SUMMARY This paper investigates the effects of relative humidity (RH) and stoichiometry of reactants on the water saturation and local transport process in proton exchange membrane fuel cells. A two‐dimensional model was developed, taking into account the effect of the formation of liquid water on the reactant transport. The results indicate that the reactant RH and stoichiometry significantly affect cell performance. At a constant anode RH = 100%, a lower cathode RH maintains membrane hydration to give better cell performance. At a constant cathode RH = 100%, a lower anode RH not only provides more hydrogen to the catalyst layer to participate in the electrochemical reaction but also increases the difference in the water concentrations between the anode and cathode. This enhances the back‐diffusion of water from the cathode to the anode, reducing possible flooding for better cell performance. Higher anodic stoichiometry results in the reduction of cathodic water saturation by increasing water back‐diffusion, thereby enhancing fuel cell performance. Higher cathodic stoichiometry also reduces water saturation by drying more liquid water to increase cathode local current density. Copyright © 2011 John Wiley & Sons, Ltd.
This paper investigates an active front steering control strategy based on quantitative feedback theory (QFT). By incorporating feedback from a yaw rate sensor into the active steering system, the control system improves the dynamic response of the vehicle. The steering response of a vehicle generally depends upon uncertain quantities like mass, velocity, and road conditions. Thus, QFT is used to design a controller with robust performance. A multi-degree-of-freedom nonlinear model is co-simulated here by MATLAB Simulink and ADAMS/CAR. The performance of the control system is evaluated under various emergency maneuvers and road conditions. The result shows that the designed robust control system has good control performance and can efficiently improve handing qualities and stability characteristics.
A multiple harmonic balance method is presented in this paper for obtaining the aperiodic steady-state solution of a piecewise-linear system. As the method utilizes general and systematic computational procedures, it can be applied to analyze the multi-tone or combination-tone responses for the higher dimensional nonlinear systems such as rotors. Moreover, it is capable of informing the stability of the obtained solution using Floquet theory. To demonstrate the systematic approach of the new method, the almost periodic forced vibration of an articulated loading platform (ALP) with a piecewise-linear stiffness is computed as an example.
This study examines the development of micro in situ sensors and analyzed the through‐plane temperature of a fuel cell. Temperature sensing inside a fuel cell is important in fuel cell diagnosis and analysis. Temperature sensors must be adequately small, so that fuel cell performance is maintained and the temperature anywhere inside the cell can be flexibly measured. In this study, a temperature sensor based on a micro‐electromechanical system (MEMS) is designed and fabricated to achieve these objectives. The micro temperature sensor was installed inside a cell to measure through‐plane temperature. The current and voltage of the fuel cell with the micro temperature sensor were measured and compared with those of a fuel cell without the sensor to analyze the effect of the sensor on fuel cell performance. The developed temperature sensor is of resistance temperature detector (RTD) type, with a flexible substrate of polyimide, high sensitivity, and easy installation characteristics. After calibration of the sensors, three sensors were inserted into the cell to measure the through‐plane temperature, and the polarization curve of the cell with and without the micro sensor was compared. Finally, a 3D computational fluid dynamics (CFD) model of a fuel cell was developed and analyzed by comparison of the measured temperature results to determine the accuracy of the model.
An overall simulation model for fuel cell hybrid vehicle (FCHV) power train in parallel configuration using MATLAB/Simulink programming is constructed in this study. The model runs on power control strategy by using logic-threshold approach, achieved by the hybrid control unit (HCU) and fuel cell stack number. Using accelerator and decelerator pedal positions deduced from the driving schedule as the primary input, the simulation implements power flow and distribution under different vehicle operating modes. The HCU control strategy also incorporates regenerative braking and recharge for battery capacity recovery. Using the D-optimality method for experiment points selection and sequential quadratic programming (SQP) algorithm for obtaining the optimal operational parameters, three control threshold variables of HCU and optimal stack cell number are selected for hydrogen fuel economy under certain driving cycles. The proposed method provides optimized configurations of the FCHV model and the fuel cell stack, which has the capability in satisfying drive power request while satisfying vehicle driving schedule and battery state of charge (SOC) recovery with lower fuel consumption.
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