Feasibility of Operating a Heavy-Duty Battery Electric Truck Fleet for Drayage Applications

Vehicle fleet electrification is regarded as one major pathway toward achieving energy independence and reducing air pollution and greenhouse gas emissions. Compared to light-duty and medium-duty vehicles, electrification of heavy-duty vehicles, especially Class 8 trucks, is more challenging owing to the battery size required to attain the driving range necessary for their operating goals. As drayage trucks generally have a limited daily mileage, return to a home base every night, and spend a large amount of time creeping and idling, drayage operation has been the first targeted application for Class 8 electric trucks. The feasibility of operating battery electric drayage trucks at the individual vehicle level has recently been demonstrated. However, questions remain as to whether these trucks are capable of meeting the needs of typical drayage operation at the fleet level. This paper presents a feasibility analysis of operating an electric truck fleet based on real-world operation data of a diesel drayage operator in Southern California. Second-by-second activity data collected from 20 trucks in the fleet were used to estimate the corresponding electric energy consumption and the state of charge of the battery using a microscopic electric energy consumption model. An algorithm for generating tours of drayage activity from the collected data was developed and implemented. Multiple scenarios with different battery charging and truck scheduling assumptions were analyzed. The results show that 85% of the tours could be served by electric trucks if there is opportunity for charging at the home base during the time gap between consecutive tours.

Tour-Based Truck Demand Modeling with Entropy Maximization Using GPS Data

An approach is presented to determine the most likely tour distributions and model behavior for investigating drayage truck movements in a coastal region. This was done by implementing a revised form of entropy maximization based on truck tours to model and better understand drayage truck tour behavior at the San Pedro Bay Ports (SPBPs) complex in Southern California. The drayage trucks at the SPBPs have features that are distinct from other commercial trucks. The tour-based entropy maximization model proposed in this paper provides an opportunity to incorporate periodically updated GPS data collected in Southern California into a large-scale tour-based model. With the dataset, four models were estimated by cargo movement: (1) year-based, (2) low period, (3) medium period, and (4) high period models. The findings were consistent with the tour patterns varying by season and by cargo movement. Furthermore, the medium period, which represented relatively steady cargo movement, indicated a better MAPE (mean absolute percent error) than did other models. This proposed approach provides a significant advantage in that the most recent touring information obtained from advanced technologies could be directly applied to the tour-based model and subsequently used to assess various strategies.

A Study on Emissions from Drayage Trucks in the Port City-Focusing on the Port of Incheon

As a result of growing international trade, port-related emission is a spreading issue for urban areas located near ports, especially, hub port cities where population density is concentrated. The awareness of rapidly increasing drayage trucks moving cargo between the port and its hinterland has motivated the necessity of a detailed look at negative environmental impacts of these truck fleets on the achievement of sustainability goals. This study analyzes emission inventory from trucking activities around the Port of Incheon (POI), especially focusing on major air pollutants, and suggests ideas to support establishing new policies in port area. Data on the number of truck, the year of production, the type of fuel, etc. during 2018 were collected from Incheon Port Security and Korea Transport Safety Authority. A bottom-up methodology is applied based on guideline from the U.S. Environmental Protection Agency (EPA). As results, the major role of drayage truck fleets to local air pollution was highlighted with the high contribution of CO and NOx emissions. Hence, this study suggested the establishment of Emission Control Area (ECA) and Affected Zone on the landside as well as implementing Integrated Information System and Truck Appointment System to reduce congestion at gate, limit the number of emissions and minimize negative impacts to local community.

Characterization of Drayage Activities in the Paso Del Norte Airshed

The overall objective of the study was to characterize drayage truck activity and associated emissions in the Paso del Norte region, which is the binational region covering El Paso in Texas and Ciudad Juárez in Mexico. Drayage trucks are a significant source of emissions in the Paso del Norte airshed. The region faces air quality problems and characterizing the unique operational and emission characteristics of drayage vehicles can better support regional air quality planning. In this study, the global positioning system and portable activity measurement system units were fitted to a sample of drayage trucks operating in the El Paso region. The resulting data were analyzed to generate trip-level information on truck activity, along with key parameters, such as speeds, origin, destination, and length. The individual trip information was also used to identify key freight corridors and to estimate emissions associated with drayage activity. The study dataset showed that the Ysleta-Zaragoza International Bridge is the most utilized by the trucks. The facilities visited in the United States tended to be more clustered closer to this bridge, in less urbanized areas, while facilities visited in Mexico tended to be more spread out geographically. Corridor truck volumes and emissions were plotted on maps to visualize emission impacts of drayage trucks, with urbanized areas and areas close to border bridges likely most affected because of higher volumes and emissions. The findings from the study provide an understanding of air quality impacts of drayage trucks in the Paso del Norte airshed.

Development of a Duty Cycle for the Design and Optimization of Advanced, Heavy-Duty Port Drayage Trucks

Hybrid electric and electric trucks are potential technology solutions for reducing emissions at ports. However, developing an advanced, low-emission technology driveline entails thoroughly understanding typical truck operations in the real-world environment. This paper presents the work performed to develop a novel, more representative drayage duty cycle that characterizes drayage truck operations in the ports of San Pedro Bay in California. Unlike a conventional vehicle, an optimized hybrid driveline requires detailed understanding not only of torque requirements and vehicle speeds but also of the potential recovery of dynamic brake energy, charging opportunities, stopping and idling times, and many other operational requirements. Keeping this in mind, the duty cycle presented in this paper incorporated real-world, near-dock activities of Class 8 drayage trucks such as daily hours of operation, mileage, altitude profiles of routes, and idling and key-off patterns. The empirical duty cycle model was subsequently integrated with a complete vehicle simulation to explore the best solutions to minimize energy consumption for drayage applications in and around the ports. The analysis presented indicates that trucks spent most of the generated power in overcoming aerodynamic drag and rolling resistance of tires for a complete drayage shift and that electrical auxiliary loads dominated for near-dock operations because of idling and low-speed profiles. Therefore, achieving zero-emission near-dock operations entails focusing on auxiliary loads and rolling resistance. By using simulations, it was estimated that a hybrid truck with electrical power limited to about 100 kW could deliver a greenhouse gas emission reduction of about 30%.