Research On Modeling Of Vehicle Proton Exchange Membrane Fuel Cell And Control Of Intake System

Affected by the energy crisis and environmental pollution,the development and utilization of clean energy has become an important issue that must be faced at present.Compared to traditional energy,fuel cells have the advantages of high energy conversion efficiency,no pollution and low noise.Among them,proton exchange membrane fuel cells are highly valued by researchers in the field of new energy vehicles due to its low operating temperature and short startup time.At present,the most common model of proton exchange membrane fuel cells is the electrochemical steady state model based on polarization curves,but in the actual reaction process,the temperature,flow,pressure and other parameters of the fuel cell are dynamically changed.Therefore,the establishment of a dynamic model of a proton exchange membrane fuel cell system is of great significance for exploring its reaction process and the design of its controller.Proton exchange membrane fuel cell system is composed of multiple coupled subsystems,the entire system has complex nonlinear characteristics coordinating the work of various subsystems and designing corresponding control algorithms are the key measures to improve system efficiency.Based on the above issues,this paper carried out the following research work on the vehicle proton exchange membrane fuel cell modeling and the research of the air intake system:(1)Starting from the electrochemical reaction mechanism of fuel cells,consider the transfer process of gas and liquid water inside the fuel cell,combining mechanism model and experimental model.Propose reasonable simplification of the system for the dynamic response characteristics and complex parameter characteristics of the model.Establish dynamic simulation model for proton exchange membrane fuel cell based on MATLAB/Simulink software.The mechanism models include output voltage model,cathode flow field model,anode flow field model and membrane hydration model;The subsystem model consists of an air supply system,a hydrogen supply system,and a thermal management system.Aiming at the effect of pressure gradient on the water transfer rate in the proton membrane,the hydrogen flow rate was directly feedback controlled by the pressure to balance the pressure on both sides of the proton membrane.(2)Considering the effects of pressure,temperature and parameter changes on the performance of the proton exchange membrane fuel cell,the dynamic response characteristics of the model under the load current step change were verified by simulation.Aiming at the thermal management system,considering the influence of the operating temperature of the reactor on the system power and proton membrane,the research on the control strategy of the thermal management system was carried out.The bypass valve in the system is controlled by a switch.,the control target is the optimal operating temperature of the stack and the difference between temperature at the inlet and outlet of the stack.The thermal management control strategy proposed in the simulation platform is verified,and the results show that the controller can effectively adjust the stack temperature and the inlet and outlet temperature difference.(3)The phenomenon of "oxygen starvation" and "oxygen saturation" in the air intake system is analyzed,and the effect of the oxygen excess ratio on the system efficiency is verified through simulation.The corresponding relationship between the load current and the optimal oxygen excess ratio is derived according to the definition of oxygen excess ratio.In order to optimize the working efficiency of the system,linearize the model at a steady-state operating point for a non-linear air supply system,determine the state variables of the system,and establish the system state space equation.Feedforward with feedback control and linear quadratic optimal control are used to control the voltage of the air compressor drive motor with the optimal oxygen excess ratio as the control target.The simulation analysis verified that both algorithms can adjust the work of the air compressor in time when the load current varies widely,ensuring the best working efficiency of the system and achieving satisfactory control accuracy.