TY - JOUR
T1 - Boosting the power density of two-chamber microbial fuel cell
T2 - Modeling and optimization
AU - Rezk, Hegazy
AU - Olabi, Abdul Ghani
AU - Abdelkareem, Mohammad Ali
AU - Sayed, Enas Taha
N1 - Publisher Copyright:
© 2022 John Wiley & Sons Ltd.
PY - 2022/12
Y1 - 2022/12
N2 - This paper estimates the optimal input parameters of a two-chamber microbial fuel cell (TCMFC) by employing Harris hawk's optimization (HHO) and ANFIS modeling. The goal is to boost the output power density of TCMFC. Three operating input controlling parameters are taken into consideration: acetate concentration in the influent of the anodic chamber, fuel feed flow rate in the anodic chamber, and oxygen concentration in the influent of the cathodic chamber. Based on measured data, an ANFIS model has been created to simulate the power density of TCMFC in terms of the input controlling parameters. The modeling results proved the superiority of ANFIS-based model, the coefficient of determination is increased from 0.703 using Response surface methodology (RSM) to 0.993 using ANFIS (boosted by 41.25%.). Next, HHO is applied to do the parameter identification process. To prove the advantage of the proposed methodology, the findings are compared to RSM and experimental data. The integration between HHO and ANFIS-based modeling boosted the output power density of TCMFC by 8.7% and 9.7% compared to measured data and RSM, respectively. In sum, the proposed strategy succeeded in boosting the power density of the TCMFC.
AB - This paper estimates the optimal input parameters of a two-chamber microbial fuel cell (TCMFC) by employing Harris hawk's optimization (HHO) and ANFIS modeling. The goal is to boost the output power density of TCMFC. Three operating input controlling parameters are taken into consideration: acetate concentration in the influent of the anodic chamber, fuel feed flow rate in the anodic chamber, and oxygen concentration in the influent of the cathodic chamber. Based on measured data, an ANFIS model has been created to simulate the power density of TCMFC in terms of the input controlling parameters. The modeling results proved the superiority of ANFIS-based model, the coefficient of determination is increased from 0.703 using Response surface methodology (RSM) to 0.993 using ANFIS (boosted by 41.25%.). Next, HHO is applied to do the parameter identification process. To prove the advantage of the proposed methodology, the findings are compared to RSM and experimental data. The integration between HHO and ANFIS-based modeling boosted the output power density of TCMFC by 8.7% and 9.7% compared to measured data and RSM, respectively. In sum, the proposed strategy succeeded in boosting the power density of the TCMFC.
KW - ANFIS
KW - Harris hawk's optimization
KW - microbial fuel cell
KW - parameter estimation
KW - renewable energy
UR - http://www.scopus.com/inward/record.url?scp=85136888444&partnerID=8YFLogxK
U2 - 10.1002/er.8589
DO - 10.1002/er.8589
M3 - Article
AN - SCOPUS:85136888444
SN - 0363-907X
VL - 46
SP - 20975
EP - 20984
JO - International Journal of Energy Research
JF - International Journal of Energy Research
IS - 15
ER -