Abstract
In this work, fractional order PIλDµ (FOPID) controller designed to enhance the dynamic performance of the Proton Exchange Membrane (PEM) fuel cell. The control objective is to regulate the supply manifold pressure on cathode side to maintain oxygen excess ratio of the PEM fuel cell. The higher order PEM fuel cell model is approximated to First order plus time delay (FOPTD) model for controller design and analysis. The proposed FOPID controller is designed based on minimization of Integral Absolute Error (IAE) with pre specified maximum sensitivity (Ms) as a constraint. Uncertainty and measurement noise analysis is carried out to verify the robustness of the designed controller. The simulation results of proposed FOPID controller is compared with other designing methods. Based on minimization of IAE value, the SP 1.4 FOPID controller produces IAE value of 0.255 where as AMIGO 1.4 tuning method and ZN based FOPID tuning methods produces 0.263 and 3.817 respectively for perfect case. Based on maximum sensitivity Ms is 1.4, the SP 1.4 FOPID controller produces Ms of 1.4 where as AMIGO 1.4 PID and ZN based FOPID tuning methods produces Ms of 1.5 and 1.25 respectively for perfect case, which indicates that the proposed SP 1.4 FOPID controller is robust. The proposed SP 1.4 FOPID provides better values (rise time of 0.331 sec, settling time of 0.692 sec and percentage of peak overshoot of 0.797 for perfect case) when compared with other methods. From simulation results, for the control of supply manifold pressure of PEM fuel cell, the proposed fractional-order PID controllers improves the closed loop performance in terms of rise time, settling time and percentage of peak overshoot when compared to the integer-order PID controllers.
Appendix
A Model parameters and constants
Simulation Parameters of PEMFC system.
Parameter | Symbol | SI Units | Value |
---|---|---|---|
Atmospheric pressure | Pa | 101,325 | |
Saturation pressure | Pa | 3140.4 | |
Average ambient air relative humidity | – | 0.5 | |
Atmospheric temperature | K | 298. 15 | |
Air-specific heat ratio | – | 1. 4 | |
Stack temperature | K | 353. 15 | |
Specific heat of air | J/kg/K | 1004 | |
Universal gas constant | J/mol/K | 8. 31451 | |
Molar mass of oxygen | kg/mol | ||
Molar mass of nitrogen | kg/mol | ||
Molar mass of vapor | kg/mol | ||
Molar mass of air | kg/mol | ||
Faraday’s constant | C/mol | 96,485 | |
Cathode volume | m3 | 0.01 | |
Supply manifold volume | m3 | 0. 02 | |
Compressor motor mechanical efficiency | % | 0.8 | |
Compressor efficiency | % | 0.98 | |
Compressor and motor inertia | N.m | ||
Compressor motor resistance | ohm | 0. 82 | |
Motor constant | Nm/A | 0. 0153 | |
Motor constant | V/(rad/sec) | 0. 0153 | |
Cathode inlet orifice constant | kg/sec/Pa | ||
Cathode outlet throttle discharge co efficient | — | 0.0124 | |
Cathode outlet throttle area | m2 | 0.002 | |
Number of cells in fuel cell stack | — | 381 | |
Oxygen mole fraction | — | 0.21 |
Constants of the PEMFC system model.
References
[1] Larminie J, Dicks AL, McDonald MS. Fuel cell systems explained. 2nd ed. Chichester, UK: J. Wiley, 2013.10.1002/9781118878330.ch11Search in Google Scholar
[2] Tong S, Qian D, Huo C. Hydrogen-air PEM fuel cell. Integration, modeling, and control. Berlin, Boston: De Gruyter, 2018.10.1515/9783110602159Search in Google Scholar
[3] Kunusch C, Puelston PF, Mayosky MA. Sliding-mode control of PEM fuel cells. London: Springer, 2012.10.1007/978-1-4471-2431-3Search in Google Scholar
[4] Guilbert D, N’Diaye A, Luberda P, Djerdir A. Fuel cell lifespan optimization by developing a power switch fault‐tolerant control in a floating interleaved boost converter. Fuel Cells. 2017;17:196–209.10.1002/fuce.201600058Search in Google Scholar
[5] Pukrushpan JT, Stefanopoulou AG, Peng H. Control of fuel cell power systems: principles, modeling, analysis and feedback design. 1st ed. London: Springer-Verlag, 2004.10.1007/978-1-4471-3792-4Search in Google Scholar
[6] Pukrushpan JT, Stefanopoulou AG, Peng H. Control of fuel cell breathing. IEEE Control Syst. 2004;24:30–46.10.1109/MCS.2004.1275430Search in Google Scholar
[7] Niknezhadi A, Allu_Fantova M, Kunusch C, Ocampo-Martinez C. Design and implementation of LQR/LQG strategies for oxygen stoichiometry control in PEM fuel cells based systems. J Power Sour. 2011;196:4277–82.10.1016/j.jpowsour.2010.11.059Search in Google Scholar
[8] Kunusch C, Puleston P, Mayosky M, Riera J. Sliding mode strategy for PEM fuel cells stacks breathing control using a super-twisting algorithm. IEEE Trans Control Syst Technol. 2009;17:167–74.10.1109/TCST.2008.922504Search in Google Scholar
[9] Baroud Z, Benmiloud M, Benalia A. Sliding mode controller for breathing sub system on a PEM fuel cell system. 3rd International Conference on Control and Engineering Information Technology (CEIT), 2015:1–6.10.1109/CEIT.2015.7233094Search in Google Scholar
[10] Matraji I, Laghrouche S, Jemei S, Wack M. Robust control of the PEM fuel cell air-feed system via sub-optimal second order sliding mode. Appl Energy. 2013;104:945–57.10.1016/j.apenergy.2012.12.012Search in Google Scholar
[11] Garcia-Gabin W, Dorado F, Bordons C. Real-time implementation of a sliding mode controller for air supply on a PEM fuel cell. J Process Control. 2010;20:325–36.10.1016/j.jprocont.2009.11.006Search in Google Scholar
[12] Sankar K, Thakre N, Singh SM, Jana AK. Sliding mode observer based nonlinear control of a PEMFC integrated with a methanol reformer. Energy. 2017;139:1126–43.10.1016/j.energy.2017.08.028Search in Google Scholar
[13] Pilloni A, Pisano A, Usai E. Observer based air excess ratio control of a PEM fuel cell system via high order sliding mode. IEEE Trans Ind Electron. 2015;62:5236–46.10.1109/TIE.2015.2412520Search in Google Scholar
[14] Gruber JK, Doll M, Bordons C. Design and experimental validation of a constrained MPC for the air feed of a fuel cell. Control Eng Pract. 2009;17:875–85.10.1016/j.conengprac.2009.02.006Search in Google Scholar
[15] Gruber JK, Bordons C, Oliva A. Nonlinear MPC for the airflow in a PEM fuel cell using a volterra series model. Control Eng Pract. 2012;20:205–17.10.1016/j.conengprac.2011.10.014Search in Google Scholar
[16] Damour C, Benne M, Kadjo JJA, Deseure J, Grondin-Perez B. On-line PEMFC control using parameterized nonlinear model-based predictive control. Fuel Cells. 2014;14:886–93.10.1002/fuce.201400080Search in Google Scholar
[17] Ha¨Hnel C, Aul V, Horn J. Power control of efficient operation of a PEM fuel cell system by nonlinear model predictive control. IFAC-Pap On Line. 2015;48:174–9.10.1016/j.ifacol.2015.09.179Search in Google Scholar
[18] Baroud Z, Benmiloud M, Benalia A, Ocampo-Martinez C. Novel hybrid fuzzy-PID control scheme for air supply in PEM fuel-cell-based systems. Int J Hydrogen Energy. 2017;42:10435–47.10.1016/j.ijhydene.2017.01.014Search in Google Scholar
[19] Li CH, Sun ZH, Wang YL, Wu XD. Unifying Electrical Engineering and Electronics Engineering, Lecture Notes in Electrical Engineering, Vol. 238. Xing S, Chen S, Wei Z, Xia J editors. New York: Springer, 2014: 933–42.10.1007/978-1-4614-4981-2_101Search in Google Scholar
[20] Aliasghary M. Control of PEM fuel cell systems using interval type‐2 fuzzy PID approach. Fuel Cells. 2018;18:449–56.10.1002/fuce.201700157Search in Google Scholar
[21] Ou K, Wang Y, Li Z, Shen Y, Xuan D. Feedforward fuzzy-PID control for air flow regulation of PEM fuel cell system. J Hydrogen Energy. 2015;40:11686–95.10.1016/j.ijhydene.2015.04.080Search in Google Scholar
[22] Benchouia NE, Derghal A, Mahmah B, Madi B, Khochemane L, Aoul EH. An adaptive fuzzy logic controller (AFLC) for PEMFC fuel cell. Int J Hydrogen Energy. 2015;40:13806–19.10.1016/j.ijhydene.2015.05.189Search in Google Scholar
[23] Abbaspour A, Khalilnejad A, Chen Z. Robust adaptive neural network control for PEM fuel cell. Int J Hydrogen Energy. 2016;41:20385–95.10.1016/j.ijhydene.2016.09.075Search in Google Scholar
[24] Methekar RN, Prasad V, Gudi RD. Dynamic analysis and linear control strategies for proton exchange membrane fuel cell using a distributed parameter model. J Power Sources. 2007;165:152–70.10.1016/j.jpowsour.2006.11.047Search in Google Scholar
[25] Liu Z, Chen J, Chen H, Yan C. Air supply regulation for PEMFC systems based on uncertainty and disturbance estimation. Int J Hydrogen Energy. 2018;43:11559–67.10.1016/j.ijhydene.2018.01.189Search in Google Scholar
[26] Divi S, Sonawane SH, Das S. Uncertainty analysis of transfer function of proton exchange membrane fuel cell and design of PI/PID controller for supply manifold pressure control. Indian Chem Eng. 2018. DOI: 10.1080/00194506.2018.1510794.Search in Google Scholar
[27] Das S. Functional fractional calculus, 2nd ed. Berlin Heidelberg: Springer-Verlag, 201110.1007/978-3-642-20545-3Search in Google Scholar
[28] Podlubny I. Fractional-order systems and PIλDμ controllers. IEEE Trans Autom Control. 1999;44:208–14.10.1109/9.739144Search in Google Scholar
[29] Vinagre BM, Podlubny I, Dorcak L, Feliu V On fractional PID controllers: a frequency domain approach. Proceedings of IFAC Workshop on Digital Control: Past, Present and Future of PID Control 2000, Terrasa, Spain, 53–8.10.1016/S1474-6670(17)38220-4Search in Google Scholar
[30] Valerio D, Costa JS. Tuning of fractional PID controllers with Ziegler–nichols type rules. Signal Process. 2006;86:2771–84.10.1016/j.sigpro.2006.02.020Search in Google Scholar
[31] Shahiri M, Ranjbar A, Karami MR, Ghaderi R. Oxygen excess ratio control of PEM fuel cell system based on a fractional order model approximation. Int J Mechatron, Electr Comput Technol. 2014;4:1524–50.Search in Google Scholar
[32] Shahiri M, Ranjbar A, Karami MR, Ghaderi R. Robust control of nonlinear PEMFC against uncertainty using fractional complex order control. Nonlinear Dyn. 2015;80(4):1785–1800. DOI: 10.1007/s11071-014-1718-1Search in Google Scholar
[33] Shahiri M, Ranjbar A, Karami MR, Ghaderi R. Tuning method for fractional complex order controller using standardized K-chart: application to PEM fuel cell. Asian J Control. 2016;18:1102–18.10.1002/asjc.1189Search in Google Scholar
[34] Lü X, Miao X, Xue Y, Deng L, Wang M, Gu DX, et al. Dynamic modeling and fractional order PIλDμ control of PEM fuel cell. Int J Electrochem Sci. 2017;12:7518–36.10.20964/2017.08.12Search in Google Scholar
[35] Bankupalli PT, Ghosh S, Kumar L, Samanta S. Fractional order modeling and two loop control of PEM fuel cell for voltage regulation considering both source and load perturbations. Int J Hydrogen Energy. 2018;43:6294–309.10.1016/j.ijhydene.2018.01.167Search in Google Scholar
[36] Taleb MA, Godoy E, Bethoux O, Irofti D PEM fuel cell fractional order modeling and identification. Prepr. 19th IFAC world congr, 2014:2125–31.10.3182/20140824-6-ZA-1003.01627Search in Google Scholar
[37] Taleb MA, Bethoux O, Godoy E. Identification of a PEMFC fractional order model. Int J Hydrogen Energy. 2016;42:1499–509.10.1016/j.ijhydene.2016.07.056Search in Google Scholar
[38] Suh KW Modeling, analysis and control of fuel cell hybrid power systems. Ph.D. dissertation, Dept. Mech. Eng., Univ. Michigan, Ann Arbor, 2006.Search in Google Scholar
[39] Padula F, Visioli A. Tuning rules for optimal PID and fractional order PID controllers. J. Process Control. 2011;21:69–81.10.1016/j.jprocont.2010.10.006Search in Google Scholar
[40] Astrom KJ, Huagglund T. Revisiting the Ziegler-Nichols step response method for PID control. J Process Control. 2004;14:635–50.10.1016/j.jprocont.2004.01.002Search in Google Scholar
[41] Gruber J, Bordons C, Dorado F Nonlinear control of the air feed of a fuel cell. American Control Conference, 2008:1121–6.10.1109/ACC.2008.4586643Search in Google Scholar
[42] Sundaresan KR, Krishnaswamy PR. Estimation of time delay time constant parameters in time, frequency, and laplace domains. Can J Chem Eng. 1978;56:257–62.10.1002/cjce.5450560215Search in Google Scholar
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Articles in the same Issue
- Research Articles
- A Simplified One-Dimensional Mathematical Model to Study the Transient Thermal Behavior of an Oxidation Catalyst with Both Low and High Levels of CO Concentration at the Inlet
- Control of Integrating Process with Time Delay
- Moisture Content and Oil Uptake Variations and Modeling in Deep-Fried Hamburger Slices
- Modelling of Thermodynamic Pressure – Composition – Temperature Relationships in the Systems of Metallic Hydride Forming Materials with Gaseous Hydrogen Using C++ Software
- CFD Investigation of Al2O3 Nanoparticles Effect on Heat Transfer Enhancement of Newtonian and Non-Newtonian Fluids in a Helical Coil
- Computational Fluid Dynamics Studies of Gas-Solid Flows in a Horizontal Pipe, Subjected to an Adiabatic Wall, Using a Variable Gas Properties Eulerian Model
- Enhanced PID Controller for Non-Minimum Phase Second Order Plus Time Delay System
- Fractional Order PID Controller Design for Supply Manifold Pressure Control of Proton Exchange Membrane Fuel Cell
Articles in the same Issue
- Research Articles
- A Simplified One-Dimensional Mathematical Model to Study the Transient Thermal Behavior of an Oxidation Catalyst with Both Low and High Levels of CO Concentration at the Inlet
- Control of Integrating Process with Time Delay
- Moisture Content and Oil Uptake Variations and Modeling in Deep-Fried Hamburger Slices
- Modelling of Thermodynamic Pressure – Composition – Temperature Relationships in the Systems of Metallic Hydride Forming Materials with Gaseous Hydrogen Using C++ Software
- CFD Investigation of Al2O3 Nanoparticles Effect on Heat Transfer Enhancement of Newtonian and Non-Newtonian Fluids in a Helical Coil
- Computational Fluid Dynamics Studies of Gas-Solid Flows in a Horizontal Pipe, Subjected to an Adiabatic Wall, Using a Variable Gas Properties Eulerian Model
- Enhanced PID Controller for Non-Minimum Phase Second Order Plus Time Delay System
- Fractional Order PID Controller Design for Supply Manifold Pressure Control of Proton Exchange Membrane Fuel Cell