Control strategy of cooling system for the optimization of parasitic power of automotive fuel cell system

2015 ◽  
Vol 40 (39) ◽  
pp. 13549-13557 ◽  
Author(s):  
Jaeyoung Han ◽  
Jisoo Park ◽  
Sangseok Yu
Author(s):  
Loïc Boulon ◽  
Marie-Cécile Péra ◽  
Philippe Delarue ◽  
Alain Bouscayrol ◽  
Daniel Hissel

This paper presents a model of a whole polymer electrolyte fuel cell system including the stack, an air compressor, a cooling system, and a power converter. This model allows its integration in a complete hybrid electric vehicle simulation. The level of detail of the model is chosen to enable control rules design, ancillaries sizing, and study of the interaction between the components of the vehicle. This model is formalized with energetic macroscopic representation, thus organized in a unified multidomain graphical description. Experimental results are compared to simulations for validation of the model accuracy.


Author(s):  
Janghwan Hwang ◽  
Sangseok Yu

Abstract Efficient hydrogen flow control is of great importance to ensure the reliable operation of an automotive fuel cell system because it is closely associated with the safety and the economic efficiency. In this study, an effective hydrogen flow control algorithm for hydrogen excess ratio control is addressed by pointing out the recovery speed and overshoot response. Unlike previous studies on the hydrogen management systems of an automotive fuel cell, this study presents an analytic hydrogen tank model which can present the characteristics of the discharge and charge of hydrogen from a type 4 hydrogen tank. To this end, a mode reference adaptive control (MRAC) based on proportional-integral (PI) control is introduced, to ensure robust hydrogen flow during the dynamic operation of fuel cell system. The MRAC was compared with the nominal PI control and PWM control in the hydrogen management system of an automotive fuel cell operating within normal conditions, under steady-state responses and transient. Based on these result, it can further demonstrate that the MRAC algorithm shows better recovery speed and tracking performance than the nominal PI, and PWM control algorithm with respect to the transient behaviors.


2022 ◽  
Author(s):  
Waheed B. Bello ◽  
Satya R T Peddada ◽  
Anurag Bhattacharyya ◽  
Mark Jennings ◽  
Sunil Katragadda ◽  
...  

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