Skip to main content
SpringerLink
Log in

Decentralized event-triggered adaptive control for interconnected nonlinear dynamics of constrained air supply and thermal management systems of PEMFCs

  • Original paper
  • Published:
Nonlinear Dynamics Aims and scope Submit manuscript

Abstract

This paper investigates a decentralized event-triggered adaptive control problem for uncertain interconnected air supply and thermal management nonlinear dynamics of proton exchange membrane fuel cells (PEMFCs). In addition, the constraint problems of the oxygen excess ratio (OER) and stack temperature (ST) are addressed for preventing oxygen starvation, parasitic loss, membrane dehydration, and electrode flooding of PEMFCs. First, the practical nonlinear interaction problem between the air pressure of the air supply subsystem and the ST of the thermal management subsystem is formulated. Then, a decentralized adaptive control design strategy is established to guarantee the constraint satisfaction of each subsystem and the asynchronously event-triggered regulation of the OER and ST. In contrast to the previous studies on the control of PEMFCs, this study first addresses the nonlinear interaction problem of the air supply and thermal management systems and their decentralized control design in the control field of PEMFCs. Based on the Lyapunov stability theorem, the stability of the resulting overall control scheme is analyzed.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Pukrushpan, J.T., Stefanopoulou, A.G., Peng, H.: Control of Fuel Cell Power Systems: Principles, Modeling Analysis and Feedback Design. Springer, Berlin (2004)

    Book  MATH  Google Scholar 

  2. Pukrushpan, J.T., Stefanopoulou, A.G., Peng, H.: Control-oriented modeling and analysis for automotive fuel cell systems. J. Dyn. Syst. Meas. Cont. 126(1), 14–25 (2004)

    Article  Google Scholar 

  3. Ali, N., Miguel, A., Cristian, K., Carlos, O.: Design and implementation of LQR/LQG strategies for oxygen stoichiometry control in PEM fuel cells based systems. J. Power Sour. 196, 4277–4282 (2011)

    Article  Google Scholar 

  4. Talj, R., Romeo, O., Alessandro, A.: Passivity and robust PI control of the air supply system of a PEM fuel cell model. Automatica 47, 2554–2561 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  5. Liu, S., Bin, Y., Li, Y., Scheppat, B.: Decentralized model predictive control for polymer electrolyte membrane fuel cell system. IFAC-PaperOnline 51(31), 659–664 (2018)

    Article  Google Scholar 

  6. Han, J., Yu, S., Yi, S.: Oxygen excess ratio control for proton exchange membrane fuel cell using model reference adaptive control. Int. J. Hydrogen Energy 44, 18425–18437 (2019)

    Article  Google Scholar 

  7. Jing, S., Ilya, V.K.: Load governor for fuel cell oxygen starvation protection. IEEE Trans. Cont. Syst. Technol. 13(6), 911–920 (2005)

    Article  Google Scholar 

  8. Abdullah, M., Idres, M.: Constrained model predictive control of proton exchange membrane fuel cell. J. Mech. Sci. Technol. 28(9), 3855–3862 (2014)

    Article  Google Scholar 

  9. Salah, L., Imad, M., Fayez, S.A., Samir, J., Maxime, W.: Load governor based on constrained extremum seeking for PEM fuel cell oxygen starvation and compressor surge protection. Int. J. Hydrogen Energy 38, 14314–14322 (2013)

    Article  Google Scholar 

  10. Chen, J., Wang, Z.L.F., Su, H.: Optimal oxygen excess ratio control for PEM fuel cells. IEEE Trans. Cont. Syst. Technol. 26(5), 1711–1721 (2018)

    Article  Google Scholar 

  11. Talj, R., Hissel, D., Ortega, R., Becherif, M., Hilairet, M.: Experimental validation of a PEM fuel-cell reduced-order model and a moto compressor higher order sliding-mode control. IEEE Trans. Ind. Elect. 57(6), 1906–1913 (2010)

    Article  Google Scholar 

  12. Li, P., Chen, J., Cai, T., Zhang, B.: Adaptive control of air delivery system for PEM fuel cell using backstepping. In: Proceedings of the 8th AAsian Control Conference, pp. 1282–1287 (2011)

  13. Alessandro, P., Alessandro, P., Elio, U.: Observer-based air excess ratio control of a PEM fuel cell system via high-order sliding mode. IEEE Trans. Ind. Elect. 62(8), 5236–5246 (2015)

    Article  Google Scholar 

  14. Sankar, K., Amiya, K.J.: Dynamics and estimator-based nonlinear control of a PEM fuel cell. IEEE Trans. Cont. Syst. Technol. 26(3), 1124–1131 (2018)

    Article  Google Scholar 

  15. Liu, Z., Chen, J., Chen, H., Yan, C.: Air supply regulation for PEMFC systems based on uncertainty and disturbance estimation. Int. J. Hydrogen Energy 43, 11559–11567 (2018)

    Article  Google Scholar 

  16. Liu, J., Gao, Y., Su, X., Wack, M., Wu, L.: Disturbance-observer-based control for air management of PEM fuel cell systems via sliding mode technique. IEEE Trans. Cont. Syst. Technol. 27(3), 1129–1138 (2019)

    Article  Google Scholar 

  17. Huiwen, D., Qi, L., Youlong, C., Yanan, Z., Weirong, C.: Nonlinear controller design based on cascade adaptive sliding mode control for PEM fuel cell air supply systems. Int. J. Hydrogen Energy 44, 19357–19369 (2019)

    Article  Google Scholar 

  18. Zhang, H.K., Wang, Y.F., Wang, D.H., Wang, Y.L.: Adaptive robust control of oxygen ratio for PEMFC system based on type-2 fuzzy logic system. Inform. Sci. 511, 1–7 (2020)

    Article  MathSciNet  Google Scholar 

  19. Kim, B.M., Choi, Y.H., Yoo, S.J.: Adaptive control of proton exchange membrane fuel cell air supply systems with asymmetric oxygen excess ratio constraints. IEEE Access 8, 5537–5549 (2020)

    Article  Google Scholar 

  20. Ahn, J.W., Choe, S.Y.: Coolant controls of a PEM fuel cell system. J. Power Sour. 179, 252–264 (2008)

    Article  Google Scholar 

  21. Zhao, X., Li, Y., Liu, Z., Li, Q., Chen, W.: Thermal management system modeling of a water-cooled proton exchange membrane fuel cell. Int. J. Hydrogen Energy 40, 3048–3056 (2015)

    Article  Google Scholar 

  22. Han, J., Park, J., Yu, S.: Control strategy of cooling system for the optimization of parasitic power of automotive fuel cell system. Int. J. Hydrogen Energy 40, 13549–13557 (2015)

    Article  Google Scholar 

  23. Han, J., Yu, S., Yi, S.: Advanced thermal management of automotive fuel cells using a model reference adaptive control algorithm. Int. J. Hydrogen Energy 42(7), 4328–4341 (2017)

    Article  Google Scholar 

  24. Rojas, J.D., Martinez, C.O., Kunusch, C.: Thermal modelling approach and model predictive control of a water-cooled PEM fuel cell system. In: Proceedings of the IECON 39th Annual Conference of the IEEE Industrial Electronics Society, pp. 3806–3811 (2013)

  25. Li, D., Li, C., Gao, Z., Jin, Q.: On active disturbance rejection in temperature regulation of the proton exchange membrane fuel cells. J. Power Sour. 283(1), 452–463 (2015)

    Article  Google Scholar 

  26. Yan, C., Chen, J., Liu, H., Lu, H.: Model-based fault tolerant control for the thermal management of PEMFC systems. IEEE Trans. Ind. Elect. 67(4), 2875–2884 (2020)

    Article  Google Scholar 

  27. Hu, P., Cao, G.Y., Zhu, X.J., Hu, M.: Coolant circuit modeling and temperature fuzzy control of proton exchange membrane fuel cells. Int. J. Hydrogen Energy 35(17), 9110–9123 (2010)

    Article  Google Scholar 

  28. Fang, C., Xu, L., Cheng, S., Li, J., Jiang, H., Ouyang, M.: Sliding-mode-based temperature regulation of a proton exchange membrane fuel cell test bench. Int. J. Hydrogen Energy 42(16), 11745–11757 (2017)

    Article  Google Scholar 

  29. Huand, L., Chen, Z., Liu, Z., Becherif, M.: Adaptive thermal control for PEMFC systems with guaranteed performance. Int. J. Hydrogen Energy 43(25), 11550–11558 (2018)

    Article  Google Scholar 

  30. Kim, B.M., Yoo, S.J.: Approximation-based adaptive control of constrained uncertain thermal management systems with nonlinear coolant circuit dynamics of PEMFCs. IEEE Access 8, 83483–83494 (2020)

    Article  Google Scholar 

  31. Zhang, J., Tang, Y., Song, C., Zhang, J., Wang, H.: PEM fuel cell open circuit voltage (OCV) in the temperature range of 23\(^\circ \)C to 120\(^\circ \)C. J. Power Sources 163, 532–537 (2006)

    Article  Google Scholar 

  32. Zhang, J., Tang, Y., Song, C., Xia, Z., Li, H., Wang, H., Zhang, J.: PEM fuel cell relative humidity (RH) and its effect on performance at high temperatures. Electrichimica Acta 53, 5315–5321 (2008)

    Article  Google Scholar 

  33. Polycarpou, M.M.: Stable adaptive neural control scheme for nonlinear systems. IEEE Trans. Autom. Cont. 41(3), 447–451 (1996)

    Article  MathSciNet  MATH  Google Scholar 

  34. Tee, K.P., Ge, S.S., Tay, E.H.: Barrier Lyapunov functions for the control of output-constrained nonlinear systems. Automatica 45(4), 918–927 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  35. He, W., Yin, Z., Sun, J.: Adaptive neural network control of a marine vessel with constraints using the asymmetric barrier Lyapunov function. IEEE Trans. Cyber. 47(7), 1641–1651 (2017)

    Article  Google Scholar 

  36. Daud, W.R.W., Rosli, R.E., Majlan, E.H., Hamid, S.A.A., Mohamed, R., Husaini, T.: PEM fuel cell system control: a review. Renewable Energy 113, 620–638 (2017)

    Article  Google Scholar 

  37. Kandlikar, S.G., Zijie, L.: Thermal management issues in a PEMFC stack: a brief review of current status. Appl. Thermal Eng. 29, 1276–1280 (2009)

    Article  Google Scholar 

  38. Wang, C., Hill, D.J., Ge, S.S., Chen, G.R.: An ISS-modular approach for adaptive neural control of pure-feedback systems. Automatica 42(5), 723–731 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  39. Kurdila, A.J., Narcowich, F.J., Ward, J.D.: Persistency of excitation in identification using radial basis function approximants. SIAM J. Cont. Optim. 33(2), 625–642 (1995)

    Article  MathSciNet  MATH  Google Scholar 

  40. Swaroop, D., Hedrick, J.K., Yip, P.P., Gerdes, J.C.: Dynamic surface control for a class of nonlinear systems. IEEE Trans. Autom. Cont. 45(10), 1893–1899 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  41. Jeffreys, H.: Methods of Mathematical Physics. Cambridge University Press, Cambridge (1988)

    MATH  Google Scholar 

  42. Khalil, H.K.: Nonlinear Systems. Prentice-Hall, Upper Saddle River (1996)

    Google Scholar 

  43. Ge, S.S., Tee, K.P.: Approximation-based control of nonlinear MIMO time-delay systems. Automatica 43, 31–43 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  44. Ioannou, P.A., Kokotovic, P.V.: Adaptive Systems with Reduced Models. Springer, Berlin (1983)

    Book  MATH  Google Scholar 

  45. Wu, L.-B., Park, J. H., Xie, X. P., Gao, C., Zhao, N. N.: Fuzzy adaptive event-triggered control for a class of uncertain nonaffine nonlinear systems with full state constraints. IEEE Trans. Fuzzy Systems, https://doi.org/10.1109/TFUZZ.2020.2966185,To be published

Download references

Acknowledgements

This research was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (NRF-2019R1A2C1004898).

Author information

Authors and Affiliations

  1. School of Electrical and Electronics Engineering, Chung-Ang University, 84 Heukseok-Ro, Dongjak-Gu, Seoul, 06974, Republic of Korea

    Byung Mo Kim & Sung Jin Yoo

Authors
  1. Byung Mo Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sung Jin Yoo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sung Jin Yoo.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kim, B.M., Yoo, S.J. Decentralized event-triggered adaptive control for interconnected nonlinear dynamics of constrained air supply and thermal management systems of PEMFCs. Nonlinear Dyn 103, 791–808 (2021). https://doi.org/10.1007/s11071-020-06124-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11071-020-06124-1

Keywords

Search

Navigation