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We compare the simulated fuel economy and emissions for both conventional and hybrid class 8 heavy-duty diesel trucks operating over multiple urban and highway driving cycles. Both light and heavy freight loads were considered, and all simulations included full aftertreatment for NOx and particulate emissions controls. The aftertreatment components included a diesel oxidation catalyst (DOC), urea-selective catalytic NOx reduction (SCR), and a catalyzed diesel particulate filter (DPF). Our simulated hybrid powertrain was configured with a pre-transmission parallel drive, with a single electric motor between the clutch and gearbox. A conventional heavy duty (HD) truck with equivalent diesel engine and aftertreatment was also simulated for comparison. Our results indicate that hybridization can significantly increase HD fuel economy and improve emissions control in city driving. However, there is less potential benefit for HD hybrid vehicles during highway driving.

This paper summarizes initial results and findings of a model developed to determine the braking performance of commercial motor vehicles in motion regardless of brake type or gross weight. Real-world data collected by Oak Ridge National Laboratory for a U.S. Department of Energy study was used to validate the model. Expanding on previous proof-of-concept research showing the linear relationship of brake application pressure and deceleration additional parameters such as elevation were added to the model. Outputs from the model consist of coefficients calculated for every constant pressure braking event from a vehicle that can be used to calculate a deceleration and thus compute a stopping distance for a given scenario. Using brake application pressure profiles derived from the dataset, stopping distances for light and heavy loads of the same vehicle were compared for various speed and road grades.

The development of a future hydrogen energy economy will require the development of several hydrogen market and industry segments including a hydrogen based commercial freight transportation ecosystem. For a sustainable freight transportation ecosystem, the supporting fueling infrastructure and the associated vehicle powertrains making use of hydrogen fuel will need to be co-established. This paper develops a long-term plan for refueling infrastructure deployment using the OR-AGENT (Optimal Regional Architecture Generation for Electrified National Transportation) tool developed at the Oak Ridge National Laboratory, which has been used to optimize the hydrogen refueling infrastructure requirements on the I-75 corridor for heavy duty (HD) fuel cell electric commercial vehicles (FCEV).

The phenomena of global warming and climate change are encouraging more and more countries, local communities, and companies to establish carbon neutrality targets, which has very significant implications for the US trucking industry. Truck electrification helps fleets to achieve zero tailpipe emissions and macro-scale decarbonization while allowing continued business growth in response to the rapid expansion of e-commerce and shipping related to increased globalization. This paper presents an analysis of Class 8 long-haul truck electrification using a commercial vehicle electrification evaluation tool and Fleet DNA drive data. The study provides new insight into the impacts of streamlined chassis, battery energy density, and superfast charging on battery capacity needs as well as implications for payload, energy consumption, and greenhouse gas emissions for electric long-haul trucks. The study also identifies a pathway for achieving optimal long-haul truck electrification.

For renewable fuels to displace petroleum, they must be compatible with emissions control devices. Pure biodiesel contains up to 5 ppm Na + K and 5 ppm Ca + Mg metals, which have the potential to degrade diesel emissions control systems. This study aims to address these concerns, identify deactivation mechanisms, and determine if a lower limit is needed. Accelerated aging of a production exhaust system was conducted on an engine test stand over 1001 h using 20% biodiesel blended into ultra-low sulfur diesel (B20) doped with 14 ppm Na. This Na level is equivalent to exposure to Na at the uppermost expected B100 value in a B20 blend for the system full-useful life. During the study, NOx emissions exceeded the engine certification limit of 0.33 g/bhp-hr before the 435,000-mile requirement.

The US Department of Energy’s Co-Optimization of Engine and Fuels Initiative (Co-Optima) investigated how unique properties of bio-blendstocks considered within Co-Optima help address emissions challenges with mixing controlled compression ignition (i.e., conventional diesel combustion) and enable advanced compression ignition modes suitable for implementation in a diesel engine. Additionally, the potential synergies of these Co-Optima technologies in hybrid vehicle applications in the medium- and heavy-duty sector was also investigated. In this work, vehicles system were simulated using the Autonomie software tool for quantifying the benefits of Co-Optima engine technologies for medium-duty trucks. A Class 6 delivery truck with a 6.7 L diesel engine was used for simulations over representative real-world and certification drive cycles with four different powertrains to investigate fuel economy, criteria emissions, and performance.

An engine-aftertreatment computational model was developed to support in-loop performance simulations of tailpipe emissions and fuel consumption associated with a range of heavy-duty (HD) truck drive cycles. For purposes of this study, the engine-out exhaust dynamics were simulated with a combination of steady-state engine maps and dynamic correction factors that accounted for recent engine operating history. The engine correction factors were approximated as dynamic first-order lags associated with the thermal inertia of the major engine components and the rate at which engine-out exhaust temperature and composition vary as combustion heat is absorbed or lost to the surroundings. The aftertreatment model included catalytic monolith components for diesel exhaust oxidation, particulate filtration, and selective catalytic reduction of nitrogen oxides (NOx) with urea.

Greenhouse gas regulations and global economic growth are expected to drive a future demand shift towards diesel fuel in the transportation sector. This may create a market opportunity for cost-effective fuels in the light distillate range if they can be burned as efficiently and cleanly as diesel fuel. In this study, the emission performance of a low cetane number, low research octane number naphtha (CN 34, RON 56) was examined on a production 6-cylinder heavy-duty on-highway truck engine and aftertreatment system. Using only production hardware, both the engine-out and tailpipe emissions were examined during the heavy-duty emission testing cycles using naphtha and ultra-low-sulfur diesel (ULSD) fuels. Without any modifications to the hardware and software, the tailpipe emissions were comparable when using either naphtha or ULSD on the heavy duty test cycles.

Eco-Approach and Departure (EAD) has been considered as a promising eco-driving strategy for vehicles traveling in an urban environment, where information such as signal phase and timing (SPaT) and geometric intersection description is well utilized to guide vehicles passing through intersections in the most energy-efficient manner. Previous studies formulated the optimal trajectory planning problem as finding the shortest path on a graphical model. While this method is effective in terms of energy saving, its computation efficiency can be further enhanced by adopting machine learning techniques. In this paper, we propose an innovative deep learning-based queue-aware eco-approach and departure (DLQ-EAD) system for a plug-in hybrid electric bus (PHEB), which is able to provide an online optimal trajectory for the vehicle considering both the downstream traffic condition (i.e. traffic lights, queues) and the vehicle powertrain efficiency.

Two hybrid powertrain configurations, including parallel and series hybrids, were simulated for fuel economy, component energy loss, and emissions control in Class 8 trucks over both city and highway driving conditions. A comprehensive set of component models describing engine fuel consumption, emissions control, battery energy, and accessory power demand interactions was developed and integrated with the simulated hybrid trucks to identify heavy-duty (HD) hybrid technology barriers. The results show that series hybrid is absolutely negative for fuel-economy improvement of long-haul trucks due to an efficiency penalty associated with the dual-step conversions of energy (i.e. mechanical to electric to mechanical).

In this study, the compression ratio of a commercial 15L heavy-duty diesel engine was lowered and a split injection strategy was developed to promote partially premixed compression ignition (PPCI) combustion. Various low reactivity gasoline-range fuels were compared with ultra-low-sulfur diesel fuel (ULSD) for steady-state engine performance and emissions. Specially, particulate matter (PM) emissions were examined for their mass, size and number concentrations, and further characterized by organic/elemental carbon analysis, chemical speciation and thermogravimetric analysis. As more fuel-efficient PPCI combustion was promoted, a slight reduction in fuel consumption was observed for all gasoline-range fuels, which also had higher heating values than ULSD. Since mixing-controlled combustion dominated the latter part of the combustion process, hydrocarbon (HC) and carbon monoxide (CO) emissions were only slightly increased with the gasoline-range fuels.

Battery electric vehicles (BEV) in heavy duty (HD) commercial freight transport face challenging technoeconomic barriers to adoption. Specifically, beyond safety and compliance, fleet and operational logistics require both high up-time and parity with diesel system productivity/Total Cost of Ownership (TCO) to enable strong adoption of electrified powertrains. At present, relatively high energy storage prices coupled with the increased weight of BEV systems limit the practicality of HD commercial freight transport to shorter range applications, where smaller batteries will suffice for the mission energy requirements (single operational shift). This paper presents an approach to extend the feasibility of BEV HD trucking for a broad range of applications.