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Turbulence is known to influence the aerodynamic and aeroacoustic performance of ground vehicles. What is not thoroughly understood are the characteristics of turbulence that influence this performance and how they can be applied in a consistent manner for aerodynamic design and evaluation purposes. Through collaboration between Transport Canada and the National Research Council Canada (NRC), a project was undertaken to develop a system for generating road-representative turbulence in the NRC 9 m Wind Tunnel, named the Road Turbulence System (RTS). This endeavour was undertaken in support of a larger project to evaluate new and emerging drag reduction technologies for heavy-duty vehicles. A multi-stage design process was used to develop the RTS for use with a 30% scale model of a heavy-duty vehicle in the NRC 9m Wind Tunnel.

In North America, heavy-duty diesel engines for on-road use have to meet strict regulations for their emissions of nitric oxide and nitrogen dioxide (cumulatively referred to as ‘NOx’) besides other criteria pollutants. Over the next decade, regulations for NOx emissions are expected to becoming more stringent in North America. One of the major technical barriers for achieving in-use NOx emissions commensurate with the levels determined from in-laboratory test procedures required by regulations is controlling NOx emissions during cold start and engine idling. Since the exhaust gas temperature can be low during these conditions, the effectiveness of the exhaust after-treatment (EAT) system may be reduced. Under colder climate conditions like in Canada, the impact may be even more significant.

Previous studies have shown that regenerating particulate filters are very effective at reducing particulate matter emissions from diesel engines. Some particulate filters are passive devices that can be installed in place of the muffler on both new and older model diesel engines. These passive devices could potentially be used to retrofit large numbers of trucks and buses already in service, to substantially reduce particulate matter emissions. Catalyst-type particulate filters must be used with diesel fuels having low sulfur content to avoid poisoning the catalyst. A project has been launched to evaluate a truck fleet retrofitted with two types of passive particulate filter systems and operating on diesel fuel having ultra-low sulfur content. The objective of this project is to evaluate new particulate filter and fuel technology in service, using a fleet of twenty Class 8 grocery store trucks. This paper summarizes the truck fleet start-up experience.

NREL completed a temporal and geospatial analysis of telematics data to estimate the fraction of platoonable miles traveled by class 8 tractor trailers currently in operation. This paper discusses the value and limitations of very large but low time-resolution data sets, and the fuel consumption reduction opportunities from large scale adoption of platooning technology for class 8 highway vehicles in the US based on telematics data. The telematics data set consist of about 57,000 unique vehicles traveling over 210 million miles combined during a two-week period. 75% of the total fuel consumption result from vehicles operating in top gear, suggesting heavy highway utilization. The data is at a one-hour resolution, resulting in a significant fraction of data be uncategorizable, yet significant value can still be extracted from the remaining data. Multiple analysis methods to estimate platoonable miles are discussed.

Transport Canada, through its ecoTECHNOLOGY for Vehicles program, retained the services of the National Research Council Canada to undertake a test program to examine the operational and human factors considerations concerning the removal of the side mirrors on a Class 8 tractor equipped with a 53 foot dry van semi-trailer. Full scale aerodynamic testing was performed in a 2 m by 3 m wind tunnel on a system component basis to quantify the possible fuel savings associated with the removal of the side mirrors. The mirrors on a Volvo VN780 tractor were removed and replaced with a prototype camera-based indirect vision system consisting of four cameras mounted in the front fender location; two cameras on either side of the vehicle. Four monitors mounted in the vehicle - two mounted on the right A-pillar and two mounted on the left A-pillar - provided indirect vision information to the vehicle operator.

Heavy-duty commercial vehicles consume a significant amount of energy due to their large size and mass, directly leading to vehicle operators prioritizing energy efficiency to reduce operational costs and comply with environmental regulations. One tool that can be used for the evaluation of energy efficiency in heavy-duty vehicles is the evaluation of energy efficiency using vehicle modeling and simulation. Simulation provides a path for energy efficiency improvement by allowing rapid experimentation of different vehicle characteristics on fuel consumption without the need for costly physical prototyping. The research presented in this paper focuses on using real-world, sparsely sampled telematics data from a large fleet of heavy-duty vehicles to create high-fidelity models for simulation. Samples in the telematics dataset are collected sporadically, resulting in sparse data with an infrequent and irregular sampling rate.

Diesel-fueled heavy-duty vehicles (HDVs) can be retrofitted with conversion kits to operate as dual-fuel vehicles in which partial diesel usage is offset by a gaseous fuel such as compressed natural gas (CNG). The main purpose of installing such a conversion kit is to reduce the operating cost of HDVs. Additionally, replacing diesel partially with a low-carbon fuel such as CNG can potentially lead to lower carbon dioxide (CO2) emissions in the tail-pipe. The main issue of CNG-diesel dual-fuel vehicles is the methane (CH4, the primary component of CNG) slip. CH4 is difficult to oxidize in the exhaust after-treatment (EAT) system and its slip may offset the advantage of lower CO2 emissions of natural gas combustion as CH4 is a strong greenhouse gas (GHG). The objective of this study is to compare the emissions of an HDV with a CNG conversion kit operating in diesel and dual-fuel mode during highway operation.

A truck platooning system was tested using two heavy-duty tractor-trailer trucks on a closed test track to investigate the thermal control/heat rejection system sensitivity to intentional lateral offsets over a range of intervehicle spacings. Previous studies have shown the following vehicle can experience elevated temperatures and reduced airflow through the cooling package as a result of close-formation platooning. Four anemometers positioned across the grille of the following trucks as well as aligned and multiple offset positions are used to evaluate the sensitivity of the impact. Straight sections of the track are isolated for the most accurate airflow impact measurements and to be most representative of on-highway driving. An intentional lateral offset in truck platooning is considered as a controls approach to mitigate reduced cooling efficacy at close following scenarios where the highest platoon savings are achieved.

We investigate tradeoffs between the airflow strategies related to engine cooling and the aerodynamic-enabled fuel savings created by platooning. By analyzing air temperatures, engine temperatures and cooling air flow at different platoon distances, we show the thermal impact to the engine from truck platooning. Previously, we collected wind and thermal data for numerous heavy-duty truck platoon configurations (gaps ranging from 4 to 87 meters) and reported the significant fuel savings enabled by these configurations. The fuel consumption for all trucks in the platoon were measured using the SAE J1321 gravimetric procedure as well as calibrated J1939 instantaneous fuel rate while travelling at 65 mph and loaded to a gross weight of 65,000 lb.

The influence of fuel aromatics type on the particulate matter (PM) and NOx exhaust emissions of a heavy-duty, single-cylinder, DI diesel engine was investigated. Eight fuels were blended from conventional and oil sands crude oil sources to form five fuel pairs with similar densities but with different poly-aromatic (1.6 to 14.6%) or total aromatic (14.3 to 39.0%) levels. The engine was tuned to meet the U.S. EPA 1994 emission standards. An eight-mode, steady-state simulation of the U.S. EPA heavy-duty transient test procedure was followed. The experimental results show that there were no statistically significant differences in the PM and NOx emissions of the five fuel pairs after removing the fuel sulphur content effect on PM emissions. However, there was a definite trend towards higher NOx emissions as the fuel density, poly-aromatic and total aromatic levels of the test fuels increased.

Annual fuel use for sleeper cab truck rest period idling is estimated at 667 million gallons in the United States, or 6.8% of long-haul truck fuel use. Truck idling during a rest period represents zero freight efficiency and is largely done to supply accessory power for climate conditioning of the cab. The National Renewable Energy Laboratory’s CoolCab project aims to reduce heating, ventilating, and air conditioning (HVAC) loads and resulting fuel use from rest period idling by working closely with industry to design efficient long-haul truck thermal management systems while maintaining occupant comfort. Enhancing the thermal performance of cab/sleepers will enable smaller, lighter, and more cost-effective idle reduction solutions. In addition, if the fuel savings provide a one- to three-year payback period, fleet owners will be economically motivated to incorporate them.

This paper presents multiple methods for predicting heavy/medium-duty vehicle fuel consumption based on driving cycle information. A polynomial model, a black box artificial neural net model, a polynomial neural network model, and a multivariate adaptive regression splines (MARS) model were developed and verified using data collected from chassis testing performed on a parcel delivery diesel truck operating over the Heavy Heavy-Duty Diesel Truck (HHDDT), City Suburban Heavy Vehicle Cycle (CSHVC), New York Composite Cycle (NYCC), and hydraulic hybrid vehicle (HHV) drive cycles. Each model was trained using one of four drive cycles as a training cycle and the other three as testing cycles. By comparing the training and testing results, a representative training cycle was chosen and used to further tune each method.

Battery electric vehicles possess great potential for decreasing lifecycle costs in medium-duty applications, a market segment currently dominated by internal combustion technology. Characterized by frequent repetition of similar routes and daily return to a central depot, medium-duty vocations are well positioned to leverage the low operating costs of battery electric vehicles. Unfortunately, the range limitation of commercially available battery electric vehicles acts as a barrier to widespread adoption. This paper describes the National Renewable Energy Laboratory's collaboration with the U.S. Department of Energy and industry partners to analyze the use of small hydrogen fuel-cell stacks to extend the range of battery electric vehicles as a means of improving utility, and presumably, increasing market adoption.

With increasing use of boat-tails on Canadian roads, a concern had been raised regarding the possibility for ice and snow to accumulate and shed from the cavity of a boat-tail affixed to a dry-van trailer, posing a hazard for other road users. This paper describes a preliminary evaluation of the potential for ice and snow accumulation in the cavity of a boat-tail-equipped heavy-duty vehicle. A transient CFD approach was used and combined with a quasi-static particle-tracking simulation to evaluate, firstly, the tendency of various representative ice or snow particles to be entrained in the vehicle wake, and secondly, the potential of such particles to accumulate on the aft end of a dry-van trailer with and without various boat-tail configurations. Results of the particle tracking analyses showed that the greatest numbers of particles impinge on the base of the trailer for the no-boat-tail case, concentrated on the upper surface of the back face of the trailer.

The National Renewable Energy Laboratory's (NREL's) Fleet Test and Evaluations team recently conducted chassis dynamometer tests of a class 8 conventional regional delivery truck over the Heavy Heavy-Duty Diesel Truck (HHDDT), West Virginia University City (WVU City), and Composite International Truck Local and Commuter Cycle (CILCC) drive cycles. A quantitative study analyzed the impacts of various factors on fuel consumption (FC) and fuel economy (FE) by modeling and simulating the truck using NREL's Future Automotive Systems Technology Simulator (FASTSim). Factors included vehicle weight and the coefficients of rolling resistance and aerodynamic drag. Simulation results from a single parametric study revealed that FC was approximately a linear function of the weight, coefficient of aerodynamic drag, and rolling resistance over various drive cycles.

Annual fuel use for long-haul truck rest period idling is estimated at 667 million gallons in the United States. The U.S. Department of Energy's National Renewable Energy Laboratory's CoolCab project aims to reduce heating, ventilating, and air conditioning (HVAC) loads and resulting fuel use from rest period idling by working closely with industry to design efficient long-haul truck climate control systems while maintaining occupant comfort. Enhancing the thermal performance of cab/sleepers will enable smaller, lighter, and more cost-effective idle reduction solutions. In order for candidate idle reduction technologies to be implemented at the original equipment manufacturer and fleet level, their effectiveness must be quantified. To address this need, a number of promising candidate technologies were evaluated through experimentation and modeling to determine their effectiveness in reducing rest period HVAC loads.