TY - GEN
T1 - Comparison of passive and active types of proton exchange membrane fuel cell / battery HEVs
AU - Wang, Lu Jung
AU - Hung, Yi Hsuan
AU - Li, Jeen Fong
AU - Kuo, Chin Guo
AU - Lue, Yeou Feng
AU - Cheng, Chin Hsien
AU - Wu, Chien Hsun
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/6/1
Y1 - 2015/6/1
N2 - The concept of this paper is to compare the performance of a passive and an active hydrogen fuel cell/battery electric vehicles under ECE-40 driving cycle. First, the subsystems of the active vehicle were modeled by low-order dynamics and performance maps. Subsystems include the battery, proton exchange membrane fuel cells (PEMFCs), DC/DC converter, vehicle dynamics, traction motor, hydrogen storage system were modeled on the Matlab/Simulink platform. Next, a set of 9 fuzzy rules are designed for energy management. Two inputs are the residual hydrogen and demanded total power while the single output is the power ratio between the battery and fuel cells. Simulation results show that the vehicle simulator is able to evaluate the battery SOC, hydrogen consumption, motor and DC/DC converter efficiencies, fuel cell current and voltage, etc.. Comparing performance of active and passive type vehicles, though the SOC of the active type is 1.97% less than the passive type, the former saves 1.31g hydrogen consumption, where the total hydrogen energy was improved by 9.75%. The comparison of two types of real fuel cell/battery hybrid vehicles will be conducted in the future.
AB - The concept of this paper is to compare the performance of a passive and an active hydrogen fuel cell/battery electric vehicles under ECE-40 driving cycle. First, the subsystems of the active vehicle were modeled by low-order dynamics and performance maps. Subsystems include the battery, proton exchange membrane fuel cells (PEMFCs), DC/DC converter, vehicle dynamics, traction motor, hydrogen storage system were modeled on the Matlab/Simulink platform. Next, a set of 9 fuzzy rules are designed for energy management. Two inputs are the residual hydrogen and demanded total power while the single output is the power ratio between the battery and fuel cells. Simulation results show that the vehicle simulator is able to evaluate the battery SOC, hydrogen consumption, motor and DC/DC converter efficiencies, fuel cell current and voltage, etc.. Comparing performance of active and passive type vehicles, though the SOC of the active type is 1.97% less than the passive type, the former saves 1.31g hydrogen consumption, where the total hydrogen energy was improved by 9.75%. The comparison of two types of real fuel cell/battery hybrid vehicles will be conducted in the future.
KW - energy management
KW - fuel cell
KW - fuzzy control
KW - hybrid powertrain
KW - modeling
UR - http://www.scopus.com/inward/record.url?scp=84941213914&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84941213914&partnerID=8YFLogxK
U2 - 10.1109/ICNSC.2015.7116089
DO - 10.1109/ICNSC.2015.7116089
M3 - Conference contribution
AN - SCOPUS:84941213914
T3 - ICNSC 2015 - 2015 IEEE 12th International Conference on Networking, Sensing and Control
SP - 509
EP - 514
BT - ICNSC 2015 - 2015 IEEE 12th International Conference on Networking, Sensing and Control
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2015 12th IEEE International Conference on Networking, Sensing and Control, ICNSC 2015
Y2 - 9 April 2015 through 11 April 2015
ER -