Dynamic Model of a Load-Following Fuel Cell Vehicle: Impact of the Air System

2002 ◽  
Author(s):  
M. Badami ◽  
C. Caldera
Keyword(s):  
Fuel Cell ◽  
Dynamic Model ◽  
Fuel Cell Vehicle ◽  
Load Following ◽  
Vehicle Impact ◽  
Air System

Control-Oriented Modeling and Analysis of Air Management System for Fuel Reforming Fuel Cell Vehicle

2008 ◽  
Vol 5 (1) ◽  
Author(s):  
Nicolas Romani ◽  
Emmanuel Godoy ◽  
Dominique Beauvois ◽  
Vincent Le Lay
Keyword(s):  
Fuel Cell ◽  
Differential Equations ◽  
Management System ◽  
Controller Design ◽  
System Optimization ◽  
Fuel Cell Vehicle ◽  
Develop Model ◽  
Design System ◽  
Fuel Reforming ◽  
Air System

With the purpose of meeting the specifically restrictive requirements of fuel reforming fuel cell vehicle, this paper brings into focus the issues of the transient operation of fuel cell systems and presents a control-oriented dynamic model of fuel cell air management system, suited for multivariable controller design, system optimization, and supervisory control strategy. In a first step, the dual analytical approach based on lumped and distributed parameter models is detailed: The partial differential equations deduced from mass/energy conservation laws and inertial dynamics are reduced to ordinary differential equations using spatial discretization and then combined with semiempirical actuator models to form the overall air system model. In a second step, a classical approach is followed to obtain a local linearization of the model. A validation of both nonlinear and linearized versions is performed by computational fluid dynamics simulations and experiments on a dedicated air system test bench. Thanks to dynamic analysis (pole/zero map), operating point impact and model order reduction are investigated. Finally, the multiinput multioutput state-space model—which balances model fidelity with model simplicity—can be coupled with reformer, stack, and thermal models to understand the system complexity and to develop model-based control methodologies.

Analysis of Effects of Fuel Cell System Dynamics on Optimal Energy Management

2017 ◽  
Author(s):  
Kai Wu ◽  
Ming Kuang ◽  
Milos Milacic ◽  
Xiaowu Zhang ◽  
Jing Sun
Keyword(s):  
Fuel Cell ◽  
Energy Management ◽  
Fuel Economy ◽  
Cell System ◽  
Fuel Cell Vehicle ◽  
Fuel Cell System ◽  
Optimal Energy ◽  
Load Following ◽  
Optimal Energy Management ◽  
Level 1

Dynamic characteristics of a proton exchange membrane fuel cell (PEMFC) system can impact fuel economy and load following performance of a fuel cell vehicle, especially if those dynamics are ignored in designing top-level energy management strategy. To quantify the effects of fuel cell system (FCS) dynamics on optimal energy management, dynamic programming (DP) is adopted in this study to derive optimal power split strategies at two levels: Level 1, where the FCS dynamics are ignored, and Level 2, where the FCS dynamics are incorporated. Analysis is performed to quantify the differences of these two resulting strategies to understand the effects of FCS dynamics. While Level 1 DP provides significant computational advantages, the resulting strategy leads to load following errors that need to be mitigated using battery or FCS itself. Our analysis shows that up to 5% fuel economy penalty on New York city cycle (NYCC) and 3% on supplemental federal test procedure (US06) can be resulted by ignoring FCS dynamics, when the dominant dynamics of the FCS has settling time as slow as 8 seconds.

scholarly journals A Simple and Safe Strategy for Improving the Fuel Economy of a Fuel Cell Vehicle

Mathematics ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 604
Author(s):  
Nicu Bizon ◽  
Phatiphat Thounthong
Keyword(s):  
Fuel Cell ◽  
Real Time ◽  
Fuel Consumption ◽  
Fuel Economy ◽  
Utilization Efficiency ◽  
Fuel Cell Vehicle ◽  
Total Power ◽  
Load Range ◽  
Feed Forward ◽  
Load Following

A new real-time strategy is proposed in this article to optimize the hydrogen utilization of a fuel cell vehicle, by switching the control references of fueling regulators, based on load-following. The advantages of this strategy are discussed and compared, with advanced strategies that also use the aforementioned load-following mode regulator of fueling controllers, but in the entire loading range, respectively, with a benchmark strategy utilizing the static feed-forward control of fueling controllers. Additionally, the advantages of energy-storage function in a charge-sustained mode, such as a longer service life and reduced size due to the implementation of the proposed switching strategy, are presented for the dynamic profiles across the entire load range. The optimization function was designed to improve the fuel economy by adding to the total power of the fuel utilization efficiency (in a weighted way). The proposed optimization loop will seek the reference value to control the fueling regulator in real-time, which is not regulated by a load-following approach. The best switching threshold between the high and low loading scales were obtained using a sensitivity analysis carried out for both fixed and dynamic loads. The results obtained were promising—(1) the fuel economy was two-times higher than the advanced strategies mentioned above; and (2) the total fuel consumption was 13% lower than the static feed-forward strategy. This study opens new research directions for fuel cell vehicles, such as for obtaining the best fuel economy or estimating fuel consumption up to the first refueling station on the planned road.

Evaluation of Electric Load Following Capability on Fuel Cell System Fueled by High-Purity Hydrogen

2011 ◽  
Vol 131 (12) ◽  
pp. 927-935
Author(s):  
Yusuke Doi ◽  
Deaheum Park ◽  
Masayoshi Ishida ◽  
Akitoshi Fujisawa ◽  
Shinichi Miura
Keyword(s):  
Fuel Cell ◽  
High Purity ◽  
Cell System ◽  
Electric Load ◽  
Fuel Cell System ◽  
Load Following ◽  
High Purity Hydrogen

Load Following Function of Fuel Cell Plant in Distributed Environment

2005 ◽  
Vol 1 (03) ◽  
pp. 285-290 ◽  
Author(s):  
F. González-Longatt ◽  
◽  
A. Hernandez ◽  
F. Guillen ◽  
C. Fortoul
Keyword(s):  
Fuel Cell ◽  
Distributed Environment ◽  
Load Following
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