Projecting adoption of truck powertrain technologies and CO2 emissions in line-haul networks. (July 2020) - Guerrero de la Peña, Ana; Davendralingam, Navindran; Raz, Ali K.; DeLaurentis, Daniel; Shaver, Gregory; Sujan, Vivek; Jain, Neera
Highlights: A mixed-integer linear program is used to model the freight transportation system. Alternative powertrain technology adoption and CO2 emissions are projected. Multiple powertrains are considered, including CNG and battery electric. Modeling framework considers infrastructure availability and policy measures. Mixed-adoption scenarios that reduce CO2 emissions by >25% are identified. Abstract: In this paper we present a mixed-integer linear program to represent the decision-making process for heterogeneous fleets selecting vehicles and allocating them on freight delivery routes to minimize total cost of ownership. This formulation is implemented to project alternative powertrain technology adoption and utilization trends for a set of line-haul fleets operating on a regional network. Alternative powertrain technologies include compressed (CNG) and liquefied natural gas (LNG) engines, hybrid electric diesel, battery electric (BE), and hydrogen fuel cell (HFC). Future policies, economic factors, and availability of fueling and charging infrastructure are input assumptions to the proposed modeling framework. Powertrain technology adoption, vehicle utilization, and resulting CO2 emissions predictions for a hypothetical, representative regional highway network are illustrated. A design of experiments (DOE) is used to quantify sensitivity of adoption outcomes to variation in vehicle performance parameters, fuel costs, economic incentives, and fueling and charging infrastructure considerations. Three mixed-adoption scenarios, including BE, HFC, and CNG vehicle market penetration, are identified by the DOE study that demonstrate the potential to reduce cumulative CO2 emissions by more than 25% throughout the period of study.