Search Results

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.

Internal combustion engines will continue to be the leading power-train in the heavy-duty, on-highway sector as technologies like hydrogen, fuel cells, and electrification face challenges. Natural gas (NG) engines offer several advantages over diesel engines including near zero particle matter (PM) emissions, lower NOx emissions, lower capital and operating costs, availability of vast domestic NG resources, and lower CO2 emissions being the cleanest burning of all hydrocarbons (HC). The main limitation of this type of engine is the lower efficiency compared to diesel counterparts. Addressing the limitations (knock and misfire) for achieving diesel-like efficiencies is key to accomplishing widespread adoption, especially for the US market. With the aim to achieve high brake thermal efficiency (BTE), three (3) computational fluid dynamics (CFD) optimized pistons with three different compression ratios (CR) have been tested.

When developing and designing new technology for integrated vehicle systems deployment, standard cycles have long existed for chassis dynamometer testing and tuning of the powertrain. However, to this day with recent developments and advancements in plug-in hybrid and battery electric vehicle technology, no true “work day” cycles exist with which to tune and measure energy storage control and thermal management systems. To address these issues and in support of development of a range-extended pickup and delivery Class 6 commercial vehicle, researchers at the National Renewable Energy Laboratory in collaboration with Cummins analyzed 78,000 days of operational data captured from more than 260 vehicles operating across the United States to characterize the typical daily performance requirements associated with Class 6 commercial pickup and delivery operation.

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.

This paper investigates the aerodynamic influence of multiple on-highway trucks in different platooning configurations. Complex pressure fields are generated on the highways due to interference of multiple vehicles. This pressure field causes an aerodynamic drag to be different than the aerodynamic drag of a vehicle in a no-traffic condition. In order to study the effect of platooning, three-dimensional modeling and numerical simulations were performed using STAR-CCM+® commercial Computational Fluid Dynamics (CFD) tool. The aerodynamic characteristics of vehicles were analyzed in five different platooning configurations with two and three vehicles in single and multiple lanes. A significant Yaw Averaged Aerodynamic Drag (YAD) reduction was observed in both leading and trailing vehicles. YAD was based on the average result of three different yaw angles at 0°, −6° and 6°. In single-lane traffic, YAD reduction was up to 8% and 38% in leading and trailing vehicles, respectively.

Design of a light duty diesel for an automotive market presents contradictory challenges related to passenger car requirements for a compact, low weight design versus the diesel's base engine that must withstand cylinder pressures that are much greater than that seen on gasoline. This was a particular challenge for Cummins because of two reasons. First, design practices developed for Cummins' traditional heavy duty and industrial markets could lead to over-design, particularly for those items that have wear based life limits like bearings. Secondly, in the pursuit of new engine business it is necessary to be able to quickly yet accurately generate conceptual engine space claims for a variety of vehicle and engine specifications. When applying traditional guidelines for crank and bearing sizing, the resulting base engine size appeared an unsolvable problem relative to size and weight requirements.

Fan and fan-shroud design is critical for underhood air flow management. The objective of this work is to demonstrate a method to optimize fan-shroud shape in order to maximize cooling air mass flow rates through the heat exchangers using the Adjoint Solver in STAR-CCM+®. Such techniques using Computational Fluid Dynamics (CFD) analysis enable the automotive/transport industry to reduce the number of costly experiments that they perform. This work presents the use of CFD as a simulation tool to investigate and assess the various factors that can affect the vehicle thermal performance. In heavy-duty trucks, the cooling package includes heat exchangers, fan-shroud, and fan. In this work, the STAR-CCM+® solver was selected and a java macro built to run the primal flow and the Adjoint solutions sequentially in an automated fashion.