Experimental Fuel Consumption Results from a Heterogeneous Four-Truck Platoon

Stegner, Evan; Ward, Jacob; Siefert, Jan; Hoffman, Mark; Bevly, David M.

doi:10.4271/2021-01-0071

Cited by 6 publications

(2 citation statements)

References 17 publications

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“…Multiple studies have shown that platooning can reduce the fuel consumption of LHTs between 4% and 17%, specifically for the following truck. Platooning has a lower impact on reducing the drag coefficient of the lead truck, resulting in a comparatively smaller FE improvement compared to the following trucks, typically ranging between zero and 5% [100][101][102][103]. The drag coefficient of the following truck decreases with shorter separation from the lead truck, but road safety and braking are limiting factors for the inter-vehicle distance [104][105][106][107].…”

Section: Vehicle Side Technologiesmentioning

confidence: 99%

Advances in Vehicle and Powertrain Efficiency of Long-Haul Commercial Vehicles: A Review

Balazadeh Meresht,

Moghadasi,

Munshi

et al. 2023

Energies

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Mitigating CO2 emissions from long-haul commercial trucking is a major challenge that must be addressed to achieve substantial reductions in greenhouse gas (GHG) emissions from the transportation sector. Extensive recent research and development programs have shown how significant near-term reductions in GHGs from commercial vehicles can be achieved by combining technological advances. This paper reviews progress in technology for engine efficiency improvements, vehicle resistance and drag reductions, and the introduction of hybrid electric powertrains in long-haul trucks. The results of vehicle demonstration projects by major vehicle manufacturers have shown peak brake thermal efficiency of 55% in heavy-duty diesel engines and have demonstrated freight efficiency improvements of 150% relative to a 2009 baseline in North America. These improvements have been achieved by combining multiple incremental improvements in both engine and vehicle technologies. Powertrain electrification through hybridization has been shown to offer some potential reductions in fuel consumption. These potential benefits depend on the vehicle use, the details of the powertrain design, and the duty cycle. To date, most papers have focused on standard drive cycles, leaving a research gap in how hybrid electric powertrains would be designed to minimize fuel consumption over real-world drive cycles, which are essential for a reliable powertrain design. The results of this paper suggest that there is no “one-size-fits-all” solution to reduce the GHGs in long-haul trucking, and a combination of technologies is required to provide an optimum solution for each application.

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Section: Vehicle Side Technologiesmentioning

confidence: 99%

Advances in Vehicle and Powertrain Efficiency of Long-Haul Commercial Vehicles: A Review

Balazadeh Meresht,

Moghadasi,

Munshi

et al. 2023

Energies

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show abstract

“…In platooning systems, the separation between vehicles is a key factor influencing fuel consumption. Previous studies have used both wind tunnel and field experiments to investigate strategies for fuel savings in platooning vehicles [21][22][23][24][25][26]. Field experiments provide a precise experimental environment that allows for repetitive testing.…”

Section: Introductionmentioning

confidence: 99%

Impact of Platooning on Fuel Consumption in Heavy-Duty Vehicles: A Computational Fluid Dynamics Modeling Approach

Kim,

Kang,

Hwang

et al. 2024

Preprint

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Platooning represents a crucial strategy for mitigating emissions from heavy-duty vehicles (HDVs). This study evaluates the effects of platoon composition on the surrounding airflow utilizing a computational fluid dynamics (CFD) model, and quantifies the resultant fuel efficiency and CO2 emissions. This study examines fuel consumption data reconstructed from field experiments to validate the CFD model’s ability to accurately simulate drag forces within a homogeneous three-truck platoon. The potential for fuel savings was assessed based on CFD-simulated fuel consumption, taking into account various inter-vehicle distances and driving speeds. The model successfully reproduced the fuel consumption observed in a platooning formation comprising lead, middle, and trailing trucks, with an error margin below 6.2%. While the lead and middle trucks exhibited increased fuel consumption with greater inter-vehicle distances, the trailing truck showed decreased fuel consumption with specific distance-to-length ratios (D/L), followed by an increase from a D/L of 1.1. Additionally, a significant decrease in total fuel efficiency was noted for D/L ratios exceeding 1.5. Considering the diverse platooning scenarios analyzed, the study anticipates an annual reduction of up to 7 tons of CO2 equivalent per vehicle. By optimizing platooning configurations, this research contributes to enhancing fuel efficiency and reducing emissions from HDVs.

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Developing Fuel Savings Performance Function Considering Various Truck Platooning Configurations

Mohamed,

Hassan

2024

Fuels and Lubricants

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<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>

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Experimental Fuel Consumption Results from a Heterogeneous Four-Truck Platoon

Cited by 6 publications

References 17 publications

Advances in Vehicle and Powertrain Efficiency of Long-Haul Commercial Vehicles: A Review

Advances in Vehicle and Powertrain Efficiency of Long-Haul Commercial Vehicles: A Review

Impact of Platooning on Fuel Consumption in Heavy-Duty Vehicles: A Computational Fluid Dynamics Modeling Approach

Developing Fuel Savings Performance Function Considering Various Truck Platooning Configurations

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