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Aerodynamic performance testing of heavy duty fans involve complicated test setups with specialized equipment and measurement systems as summarized in ANSI 210-07 standard. This paper describes virtual testing and simulation methods to obtain the fan aerodynamic performance data using commercial Computational Fluid Dynamics (CFD) software. Two different virtual test environments were used during the analysis. The first one is a virtual test chamber which is constructed based on the actual fan system installation. The second one is a virtual flow tube which approximates a fan flow test set-up as outlined in ANSI 210-07. The virtual fan is created from (i) the laser scan of the actual fan and (ii) the design specifications of the fan. The virtual test conditions simulate the actual test arrangement by imposing free boundary at flow inlet/outlet and proper fan rotation. The aerodynamic flow rate is controlled by a variable orifice located at the virtual test chamber outlet.

An optimal energy management strategy (Optimal EMS) can yield significant fuel economy (FE) improvements without vehicle velocity modifications. Thus it has been the subject of numerous research studies spanning decades. One of the most challenging aspects of an Optimal EMS is that FE gains are typically directly related to high fidelity predictions of future vehicle operation. In this research, a comprehensive dataset is exploited which includes internal data (CAN bus) and external data (radar information and V2V) gathered over numerous instances of two highway drive cycles and one urban/highway mixed drive cycle. This dataset is used to derive a prediction model for vehicle velocity for the next 10 seconds, which is a range which has a significant FE improvement potential. This achieved 10 second vehicle velocity prediction is then compared to perfect full drive cycle prediction, perfect 10 second prediction.

Prediction of vehicle velocity is important since it can realize improvements in the fuel economy/energy efficiency, drivability, and safety. Velocity prediction has been addressed in many publications. Several references considered deterministic and stochastic approaches such as Markov chain, autoregressive models, and artificial neural networks. There are numerous new sensor and signal technologies like vehicle-to-vehicle and vehicle-to-infrastructure communication that can be used to obtain inclusive datasets. Using these inclusive datasets of sensors in deep neural networks, high accuracy velocity predictions can be achieved. This research builds upon previous findings that Long Short-Term Memory (LSTM) deep neural networks provide low error velocity prediction. We developed an LSTM deep neural network that uses different groups of datasets collected in Fort Collins, Colorado.

Developing a complete understanding of the structure and behavior of the near-wall region (NWR) in reciprocating, internal combustion (IC) engines and of its interaction with the core flow is needed to support the implementation of advanced combustion and engine operation strategies, as well as predictive computational models. The NWR in IC engines is fundamentally different from the canonical steady-state turbulent boundary layers (BL), whose structure, similarity and dynamics have been thoroughly documented in the technical literature. Motivated by this need, this paper presents results from the analysis of two-component velocity data measured with particle image velocimetry near the head of a single-cylinder, optical engine. The interaction between the NWR and the core flow was quantified via statistical moments and two-point velocity correlations, determined at multiple distances from the wall and piston positions.

Light duty vehicle emission standards are getting more stringent than ever before as stipulated by US EPA Tier 2 Standards and LEV III regulations proposed by CARB. The research in this paper sponsored by US DoE is focused towards developing a Tier 2 Bin 2 Emissions compliant light duty pickup truck with class leading fuel economy targets of 22.4 mpg “City” / 34.3 mpg “Highway”. Many advanced technologies comprising both engine and after-treatment systems are essential towards accomplishing this goal. The objective of this paper would be to discuss key engine technology enablers that will help in achieving the target emission levels and fuel economy. Several enabling technologies comprising air-handling, fuel system and base engine design requirements will be discussed in this paper highlighting both experimental and analytical evaluations.

Current production heavy duty diesel engines have a brake thermal efficiency (BTE) between 43-46% [1]. In partnership with the United States Department of Energy (DOE) as part of the Supertruck 2 program, Cummins has undertaken a research program to develop a new heavy-duty diesel engine designed to deliver greater than 50% BTE without the use of waste heat recovery. A system level optimization focused on: increased compression ratio, higher injection rate, carefully matched highly efficient turbocharging, variable lube oil pump, variable cooling components, and low restriction after treatment designed to deliver 50% BTE at a target development point. This work will also illustrate the system level planning and understanding of interactions required to allow that same 50% BTE heavy duty diesel engine to be integrated with a waste heat recovery (WHR) system to deliver system level efficiency of 55% BTE at a single point.

Control and elimination of mobil-source particulate matter (PM) emissions is of increasing interest to engineers and scientists as regulators in industrialized countries promulgate lower emission levels in diesel engines. Relative to their gasoline engine counterparts, today's diesel engines, in general, still emit a higher mass of PM. While strictly speaking, this PM is an agglomeration of organic and inorganic particles, the predominant component is carbon and is commonly referred to as “soot”. For mobil-source PM control, one of the current preferred technologies is the ceramic closed-cell monolith Diesel Particulate Filter (DPF). Ideally, DPFs accumulate and store PM during low speed/temperature engine operation and burn the accumulated PM during high speed/temperature operation.

The influence of big-end bore fretting on connecting rod fatigue fracture is investigated. A finite element model, including rod-bearing contact interaction, is developed to simulate a fatigue test rig where the connecting rod is subjected to an alternating uniaxial load. Comparison of the model results with a rod fracture from the fatigue rig shows good correlation between the fracture location and the peak ‘Ruiz’ criterion, rather than the peak tensile stress location, indicating the potential of fretting to initiate a fatigue fracture and the usefulness of the ‘Ruiz’ criterion as a measure of location and severity. The model is extended to simulate a full engine cycle using pressure loads from a bearing EHL analysis. A fretting map and a ‘Ruiz’ criterion map are developed for the full engine cycle, giving an indication of a safe ‘Ruiz’ level from an existing engine which has been in service for more than 5 years.

The recent interest to use Alternative Fuels for power generation and or mobile power is mainly driven by the serious environmental concerns and energy security of the nation. In this context, the utilization of the landfill gases which are generally low heating valve (Btu) content fuels and normally produced from municipal and city solid waste such as in landfills or garbage dump sites has been increasingly used due to the two fold benefits; firstly, the proper utilization of the gas will avoid the green house gas effect and other environmental concerns and secondly it can produce revenue for the local governments or industries at the same time. The paper describes the results of the investigation of the utilization of landfill gases in a spark ignition (SI) engine. Methane and landfill gas compositions were tested and their performance and combustion characteristics are studied and compared.

The effects of fuel composition and engine operating parameters on high-pressure, direct injection gasoline (DIG) injector plugging and deposit formation have been studied. The engine used was a conventional dual-sparkplug, 2.2-liter Nissan engine modified for direct injection using one of the spark plug holes. The engine was run under 20% rich conditions to accelerate deposit formation. A ten-fuel test matrix was designed around T90, sulfur level, and olefin levels indicated in the European gasoline specifications for year 2000. The gasolines, containing no detergents, were formulated using refinery stream blends to match the specified targets. Injector flow loss was monitored by fuel flow to the engine and monitoring oxygen sensors on each of the four cylinders. The impact of fuel composition on deposit formation and injector plugging is discussed. Injector flow loss was strongly influenced by injector tip temperature.

This paper presents the findings of some fundamental characterisation of the deposits that form on the injectors of an air-assisted DISI automotive engine, including the effect of these deposits on engine performance when operated in different combustion modes, with varying fuel composition and additive content. A root cause analysis was undertaken, including an assessment of injector temperature and deposit chemistry. Fuels from a matrix designed around the European year 2000 gasoline specifications for T90, olefin and aromatic levels were used to study the effect of fuel composition on deposit formation. Two commercial gasoline detergent additives, of different chemistries, were used to investigate the impact on deposit formation. The results of the fuels study and deposit analysis are consistent with published theories concerning fuel composition impact on combustion chamber deposit (CCD).

In modern engine design, downsizing and reducing weight while still providing an increased amount of power has been a general trend in recent decades. Traditionally, an engine design with superior NVH performance usually comes with a heavier, thus sturdier structure. Therefore, modern engine design requires that NVH be considered in the very early design stage to avoid modifications of engine structure at the last minute, when very few changes can be made. NVH design optimization of engine components has become more practical due to the development of computer software and hardware. However, there is still a need for smarter algorithms to draw a direct relationship between the design and the radiated sound power. At the moment, techniques based on modal acoustic transfer vectors (MATVs) have gained popularity in design optimization for their good performance in sound pressure prediction.

With increasing energy prices and concerns about the environmental impact of greenhouse gas (GHG) emissions, a growing number of national governments are putting emphasis on improving the energy efficiency of the equipment employed throughout their transportation systems. Within the U.S. transportation sector, energy use in commercial vehicles has been increasing at a faster rate than that of automobiles. A 23% increase in fuel consumption for the U.S. heavy duty truck segment is expected from 2009 to 2020. The heavy duty vehicle oil consumption is projected to grow while light duty vehicle (LDV) fuel consumption will eventually experience a decrease. By 2050, the oil consumption rate by LDVs is anticipated to decrease below 2009 levels due to CAFE standards and biofuel use. In contrast, the heavy duty oil consumption rate is anticipated to double. The increasing trend in oil consumption for heavy trucks is linked to the vitality, security, and growth of the U.S. and global economies.

Prediction based optimal energy management systems are a topic of high interest in the automotive industry as an effective, low-cost option for improving vehicle fuel efficiency. With the continuing development of connected and autonomous vehicle (CAV) technology there are many data streams which may be leveraged by transportation stakeholders. The Suite of CAVs-derived data streams includes advanced driver-assistance (ADAS) derived information about surrounding vehicles, vehicle-to-vehicle (V2V) communications for real time and historical data, and vehicle-to-infrastructure (V2I) communications. The suite of CAVs-derived data streams have been demonstrated to enable improvements in system-level safety, emissions and fuel economy.

Changing diesel engine emission requirements for 2002 have led many diesel engine manufacturers to incorporate cooled Exhaust Gas Recirculation, EGR, as a means of reducing NOx. This has resulted in higher levels of soot being present in used oils. This paper builds on earlier work with fresh oils and describes a study of the effect of highly sooted oils on the low temperature pumpability in diesel engines. Four experimental diesel engine oils, of varying MRV TP-1 viscosities, were run in a Mack T-8 engine to obtain a soot level ranging between 6.1 and 6.6%. These sooted oils were then run in a Cummins M11 engine installed in a low temperature cell. Times to lubricate critical engine components were measured at temperatures ranging between -10 °C and -25 °C. A clear correlation was established between the MRV TP-1 viscosity of a sooted oil and the time needed to lubricate critical engine components at a given test temperature.

Production NO sensors have a strong cross-sensitivity to ammonia which limits their use for closed-loop SCR control and diagnostics since increases in sensor output can be caused by either gas component. Recently, Ammonia/NO Ratio (ANR) perturbation methods have been proposed for determining the dominant component in the post-SCR exhaust as part of the overall SCR control strategy, but these methods or the issue of sensor cross-sensitivity have not been critically evaluated or studied in their own right. In this paper the dynamic sensor direct- and cross-sensitivities are estimated from experimental FTIR data (after compensating for the dynamics of the gas sampling system) and compared to nominal values provided by the manufacturer. The ANR perturbation method and the use of different input excitations are then discussed within an analytical framework, and applied to experimental data from a large diesel engine.

The performance of an organic Rankine cycle (ORC) that recovers heat from the exhaust of a heavy-duty diesel engine was simulated. The work was an extension of a prior study that simulated the performance of an experimental ORC system developed and tested at Oak Ridge National laboratory (ORNL). The experimental data were used to set model parameters and validate the results of that simulation. For the current study the model was adapted to consider a 15 liter turbocharged engine versus the original 1.9 liter light-duty automotive turbodiesel studied by ORNL. Exhaust flow rate and temperature data for the heavy-duty engine were obtained from Southwest Research Institute (SwRI) for a range of steady-state engine speeds and loads without EGR. Because of the considerably higher exhaust gas flow rates of the heavy-duty engine, relative to the engine tested by ORNL, a different heat exchanger type was considered in order to keep exhaust pressure drop within practical bounds.

Estimated engine torque is an important parameter used by automotive systems for automated transmission and clutch control. Heavy-duty engine and transmission manufacturers widely use SAE J -1939 based ECU torque calculation based on mass air/fuel flow steady state maps created during calibration of the engine for this purpose. As an alternative, to enhance the accuracy of this important control variable, a virtual flywheel torque sensor (VFTS) was developed. It measures the engine torque based on the harmonics of the instantaneous flywheel speed signal. Initial dynamometer testing showed the VFTS estimated torque values exhibited a maximum inaccuracy of 12% of the actual measured torque over the range of conditions tested. In this paper we report the results of on road truck testing of the VFTS. A loaded heavy truck with a gross vehicle weight rating of 80,000 pounds was used.

NVH development of light duty diesel engines require significant collaboration with the OEM as compared to medium duty and heavy duty diesel engines. Typically, competitive benchmark studies and customer expectations define the NVH targets at the vehicle level and are subsequently cascaded down to the powertrain level. For engine manufacturing companies like Cummins Inc., it is imperative to work closely with OEM to deliver on the NVH expectations. In certain situations, engine level NVH targets needs to be demonstrated in the OEM or 3rd party acoustic test facility for customer satisfaction or commercial purposes. Engine noise tests across different noise test facilities may introduce some variation due to differences in the acoustic test facilities, test hardware, instrumentation differences, etc. In addition, the engine itself is a major source of variation.

Major emphasis on the use of lightweight components in engines has lead to widespread use of polymer intake manifolds. The pulsed flow through these manifolds combined with the lower elastic modulus materials can result in excessive noise under certain speed load conditions. Using full-field optical techniques allowed for the detection and analysis of the resonance behavior in polymer intake manifolds. The test procedures involved techniques including time-averaged holography, with variable excitation sources to identify resonating regions and associated critical frequencies. The results clearly indicate the development of an efficient test methodology to analyze manifold designs for resonance and structural characteristics