Optimal Li-Ion battery sizing on PEMFC hybrid powertrain using dynamic programming
This investigation studies the effect of the number of Li-Ion battery modules on the fuel consumption and the 10-year operating cost for optimal powertrain design in a Proton Exchange Membrane fuel cell (PEMFC) hybrid vehicle. A 30kW PEMFC stack is in parallel with a number of 334Wh-LiFePO4 battery...
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Main Authors: | , , |
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Format: | Conference Proceeding |
Published: |
2018
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Subjects: | |
Online Access: | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84881449474&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/52549 |
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Institution: | Chiang Mai University |
Summary: | This investigation studies the effect of the number of Li-Ion battery modules on the fuel consumption and the 10-year operating cost for optimal powertrain design in a Proton Exchange Membrane fuel cell (PEMFC) hybrid vehicle. A 30kW PEMFC stack is in parallel with a number of 334Wh-LiFePO4 battery modules to deliver its energy to a 77 kW electric drive (ED). The ED output is connected to the gear box and the lower powertrain. For a given road/load mechanical power demand on the vehicle, the ED power profile can be computed. The electrical power-split strategy between the PEMFC and the battery pack plays a great role on the hydrogen fuel consumption and cost. The dynamic programming (DP) approach is adopted to compute the optimal power management strategy and to evaluate the vehicle performance and the average fuel consumption over five different standard driving profiles, i.e. Japan 10/15 mode, UN/ECE, UDDS, HWFET, and SFTP. The objective function to be minimized consists of the fuel cost and the Li-Ion battery cost. Since the Li-Ion battery is expensive, the battery's state of charge (SOC) operating range is limited to 0.5 and 0.7 to prolong the battery lifetime. From the simulation results, it is found that for average driving distance 10,000 km/year, the set of 5 battery modules is the most appropriate option. The set of 8 battery modules is best for average driving distance more than 50,000 km/y. © 2013 IEEE. |
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