TY - JOUR
T1 - Dynamic temperature model for proton exchange membrane fuel cell using online variations in load current and ambient temperature
AU - Khan, Saad S.
AU - Shareef, Hussain
AU - Mutlag, Ammar Hussein
N1 - Funding Information:
This research was supported by United Arab Emirates University (UAEU) fund code 31R067.
Publisher Copyright:
© 2019, © 2019 Taylor & Francis Group, LLC.
PY - 2019/4/9
Y1 - 2019/4/9
N2 - This paper presents a dynamic temperature model for a proton exchange membrane fuel cell (PEMFC) system. The proposed model overcomes the complexity of conventional models using first-order expressions consisting of load current and ambient temperature. The proposed model also incorporates a PEMFC cooling system, which depends upon the temperature difference between events. A dynamic algorithm is developed to detect load changing events and calculate instantaneous PEMFC temperature variations. The parameters of the model are extracted by employing the lightning search algorithm (LSA). The temperature characteristics of the NEXA 1.2 kW PEMFC system are experimentally studied to validate model performance. The results show that the proposed model output and the temperature data obtained from experiments for linear and abrupt changes in PEMFC load current are in agreement. The root-mean-square error between the model output and experimental results is less than 0.9. Moreover, the proposed model outperforms the conventional models and provides advantages such as simplicity and adaptability for low and high sampling data rates of input variables, namely, load current and ambient temperature. The model is not only helpful for simulations but also suitable for dynamic real-time controllers and emulators.
AB - This paper presents a dynamic temperature model for a proton exchange membrane fuel cell (PEMFC) system. The proposed model overcomes the complexity of conventional models using first-order expressions consisting of load current and ambient temperature. The proposed model also incorporates a PEMFC cooling system, which depends upon the temperature difference between events. A dynamic algorithm is developed to detect load changing events and calculate instantaneous PEMFC temperature variations. The parameters of the model are extracted by employing the lightning search algorithm (LSA). The temperature characteristics of the NEXA 1.2 kW PEMFC system are experimentally studied to validate model performance. The results show that the proposed model output and the temperature data obtained from experiments for linear and abrupt changes in PEMFC load current are in agreement. The root-mean-square error between the model output and experimental results is less than 0.9. Moreover, the proposed model outperforms the conventional models and provides advantages such as simplicity and adaptability for low and high sampling data rates of input variables, namely, load current and ambient temperature. The model is not only helpful for simulations but also suitable for dynamic real-time controllers and emulators.
KW - Proton exchange membrane fuel cell
KW - algorithm
KW - lightening search algorithm
KW - root mean square error
KW - temperature modeling
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U2 - 10.1080/15435075.2018.1564141
DO - 10.1080/15435075.2018.1564141
M3 - Article
AN - SCOPUS:85060653793
SN - 1543-5075
VL - 16
SP - 361
EP - 370
JO - International Journal of Green Energy
JF - International Journal of Green Energy
IS - 5
ER -