Novel Model of Proton Exchange Membrane Fuel Cell with Predictive Control Using Hildreth Algorithm Based on Fractional-order Dynamic Model

Considering the multivariable and fractional-order characteristics of proton exchange membrane fuel cells(PEMFCs), a fractional-order subspace identification method(FOSIM) is proposed in this paper to establish a fractionalorder state space(FOSS) model, which can be expressed as a multivariable configuration with two inputs, hydrogenflow rate and stack current, and two outputs, cell voltage and power. Based on this model, a novel constrained optimal control law named the Hildreth model predictive control(H-MPC) strategy is created, which employs a Hildreth quadratic programming algorithm to adjust the output power of fuel cells through adaptively regulating hydrogen flow and stack current. dSPACE semi-physical simulation results demonstrate that, compared with proportional-integral-derivative and quadratic programming MPC(QP-MPC), the proposed H-MPC exhibits better tracking ability and strong robustness against variations of PEMFC power.