Conventional Truck Research Articles

A cost-effectiveness comparison of renewable energy pathways for decarbonizing heavy-duty vehicles in China

Decarbonizing heavy-duty vehicles is becoming increasingly important, yet multiple renewable-based decarbonization pathways have not been compared systematically. To fill this gap, this study develops a techno-economic and environmental model that integrates the fuel cycle and vehicle cycle to assess these pathways for China. The model includes two energy storage technologies: batteries and hydrogen, three energy transmission options, and two vehicle types: fuel cell electric vehicles and battery electric vehicles. Five distinct low-carbon pathways are evaluated on a ton-kilometer basis, including cost, greenhouse gas emissions, and abatement cost relative to conventional diesel trucks. Results indicate that the most cost-effective battery electric vehicle pathway offers a 7 % lower ton-km cost than diesel trucks for a 49-ton gross vehicle weight. Battery electric vehicle charging combined with hydrogen for power generation is more cost-effective than direct use of hydrogen in fuel cell electric vehicles. All studied pathways can achieve over 80 % emission reduction compared to diesel trucks, with fuel cell electric vehicle pathways having the highest abatement costs of 103–117 USD/tonCO2. Analysis of the impact of gross vehicle weight and vehicle range indicates that battery electric vehicle pathways outperform fuel cell electric vehicle pathways across most dimensions. Costs of battery electric vehicle pathways do increase sharply for vehicle ranges beyond about 700 km, and fuel cell electric vehicles become more cost-effective relative to battery electric vehicles for ranges above approximately 1100 km, although all pathways are much more costly than diesel trucks at long ranges. The sensitivity analysis highlights the importance of powertrain efficiency and cost projections show that fuel cell electric heavy-duty vehicles can achieve cost-parity before 2030. These results highlight the desirability of promoting the adoption of heavier battery electric vehicles and providing more targeted subsidies for long-range fuel cell electric vehicles.

Impact of an eHighway on the directly emitted greenhouse gases by road freight transport

German legislation sets forth that anthropogenic greenhouse gases must be net-zero from 2045 onward (KSG, 2019). In contrast, road freight transport is projected to grow significantly (BMVBS, 2008; BMVI, 2021). If sustainable solutions for road freight transport are not implemented swiftly, Germany will not be able to meet its climate protection targets. This study analyzes the potential of the eHighway system—an overhead contact line-based electrification of trucks—to reduce the road freight transport's carbon footprint. Based on more than three years of field test operation with over 500,000 real-world driven kilometers, we estimate the saving potential of directly emitted greenhouse gases from five pilot overhead contact line trucks that use the eHighway system (O-trucks). We conclude that with only a five percent electrified stretch of a trip, 14–17% of direct greenhouse gas emissions are saved compared to a conventional truck. We develop a scaling and comparison calculator for the estimation of directly emitted greenhouse gases of O-trucks. We argue that with an electricity mix based upon renewable energies and an appropriately extended eHighway network, road freight transport is capable of offering transport with net-zero greenhouse gas emissions. Based on a unique data set, we provide a benchmark for all further research in evaluating eHighway technology and for comparing it to alternative drive technologies.

Developing Fuel Savings Performance Function Considering Various Truck Platooning Configurations

<div>Truck platooning facilitates the operation of trucks in close proximity to one another, resulting in decreased air resistance and improved fuel efficiency. While previous research has mostly focused on the effects of intra-distance on fuel savings, this study aims to develop fuel savings performance functions considering various truck platooning configurations. This article comprehensively investigates the influence of different truck platoon configurations on fuel savings. This analysis focuses on examining the impacts of several variables including inter-vehicle distance, platoon speed, truck weight, number of trucks in the platoon, and the truck’s distinctive design characteristics. Data used in the analysis were collected from 10 different field experiments. Three machine learning techniques—artificial neural networks (ANN), extreme gradient boosting (XGBoost), and K-nearest neighbors (KNN)—alongside the negative binomial regression model were employed. Upon evaluation, the negative binomial regression model emerged as the most accurate, boasting a prediction accuracy of 74%. This high-performing model was subsequently leveraged to derive an equation for estimating fuel savings. The results indicated that the truck platoon’s size is the most significant factor affecting fuel efficiency. Specifically, the inclusion of additional trucks in the platoon leads to substantial fuel savings. Moreover, as the platoon’s speed increases, there is a noticeable increase in fuel savings. The design of the truck plays a role: conventional trucks are more fuel efficient than cab-over trucks. Lastly, the weight of the truck has a minor impact on the platoon’s fuel efficiency. Overall, it is essential to consider multiple variables when evaluating truck platoon arrangements for optimal fuel efficiency.</div>

Zero-Emission Heavy-Duty, Long-Haul Trucking: Obstacles and Opportunities for Logistics in North America

Background: Pressure is growing in North America for heavy-duty, long-haul trucking to reduce greenhouse gas (GHG) emissions, ultimately to zero. With freight volumes rising, improvement depends on zero-emissions technologies, e.g., battery electric vehicles (BEVs) and fuel cell electric vehicles (FCEVs). However, emissions reductions are constrained by technological and commercial realities. BEVs and FCEVs are expensive. Further, BEVs depend on existing electricity grids and FCEVs rely on steam–methane reforming (SMR) or electrolysis using existing grids to produce hydrogen. Methods: This study assembles publicly available data from reputable sources to estimate breakeven vehicle purchase prices under various conditions to match conventional (diesel) truck prices. It also estimates GHG emissions reductions. Results: BEVs face numerous obstacles, including (1) limited range; (2) heavy batteries and reduced cargo capacity; (3) long recharging time; and (4) uncertain hours-of-service (HOS) implications. On the other hand, FCEVs face two primary obstacles: (1) cost and availability of hydrogen and (2) cost of fuel cells. Conclusions: In estimating emissions reductions and economic feasibility of BEVs and FCEVs versus diesel trucks, the primary contributions of this study involve its consideration of vehicle prices, carbon taxes, and electricity grid capacity constraints and demand fees. As electricity grids reduce their emissions intensity, grid congestion and capacity constraints, opportunities arise for BEVs. On the other hand, rising electricity demand fees benefit FCEVs, with SMR-produced hydrogen a logical starting point. Further, carbon taxation appears to be less important than other factors in the transition to zero-emission trucking.

Impacts of heavy-duty electric trucks on flexible pavements

ABSTRACT The transportation sector is responsible for significant greenhouse gas (GHG) emissions, with medium- and heavy-duty trucks (MHDTs) being major contributors. In response, medium- and heavy-duty electric trucks (MHDETs) are being explored as zero-emission alternatives. However, the weight of high-capacity batteries needed for long-haul trips and heavy loads could increase the axle loads as well as the gross vehicle weight (GVW) of heavy-duty electric trucks (HDETs), leading to extra damage on flexible highway pavements. This study simulated the GVW increment of HDETs and assessed its effects on pavement damage, environmental impacts, and life-cycle costs of four typical highway pavement structures in Illinois (known as thick–weak, thick–strong, thin–weak, and thin–strong). The utilisation of electric trucks resulted in significant reductions in diesel combustion related global warming potential (GWP) emissions and costs (in $2022) by 73% and 11.5%, respectively. However, the results demonstrated that with a 100% penetration of HDETs carrying an additional weight of 8 kips per truck, the pavement deterioration accelerated compared to traffic with conventional trucks. As a consequence, GWP and costs were reduced by 69% and 10.6%, respectively.

Why and Why Not? Systematic Review of the Willingness to Accept Drone and Robot Deliveries

Last-mile deliveries using drones and robots have recently emerged as alternatives to deliveries using conventional trucks. Because of the newness of the topic, there has been no synthesized summary of the acceptance of the emerging delivery modes, although the importance of the topic has increased with the growth of home deliveries. To fill the knowledge gap, this research systematically reviewed the literature on the willingness to accept drone and robot deliveries using the two largest publication databases: Web of Science and SCOPUS. A total of 46 academic studies were reviewed with respect to their trends, study scope (i.e., type of mode, type of products, modeling framework, and background theories), and factors that positively and negatively affect the willingness. Based on the review, knowledge gaps and the corresponding future research directions were derived: (a) robot-related investigations have been understudied compared to drones; (b) research from the shipper perspective is necessary; (c) transportation and logistics planning-related factors (e.g., socio-economic factors, trip and shipment characteristics) should be investigated; (d) an investigation of users’ behaviors based on actual usage (rather than relying solely on hypothetical scenarios) is necessary; (e) regulatory aspects should be taken into account; and (f) the heterogeneity of products needs to be taken into consideration.

Application of Real-Life On-Road Driving Data for Simulating the Electrification of Long-Haul Transport Trucks

The worldwide commitment to the electrification of road transport will require a broad overhaul of equipment and infrastructure. Heavy-duty trucks account for over one-third of on-road energy use. Electrified roadways (e-Hwys) are an emerging technology where electric vehicles receive electricity while driving via dynamic wireless power transfer (DWPT), which is becoming highly efficient, and can bypass the battery to directly serve the motor. A modeling study was undertaken to compare long-haul trucks on e-Hwys with conventional battery technology requiring off-road recharging to assess the most favorable pathway to electrification. Detailed data taken from on-road driving trips from five diesel transport trucks were obtained for this study. This on-road data provided the simulations with both real-life duty cycles as well as performance targets for electric trucks, enabling an assessment and comparison of their performance on e-Hwys or with fast recharging. Battery-only trucks were found to have lifetimes down to 60% original battery capacity (60% SOH) of up to 9 years with 1600 kWh packs, and were similar to conventional diesel truck performance. On e-Hwys smaller pack sizes in the 500 to 900 kWh capacity range were sufficient for the driving duty, and showed lifetimes upwards of 20 years, comparing favorably to the battery calendar life limit of about 26 years. For a 535 kWh battery pack, an e-Hwy DWPT level of 250 kW was sufficient for a 36 tonne truck to complete all the daily driving as defined by the diesel reference trucks, and reach a battery pack end of life point of 60% SOH.

Modeling e‐Truck adoption for sustainable transport in Jordan: A system dynamics approach

AbstractThis study has developed a model that predicts the quantity of CO2 emissions reduced and the adoption of e‐Trucks until the year 2100 in Jordan. Using system dynamics software (Powersim) and business intelligence tools (Microsoft Power BI), the most significant factors affecting three modules: environment, government, and customer were examined. Twelve scenarios were modeled during the study (three factors and four cases for each factor). The factors were marketing effectiveness, environmental awareness, and government acquisition subsidy, and their values were (0.2, 0.3, 0.4, 0.5), (0.3, 0.4, 0.5, 0.6), and (500, 1500, 3000, 6000 Jordanian Dinar—JOD), respectively. Under normal conditions, with a marketing effectiveness of 0.2, environmental awareness of 0.3, and a subsidy of 500 JOD, the annual sales of e‐Trucks and Conventional Fuel Trucks (CFT) will break‐even in 2052 in Jordan. The cumulative CO2 emissions reduction at the same year will be 6165.213 Tons. Among the three factors, marketing effectiveness was found to have the highest impact followed by the environmental awareness and last came the acquisition subsidy. Based on our findings, it is recommended that policymakers prioritize improving marketing efforts to accelerate the shift towards e‐Trucks, raise environmental awareness among consumers, and provide subsidies for acquisition of e‐Trucks in Jordan. Additionally, further research is needed to incorporate other factors, such as ICT infrastructure, technology maturity and other social factors that can affect the adoption of e‐Trucks. The study's originality lies in its focus on e‐Trucks, a relatively underexplored area in the sustainable transport literature, especially in the context of Jordan as many other emerging nations. The practical implications include leading the switch to e‐Trucks, identifying infrastructural needs, and informing legislative choices. By analyzing long‐term dynamics and encouraging the deployment of e‐Trucks, it seeks to lower CO2 emissions, enhance air quality, and promote a sustainable transportation system in Jordan.

Energy Consumption and Battery Size of Battery Trolley Electric Trucks in Surface Mines

Mining production, being one of the most energy-intensive industries globally, consumes substantial amounts of fossil fuels and contributes to extensive carbon emissions worldwide. The trend toward electrification and advanced developments in battery technology have shifted attention from diesel power to battery alternatives. These alternatives are appealing, as they contribute to decarbonisation efforts when compared to conventional diesel trucks. This paper presents a comprehensive review of recent technological advancements in powertrains for Mining Haulage Truck (MHT). It also compares these configurations based on mining system-level considerations to assess their future potential. The evaluated configurations include Diesel-Electric Truck (DET), Trolley Assist Truck (TAT), Battery-only Truck (BOT), Battery Trolley with Dynamic charging truck (BT-D), and Battery Trolley with Stationary charging truck (BT-S). According to the analysis, the energy demand for on-board diesel or battery power (excluding trolley power) in these alternative options is as follows: DET—681 kWh, BOT—645 kWh, TAT—511 kWh, BT-S—471 kWh, and BT-D—466 kWh. The paper also illustrates the theory of battery size design based on the current battery technology, battery material selection, battery package design, and battery size selection methods. In the case of tailored battery size selection, BOT, BT-D, and BT-S configurations require LiFePO4 (LFP) battery masses of 25 tonnes, 18 tonnes, and 18 tonnes, respectively. Based on a techno-economic assessment of battery MHT alternatives with a future perspective, it has been determined that BT-D requires the lowest amount of on-board battery energy. Furthermore, over a span of 20 years, BT-S has demonstrated the lowest on-board battery cost.

Levelized cost of driving for medium and heavy-duty battery electric trucks

The total cost of ownership (TCO) of trucks is known as one of the main decision-making factors by logistics operators for adopting alternative powertrains such as battery electric trucks (BETs). In this study, we develop a very detailed levelized cost of driving (LCOD) model to analyse the TCO of BETs and conventional trucks (CTs) in medium and heavy-duty truck weight classes. The model has methodological advancements such as developing opportunity costs for charging activities, using a detailed operational time calculation, and analysing the optimum driving ranges or battery sizing. By implementing an extensive sensitivity analysis of LCOD for CTs and BETs over 43 variables, it is revealed that the key parameters such as operational driving range, battery pack price, state of charge of battery, driver cost, “mid-shift” charging power, ambient temperature, opportunity charging, and driving speed have major impacts on the cost competitiveness of BETs vs. CTs. In addition, the impact of battery and charging technology improvements as well as designing optimum driving ranges are examined in three different operational trip profiles (urban, short-haul or regional, long-haul). The result shows that: 1) BETs in urban trip profiles with the current and/or short-term battery technology might be economically viable alternatives for CTs without the help of the policy measures, 2) BETs with below 40 t gross vehicle weight and the long-term improvements in battery technology in all the operational trip profiles might be economically viable alternatives for CTs without the help of the policy measures, and 3) the implementation of policy measures affecting the relative costs of CTs and BETs and development of fast-charging facilities would be needed to support the above 40 t BETs in short-haul and long-haul trips for the current and/or short-term as well as mid-term battery technologies.

Analysis of the aerodynamic performance of truck semi-trailers

In the last time, trucks have shown a very high interest in terms of their technical and fuel consumption performance. Prioritizing the phenomenon of having trucks that transport as much, as quickly and as economically as possible, this represent a new challenge for industry and engineering, which are in continuous development. The attempt to create a bridge as stable as possible between technical and consumer performance is supported by the multitude of areas that, based on studies and experimental trials, allow optimization without interfering, substantially, with the actual transport of the goods (loading capacities and transport). The main objective of this paper is to present the possibility of improving the aerodynamic performance of trucks, focusing on semi-trailers. For this study, a truck modelled at one to one scale was used, whose aerodynamic performance was verified in the virtual environment (CFD–Computational Fluid Dynamics); this environment has the possibility to test several geometric models without requiring the layout of a vehicle in physical form. To check the performance, a basic model was created, a conventional truck (tractor unit with semi-trailer), to which various semi-trailer modifications were made, such as: total and partial coverage of the side areas, idea to create a more aerodynamic profile of the semi-trailer in the back and the addition of fairings under the platform (underbody of the semi-trailer). The results describe the impact these elements have and allow the visualization of the possible future profile that is as aerodynamic as possible for semi-trailers (therefore also for trucks) from both theoretical and technical point of view. Through the proposed improvements the capacity and the transport of the goods is not affected, in a significant way so it can be said that there is the possibility of implementation in the industry.

What may automation cost? Activity-based costing for autonomous transport in urban logistics

A shift towards driverless vehicles in urban logistics will only happen if the use of the new technologies is economically beneficial. For this reason, this paper discusses the question of what autonomous shipment may cost in urban logistics. Using activity-based costing, the distinction between shipment with conventional trucks and autonomous transport robots is analysed. The calculation shows that the omission of the driver does not necessarily lead to a reduction of process costs. Only by also reducing technology costs, autonomous transport in urban logistics can gain economic benefits.

Load Profile Test Development and Analysis from Heavy Duty Truck Drive Cycles

On their way to their commercialisation, Fuel Cell Heavy Duty Trucks stakeholders need to demonstrate their cost effectiveness against conventional Diesel Trucks. Beyond the economies of scale of all relevant components that are employed in a Fuel Cell Electric Heavy Duty Truck, the durability of the Fuel Cell System and notably that of the Fuel Cell Stack plays an important role in the determination of a competitive cost of ownership.A key factor for durability improvement is the understanding of the degradation mechanisms and their mitigation. Degradation, however, can be very application specific, that is, different degradation mechanisms may be prevalent in heavy duty truck applications compared to passenger cars or stationary use. This is well known to research and industry.The European research project IMMORTAL is exactly aiming at exploring these mechanisms and their mitigation specifically for heavy duty truck application and developing and MEA that meets heavy duty requirements. Within this context, FPT Industrial, a brand of the Iveco Group, assists in defining the specific conditions met by Fuel Cell Stacks used in such powertrains.This presentation discusses how heavy duty truck load profiles can be extracted, how they may differ and how they may be assessed before they are used to define load profile tests (LPTs). It is also discussed how the results of such testing can be used to estimate degradation trends of the Fuel Cell and subsequently its durability and the cost of ownership of fuel cell trucks. The research leading to these results has received funding from the IMMORTAL project, which receives funding from the Fuel Cells and Hydrogen 2 Joint Undertaking (now Clean Hydrogen Partnership) under Grant Agreement No. 101006641. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation programme, Hydrogen Europe and Hydrogen Europe Research.

Enabling sustainable freight transport with longer, heavier vehicles in India

This groundbreaking study focuses on understanding the environmental impacts of longer, heavier vehicles (LHVs) in India's transportation system. Through a comprehensive life cycle assessment using the OpenLCA program and ecoinvent database, the research reveals that LHVs have lower negative life cycle impacts than conventional trucks. Increasing the modal share of LHVs by 40% in India's road freight transportation significantly reduces the overall environmental harm compared to the current freight transport mix. Additionally, the study demonstrates that even without market expansion, a 40% increase in LHVs' presence leads to a remarkable 12% reduction in global warming effects. The findings emphasize LHVs' potential as a sustainable and eco-friendly solution for India's freight transportation while highlighting the need for infrastructure development to capitalize on these benefits fully. Although the study acknowledges limitations related to data sources, it offers valuable insights into shaping a greener and more efficient transport system for the nation's future.

Who decides which trucks to buy? Implications for electrifying freight fleets

This study characterizes fleets’ decisions to operate medium- and heavy-duty fossil fuel-powered trucks and compares those decisions with fleets’ consideration of electric trucks. Based on interviews with decision-makers in 25 such organizations, we describe the social context of truck acquisition decision-making. We use concepts of organizational structure and external network heterogeneity to create a typology of decision-making. We use the typology to compare decisions regarding fleets’ actual and prospective consideration and use of conventional vs. electric trucks. The results describe who is involved in truck decision-making and provides insights into the organizational structures and external networks of fleets that have and those who have not acquired electric trucks. We identify fleet types that may require additional support to transition to electric trucks. This support may include connecting fleets with new or additional external actors to facilitate medium- and heavy-duty truck electrification.

Study on Resourceful Treatment and Carbon Reduction Intensity of Metro Shield Slag: An Example of a Tunnel Interval of Shenzhen Line 13

At present, the scale of subway construction in Chinese cities has reached a new height, and the shield slag produced by it has also surged year by year. Untreated subway shield slag not only occupies the space resources of the country, but also carries CO2, which causes negative impacts on the environment and which, as a result, is not conducive to the realization of the goal of the national “double-carbon” strategy. Therefore, how to effectively manage the shield slag produced by subway construction has become a scientific problem that needs to be solved urgently. In order to scientifically dispose of metro shield slag and quantify the carbon reduction intensity of its disposal, based on the new shield slag integrated recycling technology, and taking a tunnel interval of Shenzhen Line 13 as an example, this study systematically sorted out the shield slag disposal process, clarified the management path of the on-site resource utilization of slag, and quantitatively compared the carbon emissions before and after the treatment as well as carbon reduction intensity. The results show that the on-site disposal process is basically feasible, and that, it is possible to achieve a shield structure slag reduction of resource products and mud cake water content of less than 40% of the target, in the case of 160,000 m3 of shield structure slag resource utilization after a total carbon reduction of about 4240.13 t CO2, of which each preparation of 1 m3 of recycled bricks can bring about a benefit of carbon reduction of 240.09 kg CO2. Compared with the conventional mud head truck slag disposal, shield structure slag resource utilization can save a utilization cost of about 10.4 million yuan, meaning that, in terms of economic and social levels, this method can achieve good benefits. This case verifies the feasibility of the new technology, and the results of the study can provide experience for other metro projects’ shield slag resource utilization, and provide stakeholders with a shield slag recycling management strategy for government departments to scientifically formulate metro shield slag management policy to provide data support.

Lithium titanate battery system enables hybrid electric heavy-duty vehicles

Electrification plays an important role in the transformation of the global vehicle industry. Targeting the rapidly growing heavy-duty off-highway vehicles, we developed a battery system for hybrid-electric heavy-duty trucks based on lithium titanium oxide (LTO) batteries. With LTO as the anode and nickel manganese cobalt (NCM) as the cathode, comprehensive measurements of the battery cells and modules indicate that LTO batteries are uniquely suitable for applications requiring high-rate fast charging and discharging. An LTO battery system was constructed and implemented to realize the first advanced lithium-ion battery-based hybrid-electric heavy-duty vehicle, a hybrid-electric mining truck with vehicle mass 34 ton and maximum load 60 ton. Field operation tests of the hybrid-electric vehicle suggest that the performance of the LTO battery system meet the design expectations. After analyzing operation parameters of the hybrid-electric heavy-duty vehicle, we found 54.9 % fuel savings compared to conventional diesel-powered truck of the same mass and load.

A micro-economic model of the market uptake of truck platooning

Truck platooning is a technology allowing trucks to travel in convoy formation using wireless communications and advanced driver assistance systems. This technology is expected to increase road safety and capacity, and to decrease fuel consumption and GHG emissions; it comes with apparently important financial benefits and positive externalities. However, forecasting the market uptake of platooning is a complex economic issue, requiring a dedicated methodology.From a micro-economic standpoint, several features of truck platooning are important. First, forming a platoon implies a coordination cost. Second, platooning requires trucks with specific and costly equipment. That makes platooning a two-layer problem. Third, the decision of one carrier depends on those of other carriers: truck platooning, as a market, is characterized with network externalities. Fourth, road freight transportation is a heterogeneous system: different vehicles follow different operation patterns.This paper submits a micro-economic model of the uptake of platooning which accounts for all of the above points. First, a conditional sub-model of platoon formation is designed, where two trucks decide whether to form a platoon or not based on the net monetary benefits of doing so. Then, platoon formation is modeled in a simplified, single road context, as a Markov chain. At that stage, the share of platoonable trucks entering the market is obtained with a numerical, dynamic model. Upgrading conventional trucks to become compatible with platooning is assumed impossible.The paper concludes that due to the positive feedback loop of network externalities, market uptake is very sensitive to the economic assumptions. In addition, due to the equipment and coordination costs induced by platooning, the overall financial benefits for carriers are much lower than what they would initially appear to be; third, energy savings can be significant on the long run if the technology spreads widely.

Accelerating electric vehicle charging investments: A real options approach to policy design

Replacing conventional cars and trucks with battery electric vehicles requires a rapid expansion of fast-charging infrastructure. However, private sector charging infrastructure investments are delayed by unfavorable project economics and uncertainty in future demand. Prior research has addressed the former using standard net present value (NPV) methods, but neglected the latter. To address this gap, this paper introduces a real options model of charging investments, which quantifies the option value of delaying investment under uncertainty. We use this model to assess the implications of optionality in a representative case. Our analysis provides indicative estimates of how investment timing is impacted by alternative policy options: grants, long-term contracts, demand charge re-design, and Zero Emission Vehicle standards. We estimate that if grant subsidies are informed by a traditional NPV analysis, firms would delay investing by more than 5 years. Perhaps surprisingly, even low levels of risk incentivize long delays. We find that policies targeting optionality are substantially more cost-effective than the traditionally used grants. Specifically, we calculate that long-term contracts for differences can trigger immediate investments at a cost 68% lower than grants. A simpler but relatively cost-effective alternative is to introduce a phase-out schedule for grants to discourage investment delays.

Feasibility of Battery Electric Pickup Trucks in a State Department of Transportation Fleet

Vehicle manufacturers are beginning to introduce battery electric pickup trucks, with at least three models in production in the United States and at least six others announced. Unlike hybrid and plug-in hybrid vehicles, which use batteries to supplement an internal combustion engine, battery electric vehicles are fully reliant on their batteries and have significantly shorter ranges, fewer refueling/recharging options, and may experience shorter ranges under towing, mountain driving, and temperature extremes. This study investigated real-world pickup truck usage data from a large state department of transportation to determine whether battery electric trucks could effectively replace trucks based on manufacturer-stated range as well as early field tests of actual vehicle range under various speeds, idling scenarios, and weather conditions. The results indicated that 97% of pickup truck day trips could be completed on a standard range battery, and 99% on an extended range battery. Among tracked department of transportation fleet pickup trucks, 31% could be replaced by a standard range electric truck with no change in operation; and up to 64% of the fleet with an extended range could be replaced by an extended range electric truck. Dynamically assigning long trips to dedicated conventional engine pickup trucks could further reduce the number of nonelectric trucks required by half.