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In the United States, the transportation sector  is the largest single source of greenhouse gas (GHG) and nitrogen oxide (NOx) emissions, and heavy-duty trucks contribute a disproportionately large share. Therefore, the trucking industry has been seeking ways to minimize emissions, such as adopting zero-emission vehicles and improving truck operating strategies to reduce truck miles. Battery-powered vehicles have different limitations than those with internal combustion engines. In this study, researchers from the University of Southern California investigated the adoption of battery electric heavy-duty trucks (BEHDTs) in the short-haul freight movement sector and the drayage industry. Drayage is a short-haul pickup and delivery service for transporting freight among ports, warehouses, and other facilities. With drayage routing, vehicles have limited weight and volume capacities and often make many stops. Routing involves optimizing for multiple factors, like fuel, distance traveled, and timeliness. This brief summarizes the findings from that research and provides implications for the field.View the NCST Project Webpage

The adoption of battery electric trucks (BETs) as a replacement for diesel trucks has potential to significantly reduce greenhouse gas (GHG) emissions from the freight transportation sector. However, BETs have shorter driving range and lower payload capacity, which need to be taken into account when dispatching them. This paper addresses the energy-efficient dispatching of BET fleets, considering backhauls and time windows. To optimize vehicle utilization, customers are categorized into two groups: linehaul customers requiring deliveries and backhaul customers requiring pickups, where the deliveries need to be made following the last-in-first-out principle. The objective is to determine a set of energy-efficient routes that integrate both linehaul and backhaul customers, while considering factors such as limited driving range, payload capacity of BETs and the possibility of en route recharging. The problem is formulated as a mixed-integer linear programming (MILP) model and propose an adaptive large neighborhood search (ALNS) metaheuristic algorithm to solve it. The effectiveness of the proposed strategy is demonstrated through extensive experiments using a real-world case study from a logistics company in Southern California. The results indicate that the proposed strategy leads to a significant reduction in total energy consumption compared to the baseline strategy, ranging from 7% to 40%, while maintaining reasonable computational time. This research contributes to the development of sustainable transportation solutions in the freight sector by providing a practical and more efficient approach for dispatching BET fleets. The findings emphasize the potential of BETs in achieving energy savings and advancing the goal of green logistics.  View the NCST Project Webpage

California has a long history of reducing greenhouse gas (GHG) emissions, and has been working to accelerate the adoption of battery electric heavy-duty trucks (BEHDTs). Unlike diesel heavy-duty trucks (DHDTs), which have hundreds of miles of range per refill, BEHDTs have a restricted, load-dependent driving range, which makes charging planning an important role in the use of BEHDTs as an alternative to DHDTs. This research study investigates a mixed fleet drayage routing problem (MFDRP) with non-linear charging times. The study extends existing mixed fleet drayage routing models by considering multiple charging locations and allowing for more flexible routes for freight pickup and delivery. We formulate the MFDRP as a mixed integer programming model. After linearization and variable elimination, the model can be solved by commercial optimization solvers. However, the model becomes inefficient to solve when the problem size increases. Therefore, we develop a modified adaptive large neighborhood search algorithm, which can solve the problem with hundreds of units of demand in a few CPU minutes. Finally, we simulate one-day drayage operations with different BEHDT shares in the fleet for the years 2022, 2025, and 2030 to assess the potential for substituting DHDTs with BEHDTs. The numerical experiments indicate that employing BEHDTs as substitutes for DHDTs will increase the fleet size under the same level of demand. To reach the maximum share of BEHDTs in the truck fleet, the fleet size increases by 47.2%, 3.4%, and 3.4% in 2022, 2025, and 2030, respectively. Over 50% (90%) CO2 (NOx) emission reductions can be achieved by employing BEHDTs to the maximum share in the fleet.View the NCST Project Webpage

In order to uptake of electric vehicles (EV) into last mile delivery, we recommend the deployment of a combination of novel and existing policies to both encourage widespread EV uptake and discourage the use of diesel-based freight through zero emission delivery zones and purchase subsidies. Our research is composed of three methods: Interviews, Quantitative Modeling, and Quantitative Modeling. The interviews and quantitative analysis revealed that the burden on delivery companies is greater than the social benefits such as GHG reductions due to the large investment in EVs. The effectiveness of the policy combination was also confirmed. Using the three criteria of Political Feasibility, Efficiency, and Equity, we evaluated the policies using the Criteria-Alternative Matrix and concluded that the voluntary ZEDZ is the most effective stand-alone policy. Since no one pollutant reducing policy can meet all criteria effectively we recommend packaging various policies together. Our model demonstrates that a combination of policies produce the highest results in decreasing costs and pollutant levels, particularly a combination of purchase subsidies and mandated ZEDZ. To better improve equity scores, we recommend cities consider adding purchase subsidies of freight electric vehicles to a ZEDZ program to offset costs businesses would incur, particularly small businesses transitioning to electric vehicle fleets. Mandated ZEDZ would add additional burdens on small businesses since these companies don’t have the capital to transform fleets.

Carbon emissions targets require large reductions in greenhouse gases (GHGs) in the near-to mid-term, and the transportation sector is a major emitter of GHGs. To understand potential pathways to GHG reductions, this project developed the U.S. Transportation Transitions Model (US TTM) to study various scenarios of zero-emission vehicle (ZEV) market penetration in the U.S. The model includes vehicle fuel economy, vehicle stock and sales, fuel carbon intensities, and costs for vehicles and fuels all projected through 2050. Market penetration scenarios through 2050 are input as percentages of sales for all vehicle types and technologies. Three scenarios were developed for the U.S.: a business as usual (BAU), low carbon (LC), and High ZEV scenario. The LC and High ZEV include rapid penetration of ZEVs into the vehicle market. The introduction of ZEVs requires fueling infrastructure to support the vehicles. Initial deployments of ZEVs are expected to be dominated by battery electric vehicles. To estimate the number and cost of charging stations for battery electric trucks in the mid-term, outputs were used from a California Energy Commission (CEC) study projecting the need for chargers in California. The study used the HEVI-Pro model to estimate electrical energy needs and number of chargers for the truck stock in several California cities. The CEC study outputs were used along with the TTM model outputs from this study to estimate charger needs and costs for six U.S. cities outside California. The LC and High ZEV scenarios reduced carbon emissions by 92% and 94% in the U.S. by 2050, respectively. Due to slow stock turnover, the LC and High ZEV scenarios contain significant numbers of ICE trucks. The biomass-based liquid volume reaches 70 (High ZEV) to 80 (LC) billion GGE by 2045. For the cities in this study, the charger cost ranges from $5 million to $2.6 billion in 2030 and from roughly $1 billion to almost $30 billion in 2040.View the NCST Project Webpage

This project aims to assess the current and future performance and costs of battery electric trucking, through reviewing key recent studies in the U.S. and presenting a detailed comparison of their cost modeling scope and coverage. This white paper presents a review of 10 recent studies of the total cost of ownership (TCO) of battery electric trucks (BET), now and in the future, compared to a baseline diesel truck, for the following 3 important types of truck: heavy-duty long-haul trucks, medium-duty delivery trucks, and heavy-duty drayage/short-haul trucks. The researchers break down the studies into their estimates for a range of important cost and operating factors, such as vehicle purchase cost, efficiency, fuel cost, maintenance cost, required range and thus battery pack sizing, and other factors. Of note are differences in major assumptions of studies and variables that are included or excluded from consideration. The authors do not judge these studies against each other but attempt to derive general findings that are robust across studies, areas of significant difference, and areas for further research. Overall, TCO estimates across the studies, for a given truck type, can vary dramatically, though often several studies cluster together. But as this study explores, the differences in TCO link directly to differences in assumptions, parameters and other differences across the studies. The studies vary in important ways that should be taken into account when comparing TCO estimates. Policy makers should consider the context of truck type, truck use and other factors when reading such studies, and pay attention to assumptions. Policies should reflect the wide range of situations that trucks may encounter and avoid assuming a simple average TCO across all situations.View the NCST Project Webpage

California’s Advanced Clean Trucks regulation requires sales of zero-emission tractor-trailer trucks starting in 2024, increasing to 30% by 2030. Since most of these trucks will travel predominantly on the state’s major highways, a robust network of battery charging infrastructure will be needed along these routes. The California Department of Transportation (Caltrans) maintains an extensive series of roadside rest areas throughout the state that are widely used by long-haul trucks. Providing charging at roadside rest areas, especially those along interstate highways, could help meet the needs of battery-electric tractortrailer trucks making multi-day trips. Thus, Caltrans should consider becoming involved with the establishment of battery charging facilities at its rest areas.Researchers at the University of California, Davis assessed the possibilities for and barriers to providing charging infrastructure for heavy-duty, long-haul trucks at rest areas in California. This policy brief summarizes the findings from that research and provides policy implications.View the NCST Project Webpage

The objective of this research was to determine the possibilities for and barriers to the provision of battery charging infrastructure for heavy-duty electric trucks at roadside rest areas in California. The initial sections of the report deal with the prospects for battery-electric long-haul trucks and the battery technology needed to make those electric trucks practical and the market for them to be successful. Simulations of trucks using present lithium battery technology indicated that for a range of 600 miles, the battery pack would need to store about1200 kWh. It is not practical to fit a battery of that size on the tractor of the truck. Another approach is to design a truck with a 300 mile range and plan to partially charge the battery once or twice during the day at rest areas. The truck could also be charged overnight at the rest areas. The total range per day could be 600 miles or more. The partial charges would put 65% of the capacity of the battery in at the 1C rate (a 60 minute charge). A 450-500 kW charging facility would be needed at the rest areas. The 300 mile range electric truck could operate much like the diesel truck with the driver taking 60 minute breaks every 200-225 miles to charge the battery. The cost analysis of the 300 mile truck indicates its TCO is less than that of the diesel truck. In California, there are Low Carbon Fuel Standards (LCFS) credits to reduce the costs to operate the charging facility. If applicable, the LCFS station credits (＄/yr) can be as much as ＄65k/yr per charger up to the total cost of the facility in about five years. The LCFS electricity credit would permit the cost of electricity to be only ＄.12/kWh to charge the batteries, because the price includes the LCFS credit to the utility. Hence with LCFS credits, the cost of operating the charging facility could be low in the early years while the market for electric long-haul trucks is developing. Caltrans maintains 86 safety rest areas along highways in California with 53 along Interstate highways. If battery charging facilities were established at about 35 of these rest areas, they would be about 100 miles apart or a little closer. Caltrans could assist private contractors in establishing a network of charging facilities for electric trucks. The total initial cost could be about ＄50 million. The major barrier to Caltrans participating in the battery charging project is that current law prohibits commercial businesses at the rest areas which would not allow charging for the electricity dispensed. There has been consideration in both California and at the federal level to relax the non-commercial requirements at the rest areas for battery charging because the need for a battery charging network is well recognized.View the NCST Project Webpage

The imperative to decarbonize long-haul, heavy-duty trucking for mitigating both global climate change as well as air pollution is clear. Given recent developments in battery and ultra-fast charging technology, some of the prominent barriers to electrification of trucking are dissolving rapidly. Here we shed light on a significant yet less-understood barrier, which is the general approach to retail electricity pricing. We show that this is a near term pathway to $0.06/kWh charging costs that will make electric trucking substantially cheaper than diesel. This pathway includes (i) reforming demand charges to reflect true, time-varying system costs; (ii) avoiding charging during a few specific periods (

The imperative to decarbonize long-haul, heavy-duty trucking for mitigating both global climate change as well as air pollution is clear. Given recent developments in battery and ultra-fast charging technology, some of the prominent barriers to electrification of trucking are dissolving rapidly. Here we shed light on a significant yet less-understood barrier, which is the general approach to retail electricity pricing. We show that this is a near term pathway to $0.06/kWh charging costs that will make electric trucking substantially cheaper than diesel. This pathway includes (i) reforming demand charges to reflect true, time-varying system costs; (ii) avoiding charging during a few specific periods (

This report presents the results of a project to develop a truck vehicle/fuel decision choice model for California and to use that model to make initial projections of truck sales by technology out to 2050. The report also describes the linkage of this model to a broader scenarios model of road transportation energy use in California to 2050. A separate report provides the authors detailed assumptions about truck technologies, fuels, and projections to 2050 that are inputs to this choice modeling effort. The need for low carbon trucking in California, as in other states and countries of the world, is outlined in IPCC reports and the Paris Agreement. An 80% reduction in energy-related CO2 emissions worldwide is targeted in that agreement. For trucks to contribute anywhere near this level of reduction, new, zero emissions technologies, such as electric and hydrogen fuel cell trucks, would need to be adopted at a large scale and at a rapid pace, both unprecedented for trucks anywhere in the world to date. Many truck models create new technology market penetration scenarios through minimizing cost or in an ad-hoc manner. This model utilizes a fleet decision choice process based on real world factors identified through discussions with trucking fleets. These factors include capital and operating costs, uncertainty (risk), model availability, refueling inconvenience, green PR (perceived benefit of environmentally beneficial technologies), and various incentives. The authors have developed a spreadsheet structured as a nested multinomial logit model that monetizes these factors to calculate a generalized cost. The authors have attempted to estimate the value of these factors to different types of fleets using a series of interviews, initial survey work, a truck choice workshop, and finally expert judgment and “basic logic” on how various factors might be valued now and in the future. The factors drive the choice analysis and are highly uncertain and likely highly variant across fleet types and even fleets within a type (early adopter, late adopter, in between), so the authors use a scenario approach to explore how this uncertainty could affect their results and projections. The authors created four scenarios and variants: 1) a business as usual (BAU), 2) a zero-emission vehicle (ZEV) mandate requiring the market share of ZEVs to reach 25% by 2050 (ZEV scenario 1a), 3) the same scenario but with a low penalty assumed for refueling time and (ZEV scenario 1b) 4) a ZEV mandate requiring the market share of ZEVs to reach 50% by 2050 (ZEV scenario 2). The authors also look at some policies that could help to spur sales growth among ZEV technologies in order to reach specific targets.View the NCST Project Webpage