Understanding Zero-Emission Truck Activity Patterns from Early Deployments in California
Research Lead: Kanok Boriboonsomsin
UC Campus(es): UC Riverside
Problem Statement: Governor Newsom’s Executive Order N-79-20 sets aggressive targets for the sales of zero-emission trucks in the state through 2035. Given the current state of vehicle technologies, most zero-emission trucks on the roads in the next five years will likely be battery electric trucks (BETs). While performance specifications of recent BETs have improved, they still have shorter driving range and require longer recharging time than conventional diesel trucks, which can significantly impact fleet operations. To facilitate a successful transition of heavy-duty truck fleets in California to zero-emission technologies, it is important to better understand activity patterns of BETs in real-world operations by learning from early deployments of these trucks. Senate Bill 535, and Assembly Bill 1550 that followed, directed the California Environmental Protection Agency to identify Disadvantaged Communities (DACs), and established minimum levels of the proceeds from the state’s Cap-and-Trade Program that should be invested in these areas. Several zero-emission truck demonstration and pilot deployment projects have occurred in DACs, however, the trucks in these projects also traveled to different areas. Therefore, an assessment of their operation inside DACs and emissions reduction benefits provided to these communities is needed.
Project Description: The project team will estimate the emissions reduction benefits from zero emission truck activity data collected by the South Coast Air Quality Management District (SCAQMD) from demonstration and pilot deployment projects in the South Coast Air Basin, especially in communities that have been heavily impacted by truck traffic. The data include time-stamped records of vehicle position and speed, battery state of charge, and charging events. The project team will identify individual trips and tours for each BET to determine average travel distance, average travel time, average energy consumption, etc. They will also determine where and when BETs travel and their charging patterns. In addition, the researchers will determine how often the BETs operated inside DACs and estimate the emissions that were avoided from operating them in place of conventional diesel trucks.
Status: In Progress