99/02080 Optimal fuel cell system design considering functional performance and production costs

1999 ◽  
Vol 40 (3) ◽  
pp. 213
Author(s):  
Deyi Xue ◽  
Zuomin Dong

Abstract In this work the optimization-based, integrated concurrent design method is extended to a general mechanical system — the transportation fuel cell system. A general optimal design model considering both functional performance and production costs is first introduced. Mathematical models of the functional performance and production costs of the Ballard fuel cell system are then discussed. A joint performance and cost optimization is carried out using the Ballard fuel cell system to demonstrate the approach. The optimization concurrently takes into account of two functional performance aspects and production costs to identify the optimal values of two key design variables. The work is a continuation of the authors’ earlier research on integrated concurrent engineering design.


Fuel Cells ◽  
2021 ◽  
Author(s):  
Alexander Fladung ◽  
Hannes Scholz ◽  
Oliver Berger ◽  
Richard Hanke‐Rauschenbach

2013 ◽  
Vol 479-480 ◽  
pp. 934-937
Author(s):  
Jium Ming Lin ◽  
Cheng Hung Lin

This paper proposes a novel fuel cell system design by integrating both methods of Ziegler-Nichols-based PID control and the intelligent fuzzy control, thus the relative stability and disturbance rejection properties can be reserved. This new method is not proposed before for fuel cell control system design. By using PID method for the normal case of fuel cell current requirement, the overshoot of the temperature is 45%, the temperature rise and the settling times are 0.65 sec and 2 sec, respectively. However, by using intelligent fuzzy Ziegler-Nichols-based PID controller design, the overshoot of the temperature is 12%, the temperature rise and the settling times are 0.7 sec and 1 sec, respectively. Thus the proposed method is better. Moreover, this paper also takes the system disturbance variation effect into consideration, e.g. the current requirement is increased by 100% for climbing a slope or speed-up conditions; note a large 60% temperature overshoot is produced by using Ziegler-Nichols based PID controller. But the overshoot is only 20% by using the intelligent fuzzy Ziegler-Nichols-based PID controller. Thus the proposed system is more robust.


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