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This paper presents an extension of our earlier work on Cummins Vehicle Mission Simulation (VMS) software. Previously, we presented VMS as a Windows based analysis tool to simulate vehicle missions quickly and to gauge, communicate, and improve the value proposition of Cummins engines to customers. Presenter Nagesh Belludi, Cummins Inc.

Piston cooling nozzles/jets play several crucial roles in the power cylinder of an internal combustion engine. Primarily, they help with the thermal management of the piston and provide lubrication to the cylinder liner and the piston’s wrist pin. In order to evaluate the oil jet characteristics from various piston cooling nozzle (PCN) designs, a quantitative and objective process was developed. The PCN characterization began with a computational fluid dynamics (CFD) turbulent model to analyze the mean oil velocity and flow distribution at the nozzle exit/tip. Subsequently, the PCN was tested on a rig for a given oil temperature and pressure. A high-speed camera captured images at 2500 frames per second to observe the evolution of the oil stream as a function of distance from the nozzle exit. An algorithm comprised of standard digital image processing techniques was created to calculate the oil jet width and density.

Wheel loader subsystems are multi-domain in nature, including controls, mechanisms, hydraulics, and thermal. This paper describes the process of developing a multi-domain simulation of a wheel loader. Working hydraulics, kinematics of the working tool, driveline, engine, and cooling system are modeled in LMS Imagine.Lab Amesim. Contacts between boom/bucket and bucket/ground are defined to constrain the movement of the bucket and boom. The wheel loader has four heat exchangers: charge air cooler, radiator, transmission oil cooler, and hydraulic oil cooler. Heat rejection from engine, energy losses from driveline, and hydraulic subsystem are inputs to the heat exchangers. 3D CFD modeling was done to calibrate airflows through heat exchangers in LMS Amesim. CFD modeling was done in ANSYS FLUENT® using a standard k - ε model with detailed fan and underhood geometry.

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.

A systems-level modeling framework developed to estimate the life cycle cost of medium- and heavy-duty trucks is discussed in this paper. Costs are estimated at a resolution of five major subsystems and 30+ subsystems, each representing a specific manufacturing technology. Interrelationships among various subsystems affecting cost are accounted for. Results of a specific Class 8 truck are finally discussed to demonstrate the modeling framework's capability, including the analysis of cost-effectiveness of some of the competing alternative system design options being considered by the industry today.

This paper presents an extension of our earlier work on Cummins Vehicle Mission Simulation (VMS) software. Previously, we presented VMS as a Windows based analysis tool to simulate vehicle missions quickly and to gauge, communicate, and improve the value proposition of Cummins engines to customers. We have subsequently extended this VMS architecture to build a grid-computing platform to support high volume of simulation needs. The building block of the grid-computing version of VMS is an executable file that consists of vehicle and engine simulation models compiled using Real Time Workshop. This executable file integrates MATLAB and Simulink with Java, XML, and JDBC technologies and interacts with the MySQL database. Our grid consists of a cluster of twenty Linux servers with quad-core processors. The Sun Grid Engine software suite that administers this cluster can batch-queue and execute 80 simulations concurrently.

A range of cycle characteristics have been used to estimate the hybrid potential for vehicle duty cycles including characteristic acceleration, aerodynamic velocity, kinetic intensity, stop time, etc. These parameters give an indication of overall hybrid potential benefits, but do not contain information on the distribution of the available braking energy and the hybrid system power required to capture the braking energy. In this paper, the authors propose two new cycle characteristics to help evaluate overall hybrid potential of vehicle cycles: P50 and P90, which are non-dimensional power limits at 50% and 90% of available braking energy. These characteristics are independent of vehicle type, and help illustrate the potential hybridization benefit of different drive cycles. First, the distribution of available braking energy as a function of brake power for different vehicle cycles and vehicle classes is analyzed.

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.

Fuel usage negatively impacts the environment and is a significant portion of operational costs of moving freight globally. Reducing fuel consumption is key to lessening environmental impacts and maximizing freight efficiency, thereby increasing the profit margin of logistic operators. In this paper, fuel economy improvements of a cab-over style 49T heavy duty Foton truck powered by a Cummins 12-liter engine are studied and systematically applied for the China market. Most fuel efficiency improvements are found within the vehicle design when compared to opportunities available at the engine level. Vehicle design (improved aerodynamics), component selection/matching (low rolling resistance tires), and powertrain electronic features integration (shift schedule/electronic trim) offer the largest opportunities for lowering fuel consumption.

Drivability and powertrain refinement continue to gain importance in the assessment of overall vehicle quality. This notion has transcended its light duty origins and is beginning to gain considerable traction in the medium and heavy duty markets. However, with drivability assessment and refinement also comes the high costs associated with vehicle testing, including items such as test facilities, prototype component evaluation, fuel and human resources. Taking all of this into account, any and all measures must be used to reduce the cost of drivability evaluation and powertrain refinement. This paper describes an analysis based co-simulation methodology, where sophisticated powertrain simulation and objective drivability evaluation tools can be used to predict vehicle drivability. A fast running GT power engine model combined with simplified controls representation in Matlab/Simulink was used to predict engine transients and responses.

Driver is a key component in vehicle simulation. An ideal driver model simulates driving patterns a human driver may perform to negotiate road profiles. There are simulation packages having the capability to simulate driver behavior. However, it is rarely documented how they work with road profiles. This paper proposes a new truck driver model for vehicle simulation to imitate actual driving behavior in negotiating road grade and curvature. The proposed model is developed based upon Gipps' car-following model. Road grade and curvature were not considered in the original Gipps' model although it is based directly on driver behavior and expectancy for vehicles in a stream of traffic. New parameters are introduced to capture drivers' choice of desired speeds that they intend to use in order to negotiating road grade and curvature simultaneously. With the new parameters, the proposed model can emulate behaviors like uphill preparation for different truck drivers.

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.

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.

Various 1D simulation tools (KULI & LMS Amesim) and 3D simulation tools (ANSYS FLUENT®) can be used to size and evaluate truck cooling system design. In this paper, ANSYS FLUENT is used to analyze and validate the design of medium duty truck cooling systems. LMS Amesim is used to verify the quality of heat exchanger input data. This paper discusses design and simulation of parent and derivative trucks. As a first step, the parent truck was modeled in FLUENT (using standard' k - ε model) with detailed fan and underhood geometry. The fan is modeled using Multiple Reference Frame (MRF) method. Detailed geometry of heat exchangers is skipped. The heat exchangers are represented by regular shape cell zones with porous medium and dual cell heat exchanger models to account for their contributions to the entire system in both flow and temperature distribution. Good agreement is observed between numerical and experimental engine out temperatures at different engine operating conditions.

This article analyzes the aerodynamic performance of Class 8 tractor-trailer geometries made available by the Environmental Protection Agency (EPA) using CFD simulation. Large Eddy Simulations (LES) were carried out with the CFD package, Simerics-MP+. A Sleeper tractor and a 53-foot box trailer configuration was considered. The configuration featured a detailed underbody, an open-grille under-hood engine compartment, mirrors, and the radiator and condenser. Multiple tractor-trailer variants were studied by adding aerodynamic surfaces to the baseline geometries. These include tank fairings and side extenders for the cabins, two types of trailer skirts, and a trailer tail. The effect of these devices towards reducing the overall vehicle drag was investigated. Mesh generation was carried out directly on the given geometry, without any surface modifications, using Simerics’ Binary-Tree unstructured mesher.