scholarly journals Temperature Control for a Proton-Exchange Membrane Fuel Cell System with Unknown Dynamic Compensations

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Yashan Xing ◽  
Ramon Costa-Castelló ◽  
Jing Na

Numerous control strategies of temperature regulation have been carried out for proton-exchange membrane fuel cell systems including a cooling fan in order to ensure operation at the desired condition and extend the lifetime of the fuel cell stack. However, most existing control strategies are developed without considering the efficiency limitation of the cooling system such that the cooling fan may be unable to eliminate the additional heat. Moreover, there are unknown modelling errors, external disturbance and noise during modelling and experiment processes for fuel cells. Due to those unknown dynamics, the conventional control strategies may fail to achieve the expectant results. To address this issue, an alternative control strategy is proposed in this paper, which consists of a composite proportional-integral (PI) controller with an unknown system dynamics estimator. First, the control strategy is developed by reducing the temperature of input air through the humidifier and simultaneously increasing the mass flow of air in order to eliminate the excess heat that a cooling fan cannot remove. Moreover, an unknown system dynamics estimator is proposed in order to compensate the effect of the unknown dynamics. The construction of the estimator is designed through finding an invariant manifold which implies the relation between known variables and the unknown manifold. The invariant manifold is derived by applying a simple low-pass filter to the system which is beneficial to avoid the requirement of the unmeasurable state derivative. Furthermore, the proposed estimator is easily merged into the proposed PI control strategy and ensures the exponential convergence of estimated errors. Besides, the estimator is further modified such that the derivative of the desired temperature is not required in the controller. Finally, numerical simulations of the PEMFC system are provided and the results illustrate the efficacy of the proposed control strategy.

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1140
Author(s):  
Xiao Tang ◽  
Chunsheng Wang ◽  
Yukun Hu ◽  
Zijian Liu ◽  
Feiliang Li

An effective oxygen excess ratio control strategy for a proton exchange membrane fuel cell (PEMFC) can avoid oxygen starvation and optimize system performance. In this paper, a fuzzy PID control strategy based on granular function (GFPID) was proposed. Meanwhile, a proton exchange membrane fuel cell dynamic model was established on the MATLAB/Simulink platform, including the stack model system and the auxiliary system. In order to avoid oxygen starvation due to the transient variation of load current and optimize the parasitic power of the auxiliary system and the stack voltage, the purpose of optimizing the overall operating condition of the system was finally achieved. Adaptive fuzzy PID (AFPID) control has the technical bottleneck limitation of fuzzy rules explosion. GFPID eliminates fuzzification and defuzzification to solve this phenomenon. The number of fuzzy rules does not affect the precision of GFPID control, which is only related to the fuzzy granular points in the fitted granular response function. The granular function replaces the conventional fuzzy controller to realize the online adjustment of PID parameters. Compared with the conventional PID and AFPID control, the feasibility and superiority of the algorithm based on particle function are verified.


2001 ◽  
Author(s):  
Daisie D. Boettner ◽  
Gino Paganelli ◽  
Yann G. Guezennec ◽  
Giorgio Rizzoni ◽  
Michael J. Moran

Abstract This paper describes use of a Proton Exchange Membrane (PEM) fuel cell system model for automotive applications in a fuel cell system/battery hybrid configuration. The fuel cell system model has been integrated into a vehicle performance simulator that determines fuel economy and allows consideration of control strategies. The simulator is used to explore relevant regions of the fuel cell-powered hybrid electric vehicle design space by conducting simulations using two simple supervisory-control strategies: thermostatic control and proportional control. During the simulations power provided by the battery and fuel cell system and operational limits on battery state of charge and fuel cell system current density are varied while maintaining minimum component sizing to meet vehicle performance criteria. Analysis of results from these simulations provides component power sizing and limits of operation suitable for development of a more advanced supervisory vehicle control strategy for a fuel cell vehicle.


2017 ◽  
Vol 359 ◽  
pp. 119-133 ◽  
Author(s):  
Etienne Dijoux ◽  
Nadia Yousfi Steiner ◽  
Michel Benne ◽  
Marie-Cécile Péra ◽  
Brigitte Grondin Pérez

Sign in / Sign up

Export Citation Format

Share Document