Search Results

Today’s transportation is quickly transforming with the nascent advent of connectivity, automation, shared-mobility, and electrification. These technologies will not only affect our safety and mobility, but also our energy consumption, and environment. As a result, it is of unprecedented importance to understand the overall system impacts due to the introduction of these emerging technologies and concepts. Existing modeling tools are not able to effectively capture the implications of these technologies, not to mention accurately and reliably evaluating their effectiveness with a reasonable scope. To address these gaps, a dynamometer-in-the-loop (DiL) development and testing approach is proposed which integrates test vehicle(s), chassis dynamometer, and high fidelity traffic simulation tools, in order to achieve a balance between the model accuracy and scalability of environmental analysis for the next generation of transportation systems.

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.

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.

A prototype three-way catalyst (TWC) with NOX storage component was evaluated for ammonia (NH3) generation on a 2.0-liter BMW lean burn gasoline direct injection engine as a component in a passive ammonia selective catalytic reduction (SCR) system. The passive NH3 SCR system is a potential approach for controlling nitrogen oxides (NOX) emissions from lean burn gasoline engines. In this system, NH3 is generated over a close-coupled TWC during periodic slightly-rich engine operation and subsequently stored on an underfloor SCR catalyst. Upon switching to lean, NOX passes through the TWC and is reduced by the stored NH3 on the SCR catalyst. Adding a NOX storage component to a TWC provides two benefits in the context of a passive SCR system: (1) enabling longer lean operation by storing NOX upstream and preserving NH3 inventory on the downstream SCR catalyst; and (2) increasing the quantity and rate of NH3 production during rich operation.

Reliable means for on-board detection of particulate filter failures or malfunctions are needed to meet diagnostics (OBD) requirements. Detecting these failures, which result in tailpipe particulate matter (PM) emissions exceeding the OBD limit, over all operating conditions is challenging. Current approaches employ differential pressure sensors and downstream PM sensors, in combination with particulate filter and engine-out soot models. These conventional monitors typically operate over narrowly-defined time windows and do not provide a direct measure of the filter’s state of health. In contrast, radio frequency (RF) sensors, which transmit a wireless signal through the filter substrate provide a direct means for interrogating the condition of the filter itself.

The increasing use of diesel and gasoline particulate filters requires advanced on-board diagnostics (OBD) to prevent and detect filter failures and malfunctions. Early detection of upstream (engine-out) malfunctions is paramount to preventing irreversible damage to downstream aftertreatment system components. Such early detection can mitigate the failure of the particulate filter resulting in the escape of emissions exceeding permissible limits and extend the component life. However, despite best efforts at early detection and filter failure prevention, the OBD system must also be able to detect filter failures when they occur. In this study, radio frequency (RF) sensors were used to directly monitor the particulate filter state of health for both gasoline particulate filter (GPF) and diesel particulate filter (DPF) applications.

It is widely recognized in the automotive industry that, in very cold climatic conditions, the driving range of an Electric Vehicle (EV) can be reduced by 50% or more. In an effort to minimize the EV range penalty, a novel thermal energy storage system has been designed to provide cabin heating in EVs and Plug-in Hybrid Electric Vehicles (PHEVs) by using an advanced phase change material (PCM). This system is known as the Electrical PCM-based Thermal Heating System (ePATHS) [1, 2]. When the EV is connected to the electric grid to charge its traction battery, the ePATHS system is also “charged” with thermal energy. The stored heat is subsequently deployed for cabin comfort heating during driving, for example during commuting to and from work. The ePATHS system, especially the PCM heat exchanger component, has gone through substantial redesign in order to meet functionality and commercialization requirements.

Radio frequency (RF)-based sensors provide a direct measure of the particulate filter loading state. In contrast to particulate matter (PM) sensors, which monitor the concentration of PM in the exhaust gas stream for on-board diagnostics purposes, RF sensors have historically been applied to monitor and control the particulate filter regeneration process. This work developed an RF-based particulate filter control system utilizing both conventional and fast response RF sensors, and evaluated the feasibility of applying fast-response RF sensors to provide a real-time measurement of engine-out PM emissions. Testing with a light-duty diesel engine equipped with fast response RF sensors investigated the potential to utilize the particulate filter itself as an engine-out soot sensor.

Cabin heating of current electric vehicle (EV) designs is typically provided using electrical energy from the traction battery, since waste heat is not available from an engine as in the case of a conventional automobile. In very cold climatic conditions, the power required for space heating of an EV can be of a similar magnitude to that required for propulsion of the vehicle. As a result, its driving range can be reduced very significantly during the winter season, which limits consumer acceptance of EVs and results in increased battery costs to achieve a minimum range while ensuring comfort to the EV driver. To minimize the range penalty associated with EV cabin heating, a novel climate control system that includes thermal energy storage from an advanced phase change material (PCM) has been designed for use in EVs and plug-in hybrid electric vehicles (PHEVs).

We present simulated fuel economy and emissions of city transit buses powered by conventional diesel engines and diesel-hybrid electric powertrains of varying size. Six representative city drive cycles were included in the study. In addition, we included previously published aftertreatment device models for control of CO, HC, NOx, and particulate matter (PM) emissions. Our results reveal that bus hybridization can significantly enhance fuel economy by reducing engine idling time, reducing demands for accessory loads, exploiting regenerative braking, and shifting engine operation to speeds and loads with higher fuel efficiency. Increased hybridization also tends to monotonically reduce engine-out emissions, but tailpipe (post-aftertreatment) emissions are affected by complex interactions between engine load and the transient catalyst temperatures, and the emissions results were found to depend significantly on motor size and details of each drive cycle.

Low temperature combustion (LTC) has been shown to yield higher brake thermal efficiencies with lower NOx and soot emissions, relative to conventional diesel combustion (CDC). However, while demonstrating low soot carbon emissions it has been shown that LTC operation does produce particulate matter whose composition appears to be much different than CDC. The particulate matter emissions from dual-fuel reactivity controlled compression ignition (RCCI) using gasoline and diesel fuel were investigated in this study. A four cylinder General Motors 1.9L ZDTH engine was modified with a port-fuel injection system while maintaining the stock direct injection fuel system. The pistons were modified for highly premixed operation and feature an open shallow bowl design. RCCI operation was carried out using a certification grade 97 research octane gasoline and a certification grade diesel fuel.

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.

We summarize results from comparative simulations of hybrid electric vehicles with either stoichiometric gasoline or diesel engines. Our simulations utilize previously published models of transient engine-out emissions and models of aftertreatment devices for both stoichiometric and lean exhaust. Fuel consumption and emissions were estimated for comparable gasoline and diesel light-duty hybrid electric vehicles operating over single and multiple urban drive cycles. Comparisons between the gasoline and diesel vehicle fuel consumptions and emissions were used to identify potential advantages and technical barriers for diesel hybrids.

We utilize physically-based models for diesel exhaust catalytic oxidation and urea-based selective catalytic NOx reduction to study their impact on drive cycle performance of hypothetical light-duty diesel-powered hybrid and plug-in hybrid vehicles (HEVs and PHEVs). The models have been implemented as highly flexible SIMULINK block modules that can be used to study multiple engine-aftertreatment system configurations. The parameters of the NOx reduction model have been adjusted to reflect the characteristics of commercially available Cu-zeolite catalysts, which are of widespread current interest. We demonstrate application of these models using the Powertrain System Analysis Toolkit (PSAT) software for vehicle simulations, along with a previously published methodology that accounts for emissions and temperature transients in the engine exhaust.

In-cylinder fuel blending of gasoline with diesel fuel is investigated on a multi-cylinder light-duty diesel engine as a strategy to control in-cylinder fuel reactivity for improved efficiency and lowest possible emissions. This approach was developed and demonstrated at the University of Wisconsin through modeling and single-cylinder engine experiments. The objective of this study is to better understand the potential and challenges of this method on a multi-cylinder engine. More specifically, the effect of cylinder-to-cylinder imbalances and in-cylinder charge motion as well as the potential limitations imposed by real-world turbo-machinery were investigated on a 1.9-liter four-cylinder engine. This investigation focused on one engine condition, 2300 rpm, 5.5 bar net mean effective pressure (NMEP). Gasoline was introduced with a port-fuel-injection system.

A transient, one-dimensional lean NOx trap (LNT) model is described and implemented for vehicle systems simulations. The model accounts for conservation of chemical species and thermal energy, and includes the effects of O₂ storage and NOx storage (in the form of nitrites and nitrates). Nitrites and nitrates are formed by diffusion of NO and NO₂, respectively, into sorbent particles, and reaction rates are controlled by chemical kinetics and solid-phase diffusion. The model also accounts for thermal aging and sulfation by means of empirical correlations, which have been derived from laboratory experiments. Example simulation results using the Powertrain Systems Analysis Toolkit (PSAT) are presented.

Due to increasingly stringent emissions regulations, Lean NOx Trap (LNT) catalysts are being researched as a potential solution for diesel engine emissions reduction. LNTs are practical for diesel NOx reduction due to their ability to reduce NOx from the O2 rich environment produced by diesel engines. LNTs function by storing NOx on the catalyst surface during efficient lean operation then, under rich conditions, releasing and reducing the trapped NOx. One method of producing this rich environment which regenerates a LNT involves manipulating the fuel injection parameters and throttling the air intake. This process is called in-cylinder regeneration. Experiments will be described here in which a 1.7 L common rail diesel engine has been used to regenerate LNTs at various stages of sulfur exposure, a known poison of the LNT.

Hydrogen (H2) is an excellent reductant, and has been shown to be highly effective when introduced into a variety of catalysts such as three-way catalysts, lean NOx traps (LNTs), and hydrocarbon lean NOx catalysts (also termed hydrocarbon selective catalytic reduction (SCR) catalysts). Furthermore, since lean-burn engines offer improved fuel efficiency yet difficult NOx emission control, H2 production during lean operation for the purpose of NOx reduction could be beneficial. On-board generation of hydrogen is being explored via catalytic or plasma-based reformers. A possible alternative to these add-on systems is generation of the H2 in-cylinder with standard fuel injection hardware. This paper details experiments relating to the production and measurement of H2 under net-lean operation in a common-rail diesel engine. In-cylinder fuel control is used to tailor the combustion process such that H2 is generated while maintaining a lean Air:Fuel ratio in the bulk exhaust gas.

Lean NOx Trap (LNT) catalysts are capable of reducing NOx in lean exhaust from diesel engines. NOx is stored on the catalyst during lean operation; then, under rich exhaust conditions, the NOx is released from and reduced by the catalyst. The process of NOx release and reduction is called regeneration. One method of obtaining the rich conditions for regeneration is to inject additional fuel into the engine cylinders while throttling the engine intake air flow to effectively run the engine at rich air:fuel ratios; this method is called “in-cylinder” regeneration. In-cylinder regeneration of LNT catalysts has been demonstrated and is a candidate emission control technique for commercialization of light-duty diesel vehicles to meet future emission regulations. In the study presented here, a 1.7-liter diesel engine with a LNT catalyst system was used to evaluate in-cylinder regeneration techniques.