Search Results

Maintaining the fuel temperature and fuel system components below certain values is an important design objective. Predicting these temperatures is therefore one of the key parts of the vehicle’s thermal management process. One of the physical processes affecting fuel tank temperature is fuel vaporization, which is controlled by the vapor pressure in the tank, fuel composition and fuel temperature. Models are developed to enable the computation of the fuel temperature, fuel vaporization rate in the tank, fuel temperatures along the fuel supply lines, and follow its path to the charcoal canister and into the engine intake. For diesel fuel systems where a fuel return line is used to return excess fluid back to the fuel tank, an energy balance will be considered to calculate the heat added from the high-pressure pump and vehicle under-hood and underbody.

A cargo box is a key structure in a pickup truck which is used to hold various items. Therefore, a cargo box must be durable and robust under different ballast conditions when subjected to road load inputs. This paper discusses a Design for Six Sigma (DFSS) approach to improve the durability of cargo box panel in its early development phase. Traditional methods and best practices resulted in multiple iterations without an obvious solution. Hence, DFSS tools were proposed to find a robust and optimum solution. Key control factors/design parameters were identified, and L18 Orthogonal Array was chosen to optimize design using CAE tools. The optimum design selected was the one with the minimum stress level and the least stress variation. This design was confirmed to have significant improvement and robustness compared to the initial design. DFSS identified load paths which helped teams finally come up with integrated shear plate to resolve the durability concern.

Autonomous vehicle operation is dependent upon accurate position estimation and thus a major concern of implementing the autonomous navigation is obtaining robust and accurate data from sensors. This is especially true, in case of Inertial Measurement Unit (IMU) sensor data. The IMU consists of a 3-axis gyro, 3-axis accelerometer, and 3-axis magnetometer. The IMU provides vehicle orientation in 3D space in terms of yaw, roll and pitch. Out of which, yaw is a major parameter to control the ground vehicle’s lateral position during navigation. The accelerometer is responsible for attitude (roll-pitch) estimates and magnetometer is responsible for yaw estimates. However, the magnetometer is prone to environmental magnetic disturbances which induce errors in the measurement.

The effects of an oxidation catalytic converter (OCC), an emulsified fuel, and their combined effects on particle number and volume concentrations compared to those obtained when using a basefuel were studied. Particle size and particulate emission measurements were conducted at three operating conditions; idle (850 rpm, 35 Nm), Mode 11 (1900 rpm, 277 Nm) and Mode 9 (1900 rpm, 831 Nm) of the EPA 13 mode cycle. The individual effects of the emulsified fuel and the OCC as well as their combined effects on particle number and volume concentrations were studied at two different particle size ranges; the nuclei (less than or equal to 50 nm) and accumulation (greater than 50 nm) modes. An OCC loaded with 10 g/ft3 platinum metal (OCC1) and a 20% emulsified fuel were used for this study and a notable influence on the particle size with respect to number and volume distributions was observed.

A study was conducted to assess the effects of a water-diesel fuel emulsion with and without an oxidation catalytic converter (OCC) on steady-state heavy-duty diesel engine emissions. Two OCCs with different metal loading levels were used in this study. A 1988 Cummins L10-300 heavy-duty diesel engine was operated at the rated speed of 1900 rpm and at 75% and 25% load conditions (EPA modes 9 and 11 respectively) of the 13 mode steady-state test as well as at idle. Raw exhaust emissions' measurements included total hydrocarbons (HC), oxides of nitrogen (NOx) and nitric oxide (NO). Diluted exhaust measurements included total particulate matter (TPM) and its primary constituents, the soluble organic (SOF), sulfate (SO42-) and the carbonaceous solids (SOL) fractions. Vapor phase organic compounds (XOC) were also analyzed. The SOF and XOC samples were analyzed for selected polynuclear aromatic hydrocarbons (PAHs).

During development of new vehicles, CAE driven optimizations are helpful in achieving the optimal designs. In the early phase of vehicle development there is an opportunity to explore shape changes, gage reduction or alternative materials as enablers to reduce weight. However, in later phases of vehicle development the window of opportunity closes on most of the enablers discussed above. The paper discusses a simplified methodology for reducing the weight in design cycle for truck frames using parametric Design of Experiments (DOE). In body-on-frame vehicles, reducing the weight of the frame in the design cycle without down gaging involves introducing lightening holes or cutouts while still maintaining the fatigue life. It is also known that the lightening holes might cause stress risers and be detrimental to the fatigue life of the component. Thus the ability to identify cutout locations while maintaining the durability performance becomes very critical.

The increased availability of natural gas (NG) in the United States (US) and its relatively low cost versus diesel fuel has increased interest in the conversion of medium duty (MD) and heavy duty (HD) engines to NG fueled combustion systems. The aim for development for these NG engines is to realize fuel cost savings and increase operating range while reduce harmful emissions and maintaining durability. Traditionally, port-fuel injection (PFI) or premixed NG spark-ignited (SI) combustion systems have been used for light duty LD, and MD engines with widespread use in the US and Europe [1]. However, this technology exhibits poor thermal efficiency and is load limited due to knock phenomenon that has prohibited its use for HD engines. Spark Ignited Direct Injection (SIDI) can be used to create a partially stratified combustion (PSC) mixture of NG and air during the compression stroke.

A detailed Design of Experiments (DOE) study is presented to understand the aerodynamic effects of exterior design features and shape parameters of a pick-up truck using Computational Fluid Dynamics (CFD). The goal of the study is to characterize several key design parameters and the interactions between them as related to overall drag of the vehicle. Using this data, the exterior shape is optimized to minimize drag within specified design constraints. An adaptive sampling methodology is also presented that progressively reduces errors in the design response surfaces generated. This combined with a Latin Hypercube based initial design space characterization yields computational efficiency. A trend-predictive meta-model is presented that can be used for early design development. Results from the meta-model are also correlated with experimental data from the wind tunnel.

This paper describes the results of experiments that were performed using a Ground Research Vehicle (GRV) at the National Aeronautics and Space Administration's (NASA) Dryden Flight Research Center in Edwards, CA and a comparison with computational results. The GRV is a modified 1984 General Motors (GMC) van and measures 40 feet long and 9 feet high, with a base area of 83 by 83, and it weighs 10260 lbs and holds a crew of up to three. Air data is measured from a nose-boom, 2 global positioning (GPS) units, and an absolute Honeywell Pressure Transducer with 4 Electronic Signal Processor (ESP) scanners and 64 surface pressure ports. This allows for detailed measurements of the surface pressure profiles around the vehicle. The total vehicle drag is estimated from coast-down tests, while the pressure component of the drag force may be calculated by integrating the pressure profiles on the front and base of the vehicle.

The hardware and software for a prototype computer controlled cooling system for a diesel powered truck has been designed and tested. The basic requirements for this system have been defined and the control functions, previously investigated in a study using the computer simulation model, were incorporated into the software. Engine dynamometer tests on the MACK-676 engine, comparing the conventional cooling system and the computer controlled system, showed the following advantages of the computer controlled system: 1. The temperature level to which the engine warms up to at low ambient temperature, was increased. 2. The faster shutter response reduced the temperature peaks and decreased total fan activity time. 3. The faster fan response reduces fan engagement time which should improve truck fuel economy.

Several very different order tracking and analysis techniques for rotating equipment have been developed recently that are available in commercial noise and vibrations software packages. Each of these order tracking methods has distinct trade-offs for many common applications and very specific advantages for special applications in sound quality or noise and vibrations troubleshooting. The Kalman, Vold-Kalman, Computed Order Tracking, and the Time Variant Discrete Fourier Transform as well as common FFT based order analysis methods will all be presented. The strengths and weaknesses of each of the methods will be presented as well as the highlights of their mathematical properties. This paper is intended to be an overview of currently available technology with all methods presented in a common format that allows easy comparison of their properties. Several analytical examples will be presented to thoroughly document each methods' behavior with different types of data.

The increased availability of natural gas (NG) in the United States (US) and its relatively low cost compared to diesel fuel has heightened interest in the conversion of medium duty (MD) and heavy duty (HD) engines to NG fueled combustion systems. The aim for development for these NG engines is to realize fuel cost savings and reduce harmful emissions while maintaining durability. Transforming part of the vehicle fleet to NG is a path to reduce dependence on crude oil. Traditionally, port-fuel injection (PFI) or premixed NG spark-ignited (SI) combustion systems have been used for MD and HD engines with widespread use in the US and Europe. But this technology exhibits poor cycle efficiency and is load limited due to knock phenomenon. Direct Injection of NG during the compression stroke promises to deliver improved thermal efficiency by avoiding excessive premixing and extending the lean limits which helps to extend the knock limit.

The increased availability of natural gas (NG) in the United States (US), and its relatively low cost compared to diesel fuel has heightened interest in the conversion of medium duty (MD) and heavy duty (HD) engines to NG fueled combustion systems. The aim is to realize fuel cost savings and reduce harmful emissions, while maintaining durability. This is a potential path to help the US reduce dependence on crude oil. Traditionally, port-fuel injection (PFI) or premixed NG spark-ignited (SI) combustion systems have been used for MD and HD engines with widespread use in the US and Europe; however, this technology exhibits poor cycle efficiency and is load limited due to knock phenomenon. Direct Injection of NG during the compression stroke promises to deliver improved thermal efficiency by avoiding excessive premixing and extending the lean limits which helps to extend the knock limit.

Flexibility and backlash of vehicle drivelines typically cause unwanted oscillations and noise, known as shuffle and clunk, during tip-in and tip-out events. Computationally efficient and accurate driveline models are necessary for the design and evaluation of torque shaping strategies to mitigate this shuffle and clunk. To accomplish these goals, this paper develops a full-order physics-based model and uses this model to develop a reduced-order model (ROM), which captures the main dynamics that influence the shuffle and clunk phenomena. The full-order model (FOM) comprises several components, including the engine as a torque generator, backlash elements as discontinuities, and propeller and axle shafts as compliant elements. This model is experimentally validated using the data collected from a Ford vehicle. The validation results indicate less than 1% error between the model and measured shuffle oscillation frequencies.

The use of numerical simulations in the development processes of engineering products has been more frequent, since it enables prediction of premature failures and study of new promising concepts. In industry, numerical simulation has the function of reducing the necessary number of validation tests prior to spending resources on alternatives with lower likelihood of success. The internal combustion Diesel engine plays an important role in Brazil, since they are used extensively in automotive applications and commercial cargo transportation, mainly due to their relevant advantage in fuel consumption and reliability. In this case, the most critical pollutants are oxides of nitrogen (NOx) and particulate matter (PM) or soot. The reduction of their levels without affecting the engine performance is not a simple task. This paper presents a methodology for guiding the combustion analysis by the prediction of NOx emissions and soot using numerical simulation.

While significant progress has been made in recent years to develop hybrid and battery electric vehicles for passenger car and light-duty applications to meet future fuel economy targets, the application of hybrid powertrains to heavy-duty truck applications has been very limited. The relatively lower energy and power density of batteries in comparison to diesel fuel and the operating profiles of most heavy-duty trucks, combine to make the application of hybrid powertrain for these applications more challenging. The high torque and power requirements of heavy-duty trucks over a long operating range, the majority of which is at constant cruise point, along with a high payback period, complexity, cost, weight and range anxiety, make the hybrid and battery electric solution less attractive than a conventional powertrain.

More stringent Federal emission regulations and fuel economy requirements have driven the automotive industry towards more sophisticated vehicle thermal management systems to best utilize the waste heat and improve driveline efficiency. The final drive unit in light and heavy duty trucks usually consists of geared transmission and differential housed in a lubricated axle. The automotive rear axle is one of the major sources of power loss in the driveline due to gear friction, churning and bearing loss affecting vehicle fuel economy. These losses vary significantly with lubricant viscosity. Also the temperatures of the lubricant are critical to the overall axle performance in terms of power losses, fatigue life and wear. In this paper, a methodology for modeling thermal behavior of automotive rear axle with heat exchanger is presented. The proposed model can be used to predict the axle lubricant temperature rise.

This paper describes the design, development, and operation of a rear axle dual-shell heat exchanger on the RAM 1500 Light Duty truck. This system has been proven to increase fuel economy and reduce exhaust emissions, particularly CO2, on the EPA Cold City schedule. The energy conversion strategy was first explored using math modeling. A PUGH analysis associated with concept selection is included. To refine the hardware and develop a control strategy prior to testing, a portable flow cart was developed to assess system performance and to correlate the multi-node heat transfer model. Bench testing focused on the durability and functional aspects of integrating the dual-shell axle cover with the axle and coolant delivery system through a comprehensive design and validation plan. Vehicle testing included various fuel economy and emissions related driving schedules to quantify the benefits.

The LEV IV FTP PM limit in the recently approved CARB ACC II regulations for passenger cars and light duty trucks will be 1 mg/mile starting in 2025. Gravimetric PM measurement at these levels is very challenging as the net mass of PM on the filter in full flow tunnel testing ranges between 8 to 32 micrograms depending on amount of dilution. This is approaching tunnel background levels which, in combination with filter handling, static charge removal and microbalance instability, compounds the uncertainty. One major source of the uncertainty at these low levels is the tunnel contamination resulting in high variability from test to test and cell to cell. This tunnel background is mostly HC artifact which cannot be easily controlled and can be significantly higher than the 5-μg CFR allowable correction limit in some test cells.

Cargo box is one of the indispensable structures of a pickup truck which makes it capable of transporting heavy cargo weights. This heavy cargo weight plays an important role in durability performance of the box structure when subjected to road load inputs. Finite element representation for huge cargo weight is always challenging, especially in a linear model under dynamic proving ground road load durability analysis using a superposition approach. Any gap in virtual modeling technique can lead to absurd cargo box modes and hence durability results. With the existing computer aided engineering (CAE) approach, durability results could not correlate much with physical testing results. It was crucial to have the right and robust CAE modeling technique to represent the heavy cargo weight to provide the right torsional and cargo modes of the box structure and in turn good durability results.