell Control Using Successive Linearization Based Model Predictive Control Validated on Real Vehicle Data

Adaptive Control of Proton Exchange Membrane Fuel Cell Air Supply Systems With Asymmetric Oxygen Excess Ratio Constraints

Robust analytical proportional‐integral‐derivative tuning rules for regulation of air pressure in supply manifold of proton exchange membrane fuel cell

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