This research presents a two-part study on a fuel cell electric van (FCEV), focusing on
vehicle modelling and developing different control strategies for the modelled vehicle.
The modelling phase accounts for the aging effects on the fuel cell (FC) and battery, analyzing FCEV behavior over time. This includes estimating and integrating
the degradation impacts on characteristic curves, such as the FC’s polarization and
efficiency curves, the battery’s charging and discharging resistance curves, and the
open-circuit voltage curve. A simplified fuel cell system (FCS) model is designed to
consider power losses in multiple components, including the FC stack, air compressor,
and others. The dynamic limits of the FC are also included to yield more realistic
results. The model is based on the vehicle Opel Vivaro FC specifications, incorporating parameters like maximum FC power, battery capacity, vehicle weight, and tire
dimensions.
Subsequently, various control strategies are applied to analyze their effectiveness
in FC and battery State-of-Health (SOH) degradation and hydrogen consumption. A
rule-based energy management system (EMS) is implemented first, which operates
with five different operational modes dependent on the vehicle’s state. This is followed
by a look-up table (LUT) based strategy, which uses two two-dimensional tables
generated by a Neural Network (NN). The network is trained with discretized optimal / Thesis / Master of Applied Science (MASc)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/30130 |
| Date | January 2024 |
| Creators | Miranda, Tiago Suede |
| Contributors | Emadi, Ali, Mechanical Engineering |
| Source Sets | McMaster University |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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