Abstract

Control of output voltage is critical for the power quality of solid oxide fuel cells (SOFCs), which is, however, challenging due to electrochemical nonlinearity, load disturbances, modelling uncertainties, and actuator constraints. Moreover, the fuel utilization rate should be limited within a safety range during the voltage regulation transient. The current research is usually appealing to model predictive control (MPC) by formulating the difficulties into a constrained optimization problem, but its huge computational complexity makes it formidable for real-time implementation in practice. To this end, this paper aims to develop a combined control structure, with basic function blocks, to fulfill the objectives with minor computation. Firstly, the disturbance, nonlinearity and uncertainties are lumped as a total disturbance, which is estimated and mitigated by active disturbance rejection controller (ADRC). Secondly, a feed-forward controller is introduced to improve the load disturbance rejection response. Finally, the constraints are satisfied by designing a cautious switching strategy. The simulation results show that the nominal performance of the proposed strategy is comparable to MPC. In the presence of parameter perturbation, the proposed strategy shows a better performance than MPC.

Highlights

  • Fuel cell electricity generation is considered to be the core of the future hydrogen industry [1]

  • A significant advantage of the solid oxide fuel cells (SOFCs) power plant is that its power can be adjusted conveniently, which is favorable for maintaining the stability of a microgrid

  • In light of the fuel utilization rate constraint, we propose a logical judgment block to complement the ability of active disturbance rejection control (ADRC)

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Summary

Introduction

Fuel cell electricity generation is considered to be the core of the future hydrogen industry [1]. Based on the benchmark model proposed in [3], it was revealed in [4,5] that the proportional-integral (PI) controller and even the H∞ optimal control are not able to give a satisfactory performance without exceeding the safety range of the fuel utilization. To this end, the mainstream research resorts to Model Predictive Control (MPC), which is suitable for constrained optimization.

Problem Formulation
Control Difficulties
An Offset-Free MPC Solution
Fundamentals of ADRC
Parameter Tuning and Verification
The Comprehensive Control Strategy
Comparative Simulation
Simulation Results of MPC
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