Impacts of Electric Highways for Heavy-Duty Trucks

*PhD Defense*
March 9 2020 09:00–12:00
Calit 2 Room 3008
Mariana Teixeira Sebastiani
Mariana Teixeira Sebastiani
TSE PhD Candidate

The incorporation of alternative fuel vehicles has been essential in reducing emissions in the transportation sector. Particularly to heavy-duty trucks, zero-emission technologies are becoming more attractive. However, batteries and fuel cells still face a long way until they became became a viable solution in terms of price, autonomy, weight, and infrastructure. An interim solution is the use an overhead catenarysystem, also known as eHighway. The pilot project demonstrated the feasibility of the eHighway system; however, the literature exploring this type of technology is lacking. This dissertation aims to cover this literature gap and propose a new framework to comprehensively explore the aspects of an eHighway implementation in terms of optimal placement, effects on the well-to-wheel (WTW) emissions, and impacts on the power grid. This methodology was applied to a California model using data from the California Statewide Freight Forecasting Model.

First, we defined the optimal eHighway placement to maximize vehicle miles traveled in the system or minimize emissions around disadvantage communities in four different scenarios for the years of 2020 and 2040. This process shows that most eHighways would be located along the I-5 or close to ports to maximize vehicle miles traveled or in Central Valley to maximize the benefit for disadvantage communities.

Second, we estimated the WTW emissions for heavy-duty truck according to the truck fuel type for each of the scenarios with adoption rates from 25% to 100%. The total emissions in terms of CO2 and NOx were compared to a scenario without eHighway. All the eHighway scenarios for 2020 and 2040 reduced the total WTW heavy-duty truck emissions. The best-case scenario for 2020, with 500 miles of total eHighway length and adoption rate of 100%, reached a reduction of almost 8% in CO2 emission and over 20% of NOx. The same scenario showed a reduction of 16% in CO2 and 20% of NOx for the year 2040. 

Finally, we analyzed the impacts of the eHighway energy demand on the state's power grid. We showed that some of the systems would require up to 1 MWh of daily energy from some power substation. However, due to the unavailability of public data on California's power grid, we could not draw conclusions in terms of the ability of these substation to handle such demand.

These results show the applicability of the proposed methodology for the deployment and impacts of the eHighway system. Furthermore, although there are other aspects to be considered before large-scale implementation of the eHighway system (e.g., costs), the results presented in this study support the deployment of an eHighway system in California to support the urgent need for making road freight transport more sustainable.