Performance Optimization Method for Proton Exchange Membrane Fuel Cell Power Generation System Based on Dual-Closed-Loop Active Disturbance Rejection Control

The purpose of this research is to apply proton membrane fuel cells to toys, and assess its feasibility. The study uses Taguchi Methods to analyze the "Proton Exchange Membrane Fuel Cell Power Supply and Work Module for Toys". The study assembled the proton exchange membrane fuel cell power supply module in the "Toy of Hydrogen-based Energy Module-Ship of Hydrogen-based Energy" and observes its operation state. It finds that the ship moved forward smoothly, and indicates that hydrogen can be used for this toy. This study uses renewable "Solar Energy" matching "the Proton Exchange Membrane" to design the "Hydrogen and Oxygen Fuel Module", which creates the hydrogen and oxygen fuel supply for the "Proton Exchange Membrane Fuel Cell Power Supply and Work Module" for toys using hydrogen-based energy. "Hydrogen-based Energy" will become applied extensive to the toy field in the future by way of this study.

An H2 Polymer Electrolyte Membrane (PEM) Fuel Cell power generation system composed of three subsystems: fuel reforming, fuel cell stack, and post combustion is examined. The system is simulated and optimized with a fuel cell model integrated within the process flow sheet. A case study optimization of the entire power generation system is presented and the influence of heat integration on the optimization is demonstrated. Our objectives are to maximize the energy and system efficiencies as well as the system profit. Here, optimization formulations with heat integration are used to realize our objectives, which explore the synergy between optimization and heat integration. Our results showed that we can achieve an energy efficiency as high as 58.30% and a system efficiency as high as 28.35%. For comparison, we provide results obtained from sequential process optimization followed by heat integration. The gain from the synergy is mostly exemplified in the profit maximization study, where the profit increases by almost 27.15% in the best case. Finally, we obtain optimization results that include feed vaporization of water to steam as a comparison for the heat integration. These results demonstrate the importance of simultaneous optimal heat integration for fuel cell‐based processes. © 2006 American Institute of Chemical Engineers AIChE J, 2006

Design of a methanol reformer for on-board production of hydrogen as fuel for a 3 kW High-Temperature Proton Exchange Membrane Fuel Cell power system

The performance of proton exchange membrane fuel cells is very sensitive to temperature. The electrochemical reaction results directly in temperature variations in the proton exchange membrane fuel cell. Ensuring effective temperature control is crucial to ensure fuel cell reliability and durability. This paper uses active disturbance rejection control in the thermal management system to maintain the operating temperature and the stack inlet and outlet temperature difference at the set value. First, key cooling system modules such as expansion tanks, coolant circulation pumps and radiators based on Simulink were built. Then, physical modeling and simulation of the fuel cell cooling system was carried out. In order to ensure the effectiveness of the control strategy and reduce the parameter tuning workload, an active disturbance rejection control parameter optimization method using an elite genetic algorithm was proposed. When the optimized control strategy responds to input disturbances, the maximum overshoot of the system is only 1.23% and can reach stability again in 30 s, so the fuel cell temperature can be controlled effectively. Simulation results show that the optimized control strategy can effectively control the stack temperature and coolant temperature difference under the influence of stepped charging current without interference or with interference, and has strong robustness and anti-interference capability.

Aiming at the problem that the suspension force under disturbance of the permanent magnet slice rotor is difficult to be accurately detected, a new displacement controller based on the active disturbance rejection control is proposed. Firstly, the mathematic models of torque and suspension forces of the bearingless permanent magnet slice motor (BPMSM) are deduced. Secondly, the active disturbance rejection (ADR) controller is constructed. Thirdly, the BPMSM direct control system based on the ADR controller is built and the simulation is carried out, the correctness of the mathematic model and the control algorithm are verified. Finally, the displacement controller is used for a 4 kW prototype. Compared with the traditional PI controller, the floating stability time and the disturbed recovery time of the slice rotor are both decreased, the vibration displacement of rotor in stable state is reduced by 44%.

This paper presents a comparision between two controllers for Proton Exchange Membrane Fuel Cell PEMFC power system. The aim of this work is to keep the PEMFC working at its MPP by acting on the DC/DC converter, and ensure an adequate robustness against load and inputs variations. Conventional controller PI and backstepping technique are applied to the DC/DC boost converter. The stability of the backstepping is demonstrated by means of Lyapunov analysis. The model and the controllers are implemented in the MATLAB and SIMULINK environment. Simulation results indicate that the aim of this work is achieved using the backstepping algorithm.

Experimental campaign and assessment of a complete 240-kW Proton Exchange Membrane Fuel Cell power system for maritime applications

Tracking control of the oxygen excess ratio (OER) and keeping the cathode air pressure relatively stable are essential for the operation of polymer electrolyte membrane fuel cell (PEMFC). In automotive fuel cell air supply systems, the cathode air pressure and OER are usually unmeasurable parameters, which makes the air supply system control and fault analysis very difficult. To solve this problem, this paper proposes an extended state observer based on the hyperbolic tangent function (HTF-ESO) to estimate the cathode air pressure of the fuel cell gas supply system, and indirectly obtains the OER according to the estimated cathode pressure, and designs the sliding mode control (SMC) and a first-order active disturbance rejection control (ADRC) for the tracking control of the OER. The simulation results show that the improved HTF-ESO effectively mitigates the initial differential peak phenomenon and reduces the initial estimation error of the cathode air pressure, and the RMSE of the cathode pressure and supply manifold pressure observation errors are reduced by 68% and 20%, respectively, compared with the present unimproved ESO. Compared with the PI, the RSME of the control error after convergence of the designed SMC and ADRC is reduced by 4.3%, and the OER can be restored to the reference value within 1 second, with good dynamic response.

Integrated electro-mechanical actuators (EMAs) are widely used in cooperative robots. Their control system has to be carefully designed to achieve a desirable performance. The proportional-integral (PI) control and the active disturbance rejection control (ADRC) are the two commonly used controllers. Compared with the PI, the ADRC shows better performance in terms of disturbance rejection, response speed and overshooting suppression. However, the ADRC utilises numerous parameters and the optimisation of these parameters is a challenge. In this study, the influence of the parameters of β 01 , β 02 , β 03 , β 1 , β 2 on the ADRC performance is deeply analysed. Considering the two non-linear factors of permanent magnet synchronous motor and harmonic transmission in the EMA, a simulation model of the EMA was established. An improved swarm optimisation algorithm was employed to optimise the parameters of the ADRC. A second-order ADRC in speed and position modes was designed. The parameters of the ADRC in these modes were adjusted using improved particle swarm optimisation. ADRC was applied to the EMA field-oriented control system instead of cascade PI, and the simulation and experimental results were compared using the cascade PI control method. When the target speed is to 15 rpm, the speed fluctuation range of the ADRC is about ±0.3 rpm, which is smaller than that of the PI controller’s ±0.5 rpm. Compared with the cascade PI control, ADRC affords a faster response speed, greater robustness and stronger disturbance resistance in the steady-state operation process.

Challenges and opportunities in modelling of proton exchange membrane fuel cells (PEMFC)

Nowadays, Dynamic Positioning (DP) is applied to various tasks such as subsea pipeline laying and the requirements for the positioning performance in marine operations are higher and higher. The main objective of this paper is to design a DP controller based on the Active Disturbance Rejection Control (ADRC) to solve the problems of long response time, large overshoot and low positioning accuracy in ship positioning. Firstly, the mathematical models of the ship and environmental disturbances are established. Secondly, the basic principle of ADRC is described. Meanwhile, stability analysis of the control system is introduced. Thirdly, ADRC is improved by the fal function filter and phase prediction method which solve the problem of dither and phase delay in tracking differentiators. Finally, simulations are carried out to verify the performance of the designed ADRC and the improved ADRC. Several simulation results show that the designed ADRC can realize the fixed-point control of the ship, which effectively solves the problems of long response time, overshoot and positioning accuracy, and compared with the traditional ADRC, the improved ADRC can reduce the error of straight track control, which indicates that ADRC can meet the requirements for the positioning performance and has a strong application value.

The piezoelectric smart structures, which can be labeled as the cream of the crop of smart structures without overstatement, are strongly impacted by a large number of uncertainties and disturbances during operation. The present paper reviews active disturbance rejection control (ADRC) technologies developed for application in piezoelectric smart structures, focusing on measurement, analysis, estimation, and attenuation of uncertainties/disturbances in systems. It first explained vast categories of uncertainties/disturbances with their adverse influences. Then, after a brief introduction to the application of basic ADRC in smart structures, a thorough review of recently modified forms of ADRC is analyzed and classified in terms of their improvement objectives and structural characteristics. The universal advantages of ADRC in dealing with uncertainties and its improvement on the particularity of smart structures show its broad application prospects. These improved ADRC methods are reviewed by classifying them as modified ADRC for specific problems, modified ADRC by nonlinear functions, composite control based on ADRC, and ADRC based on other models. In addition, the application of other types of active anti-disturbances technologies in smart structures is reviewed to expand horizons. The main features of this review paper are summarized as follows: (1) it can provide profound understanding and flexible approaches for researchers and practitioners in designing ADRC in the field and (2) light up future directions and unsolved problems.

Linear active disturbance rejection control (ADRC) is known for its simplicity and its performance in disturbance attenuation. Currently, tuning of linear ADRC is via the bandwidth idea proposed in [1]. It is first shown that there are some limitations using only two bandwidths to tune the linear ADRC controllers. In this paper, tuning of linear ADRC with extra model dynamic information is investigated. It is shown that the available model dynamic information used in generalized ADRC (GADRC) can be realized by the observer gain and the controller gain of the conventional linear ADRC, thus extends the applicability of conventional linear ADRC. Simulation results show that with extra model dynamic information incorporated, by tuning the observer gain and controller gain, the performance of a conventional linear ADRC can indeed be improved, especially for non-minimum phase and time-delayed processes.

Feedback-linearization decoupling based coordinated control of air supply and thermal management for vehicular fuel cell system

For high‐order systems, strong nonlinearities, parameter uncertainties and external disturbances pose significant control challenges. Several improved active disturbance rejection controller (ADRC) methods are proposed, including input modified ADRC (MADRC), time‐delay ADRC (DADRC) and Smith‐like ADRC (SLADRC). These improved ADRC methods are systematically compared with conventional proportional integral (PI) control and regular ADRC, focusing on key performance metrics such as tracking accuracy and disturbance rejection capability. The effectiveness of the proposed improved ADRC methods is validated via numerical simulations of a typical superheated steam temperature (SST) system. The integral absolute error (IAE) of ADRC, MADRC, DADRC and SLADRC shows a reduction of around 30, 50, 33 and 35, respectively, relative to that of PI. The outcomes of numerical simulations demonstrate that improved ADRC methods achieve satisfactory control performance, whereas MADRC stands out with the best overall performance. Thus, field application data show that compared with PI, MADRC exhibits significant reductions in key deviation metrics, with the maximum positive deviation decreasing by 33, the maximum negative deviation decreasing by 8, the average positive deviation decreasing by 25, the average negative deviation decreasing by 11 and the variance deviation decreasing by 18.