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Diesel Cylinder Deactivation (CDA) has been shown in previous work to increase exhaust temperatures, improve fuel efficiency, and reduce engine-out NOx for engine loads up to 3 bar BMEP. The purpose of this study is to determine whether or not the turbocharger needs to be altered when implementing CDA on a diesel engine. This study investigates the effect of CDA on exhaust temperature, fuel efficiency, and turbocharger performance in a 15L heavy-duty diesel engine under low-load (0-3 bar BMEP) steady-state operating conditions. Two calibration strategies were evaluated. First, a “stay-hot” thermal management strategy in which CDA was used to increase exhaust temperature and reduce fuel consumption. Next, a “get-hot” strategy where CDA and elevated idle speed was used to increase exhaust temperature and exhaust enthalpy for rapid aftertreatment warm-up.

Over twenty prototype hybrid buses and other commercial vehicles are currently being completed and deployed. These vehicles are primarily “series” hybrid vehicles which use electric motors for primary traction while internal combustion engines, or high-speed turbine engines connected to generators, supply some portion of the electric propulsion and battery recharge energy. Hybrid-electric vehicles have an electric energy storage system on board that influences the operation of the heat engine. The storage system design and level affect the vehicle emissions, electricity consumption, and fuel economy. Existing heavy-duty emissions test procedures require that the engine be tested over a transient cycle before it can be used in vehicles (over 26,000 lbs GVW). This paper describes current test procedures for assessing engine and vehicle emissions, and proposes techniques for evaluating engines used with hybrid-electric vehicle propulsion systems.

The U.S. Army's National Automotive Center has contracted with Illinois Institute of Technology Research Institute (IITRI), Southwest Research Institute (SwRI), and Advanced Propulsion, LLC, to evaluate the effects on fuel consumption and logistics that would result from hybridizing the powertrains of the Army's tactical wheeled vehicle fleet. This paper will outline the approach taken to perform that evaluation and present a synopsis of results achieved to date.

Road tests of class 8 tractor trailers were conducted by the US Environmental Protection Agency (EPA) on a new and retreaded tires of varying rolling resistance in order to provide estimates of the quantitative relation between rolling resistance and fuel consumption. Reductions in fuel consumption were measured using the SAE J1231 (reaffirmation of 1986) test method. Vehicle rolling resistance was calculated as a load-weighted average of the rolling resistance (as measured by ISO28580) of the tires in each axle position. Both new and retreaded tires were tested in different combinations to obtain a range of vehicle coefficient of rolling resistance from a baseline of 7.7 kg/ton to 5.3 kg/ton. Reductions in fuel consumption displayed a strong linear relationship with coefficient of rolling resistance, with a maximum reduction of fuel consumption of 10 percent relative to the baseline.

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.

An Automatic Tire Inflation System (ATIS), specifically designed for use on commercial long haul trailers, requires modification of the axles to direct air to the tires. The ATIS requires a drilled hole through the axle tube for the installation of a pneumatic fitting. The trucking industry expressed concern about the modification and its impact upon the axle structure, and the general durability of the system over a long period. A three-phase test program was developed and conducted to satisfy the concerns of the industry.

Smart technologies enabling connection among vehicles and between vehicles and infrastructure as well as vehicle automation to assist human operators are receiving significant attention as a means for improving road transportation systems by reducing fuel consumption – and related emissions – while also providing additional benefits through improving overall traffic safety and efficiency. For truck applications, which are currently responsible for nearly three-quarters of the total U.S. freight energy use and greenhouse gas (GHG) emissions, platooning has been identified as an early feature for connected and automated vehicles (CAVs) that could provide significant fuel savings and improved traffic safety and efficiency without radical design or technology changes compared to existing vehicles. A statistical analysis was performed based on a large collection of real-world U.S. truck usage data to estimate the fraction of total miles that are technically suitable for platooning.

To reach its objective of reducing vehicle fuel consumption by 50 percent, the development of the 21st Century Truck (21T) will address all the aspects of truck design contributing to the achievement of that goal. [1] This paper will address one of these aspects, specifically vehicle parasitic loss reduction with special emphasis on drive train losses, concentrating on the potential benefits of replacing mechanical coolant (water) and oil pumps with electrically powered pumps.

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.

As fuel economy becomes increasingly important in all markets, complete engine system optimization is required to meet future standards. In many applications, it is difficult to realize the optimum coolant or lubricant pump without first evaluating different sets of engine hardware and iterating on the flow and pressure requirements. For this study, a Heavy Duty Diesel (HDD) engine was run in a dynamometer test cell with full variability of the production coolant and lubricant pumps. Two test stands were developed to allow the engine coolant and lubricant pumps to be fully mapped during engine operation. The pumps were removed from the engine and powered by electric motors with inline torque meters. Each fluid circuit was instrumented with volume flow meters and pressure measurements at multiple locations. After development of the pump stands, research efforts were focused on hardware changes to reduce coolant and lubricant flow requirements of the HDD engine.

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.

A simulation framework with a validated system model capable of estimating fuel consumption is a valuable tool in analysis and design of the hybrid vehicles. In particular, the framework can be used for (1) benchmarking the fuel economy achievable from alternate hybrid powertrain technologies, (2) investigating sensitivity of fuel savings with respect to design parameters (for example, component sizing), and (3) evaluating the performance of various supervisory control algorithms for energy management. This paper describes such a simulation framework that can be used to predict fuel economy of series hydraulic hybrid vehicle for any specified driver demand schedule (drive cycle), developed in MATLAB/Simulink. The key components of the series hydraulic hybrid vehicle are modeled using a combination of first principles and empirical data. A simplified driver model is included to follow the specified drive cycle.

This paper presents the results of engine and vehicle simulation modeling for a wide variety of individual technologies and technology packages applied to two medium-duty vocational vehicles. Simulation modeling was first conducted on one diesel and two gasoline medium-duty engines. Engine technologies were then applied to the baseline engines. The resulting fuel consumption maps were run over a range of vehicle duty cycles and payloads in the vehicle simulation model. Results were reported for both individual engine technologies and combinations or packages of technologies. Two vehicles, a Kenworth T270 box delivery truck and a Ford F-650 tow truck were evaluated. Once the baseline vehicle models were developed, vehicle technologies were added. As with the medium-duty engines, vehicle simulation results were reported for both individual technologies and for combinations. Vehicle technologies were evaluated only with the baseline 2019 diesel medium-duty engine.

This paper presents a discussion on manual transmission torque losses and focuses specifically on the relationship between torque loss, input speed and torque. It also includes a discussion on other factors affecting torque loss, such as inclination angle and lube oil temperature. Manual transmissions used in compact light truck applications have torque losses that are a function of input speed and torque. Efficiency studies done on manual transmissions in the engine-driving mode indicate that torque losses, in other than direct-drive gears, are considerably more dependent on input torque than input speed. It was also observed that efficiency was significantly affected by the inclination angle and lube oil temperature.

This paper reviews the technologies available for Bharat Stage 3 and 4 Heavy Duty on-highway emissions standards. Benchmarking data from several existing engines is used to explore the trade-offs between engine/vehicle cost and fuel consumption. Other implications of the available technologies, such as durability / reliability requirements, are also addressed. The paper provides recommendations for low cost approaches to meeting Bharat Stage 3 and 4 standards with good fuel consumption and reliability/ durability characteristics. A brief look ahead to future Bharat Stage 5 requirements is also provided.

The objective of this project was to assess the effects of various blends of biodiesel on locomotive engine exhaust emissions. Systematic, credible, and carefully designed and executed locomotive fuel effect studies produce statistically significant conclusions are very scarce, and only cover a very limited number of locomotive models. Most locomotive biodiesel work has been limited to cursory demonstration programs. Of primary concern to railroads and regulators is understanding any exhaust emission associated with biodiesel use, especially NOX emissions. In this study, emissions tests were conducted on two locomotive models, a Tier 2 EMD SD70ACe and a Tier 1+ GE Dash9-44CW with two baseline fuels, conventional EPA ASTM No. 2-D S15 (commonly referred to as ultra-low sulfur diesel - ULSD) certification diesel fuel, and commercially available California Air Resource Board (CARB) ULSD fuel.

An integrated adaptive cruise control (ACC) and cooperative ACC (CACC) was implemented and tested on three heavy-duty tractor-trailer trucks on a closed test track. The first truck was always in ACC mode, and the followers were in CACC mode using wireless vehicle-vehicle communication to augment their radar sensor data to enable safe and accurate vehicle following at short gaps. The fuel consumption for each truck in the CACC string was measured using the SAE J1321 procedure while travelling at 65 mph and loaded to a gross weight of 65,000 lb, demonstrating the effects of: inter-vehicle gaps (ranging from 3.0 s or 87 m to 0.14 s or 4 m, covering a much wider range than previously reported tests), cut-in and cut-out maneuvers by other vehicles, speed variations, the use of mismatched vehicles (standard trailers mixed with aerodynamic trailers with boat tails and side skirts), and the presence of a passenger vehicle ahead of the platoon.

This study compared fuel economy and emissions between heavy-duty hybrid electric vehicles (HEVs) and equivalent conventional diesel vehicles. In-use field data were collected from daily fleet operations carried out at a FedEx facility in California on six HEV and six conventional 2010 Freightliner M2-106 straight box trucks. Field data collection primarily focused on route assessment and vehicle fuel consumption over a six-month period. Chassis dynamometer testing was also carried out on one conventional vehicle and one HEV to determine differences in fuel consumption and emissions. Route data from the field study was analyzed to determine the selection of dynamometer test cycles. From this analysis, the New York Composite (NYComp), Hybrid Truck Users Forum Class 6 (HTUF 6), and California Air Resource Board (CARB) Heavy Heavy-Duty Diesel Truck (HHDDT) drive cycles were chosen.

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.

A two-truck platoon based on a prototype cooperative adaptive cruise control (CACC) system was tested on a closed test track in a variety of realistic traffic and transient operating scenarios - conditions that truck platoons are likely to face on real highways. The fuel consumption for both trucks in the platoon was measured using the SAE J1321 gravimetric procedure as well as calibrated J1939 instantaneous fuel rate, serving as proxies to evaluate the impact of aerodynamic drag reduction under constant-speed conditions. These measurements demonstrate the effects of: the presence of a multiple-passenger-vehicle pattern ahead of and adjacent to the platoon, cut-in and cut-out manoeuvres by other vehicles, transient traffic, the use of mismatched platooned vehicles (van trailer mixed with flatbed trailer), and the platoon following another truck with adaptive cruise control (ACC).