UC Irvine

Heavy-duty vehicles (HDVs) are one of the largest contributors of both greenhouse gas (GHG) and criteria pollutant emissions in California. The burning of heavy diesel fuels and even the cleaner burning of natural gas within internal combustion engine (ICE) trucks are unsustainable. As such, as part of California’s goals to reach net zero GHG emissions by 2045, California has mandated that all drayage trucks must be zero-emission by 2035 and all other HDVs be zero-emission by 2045. This mandate will force the adoption of zero-emission technologies such as battery electric trucks (BETs) and fuel cell electric trucks (FCETs).While battery electric technology has begun to succeed in the light-duty vehicle (LDV) market, the challenges associated with battery power are exacerbated in HDV applications including long charge times, immense power demands on grid infrastructure, heavier vehicle weight, and limited vehicle range. Hydrogen fueled FCETs have the advantages of faster refuel times, lighter vehicles, and larger vehicles ranges, all of which are more comparable to the performance of modern diesel trucks. As such, hydrogen fueled FCETs will play a major role in all HDV vocations, likely dominating in long-haul applications. The major inhibition to the adoption of FCETs is the lack of refueling infrastructure, the subject of this thesis. To study and aid the initial deployment and rollout of Hydrogen Refueling Stations (HRSs), a model was developed in ArcGIS to spatially optimize HRS deployment within California and optimally support the predicted adoption of FCETs in the coming years. The model aims at optimizing refueling coverage to provide the most support possible and the least compromises of desired truck routing. The model also accurately informs the number of HRSs needed within the state to cover the anticipated fueling demands and how different station parameters might affect the performance of the network. While stations will be required to meet the total demand of the state, an initial subset of well optimized stations can effectively meet a majority of the trucking demand in California.