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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.

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.

Cooled EGR continues to be a key technology to meet emission regulations, with EGR coolers performing a critical role in the EGR system. Designing EGR coolers that reliably manage thermal loads is a challenge with thermal fatigue being a top concern. The ability to estimate EGR cooler thermal fatigue life early in the product design and validation cycle allows for robust designs that meet engine component reliability requirements and customer expectations. This paper describes a process to create an EGR cooler thermal fatigue life model. Components which make up the EGR cooler have differing thermal responses, consequently conjugate transient CFD must be used to accurately model metal temperatures during heating and cooling cycles. Those metal temperatures are then imported into FEA software for structural analysis. Results from both the CFD and FEA are then used in a simplified numerical model to estimate the virtual strain of the EGR cooler.

Simulations used to estimate carbon dioxide (CO2) emissions and fuel consumption of medium- and heavy-duty vehicles over prescribed drive cycles often employ engine fuel maps consisting of engine measurements at numerous steady-state operating conditions. However, simulating the engine in this way has limitations as engine controls become more complex, particularly when attempting to use steady-state measurements to represent transient operation. This paper explores an alternative approach to vehicle simulation that uses a “cycle average” engine map rather than a steady state engine fuel map. The map contains engine CO2 values measured on an engine dynamometer on cycles derived from vehicle drive cycles for a range of generic vehicles. A similar cycle average mapping approach is developed for a powertrain (engine and transmission) in order to show the specific CO2 improvements due to powertrain optimization that would not be recognized in other approaches.

A 1-dimensional analytic solution has been developed to evaluate the pressure drop and filtration performance of ceramic wall-flow partial diesel particulate filters (PFs). An axially resolved mathematical model for the static pressure and velocity profiles prevailing inside wall-flow filters, with such unique plugging configurations, is being proposed for the first time. So far, the PF models that have been developed are either iterative/numerical in nature [1], or based on commercial CFD packages [7]. In comparison, an analytic solution approach is a transparent and computationally inexpensive tool that is capable of accurately predicting trends as well as, offering explanations to fundamental performance behavior. The simple mathematical expressions that have been obtained facilitate rational decision-making when designing partial filters, and could also reduce the complexity of OBD logic necessary to control onboard filter performance.

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.

Over the last two decades, global emission regulations have become more stringent and have required the use of more advanced fuel injection systems. This includes the use of tighter tolerances, more rapid injections and internal components actuated by weaker injection forces. Unfortunately, these design features make the entire system more susceptible to fuel contaminants. Over the last six years, the composition of these contaminants has evolved from hard insoluble debris, such as dust and rocks, to soluble chemical contaminants. Recent research by the diesel engine manufacturers, fuel injection equipment suppliers and the fuel and fuel additive industry has discovered a major source of the soluble chemical contaminant that leads to injector deposits to be derived from cost effective and commonly used additives used to protect against pipeline corrosion.

A head gasket is a component that sits between the engine block/liner and cylinder head(s) in an internal combustion engine. Its purpose is to seal high pressure combustion gasses in the cylinders and to seal coolant and engine oil. It is the most critical sealing application in an engine. As a general practice, the load deflection(L/D) characteristic is generated by the gasket manufacturer for edge molded or composite gasket types. However, in the case of a solid-sheet metallic gasket, where the gasket is expected to undergo localized yielding to provide adequate conformance and sealing, usually supplier may not be able to provide the required L/D curve due to difficulties to experimentally separate the large loads and small displacements from the elastic loads and deflections of the experimental apparatus. In absence of L/D curve, the typical analysis approach is to model gasket as 3D continuum elements available in ansys by considering nonlinear material and frictional contacts.

In previous publications, Singh et al. [1, 2] have shown that direct integration of CFD with a detailed chemistry auto-ignition model (KIVA-CHEMKIN) performs reasonably well for predicting combustion, emissions, and flame structure for stratified diesel engine operation. In this publication, it is shown that the same model fails to predict combustion for partially premixed dual-fuel engines. In general, models that account for chemistry alone, greatly under-predict cylinder pressure. This is shown to be due to the inability of such models to simulate a propagating flame, which is the major source of heat release in partially premixed dual-fuel engines, under certain operating conditions. To extend the range of the existing model, a level-set-based, hybrid, auto-ignition/flame-propagation (KIVA-CHEMKIN-G) model is proposed, validated and applied for both stratified diesel engine and partially premixed dual-fuel engine operation.

This paper presents the business purpose, software architecture, technology integration, and applications of the Cummins Vehicle Mission Simulation (VMS) software. VMS is the value-based analysis tool used by the marketing, sales, and product engineering functions to simulate vehicle missions quickly and to gauge, communicate, and improve the value proposition of Cummins engines to customers. VMS leverages the best of software architecture practices and proven technologies available today. It consists of a close integration of MATLAB and Simulink with Java, XML, and JDBC technologies. This Windows compatible application software uses stand-alone mathematical models compiled using Real Time Workshop. A built-in MySQL database contains product data for engines, driveline components, vehicles, and topographic routes. This paper outlines the database governance model that facilitates effective management, control, and distribution of engine and vehicle data across the enterprise.

Based on our error budget analysis, the urea SCR aftertreatment system is uncontrollable under EPA 2007-emission level without an effective closed-loop control strategy. The objective of the closed-loop control is to improve transient response as well as reduce the steady state control error. But the inherent large dead time in the urea SCR aftertreatment system makes the closed-loop control a challenge. In this paper, an innovative closed-loop control architecture is introduced, which combines model-based feedforward control with variable gain-scheduling feedback control. Transient response is improved with the inverse-dynamic feedforward control and the variable-gain closed-loop control. The steady-state response is improved with the closed-loop control. Based on this new strategy, a controller is designed and validated under the simulation and test cell environment. Comparison with the baseline open-loop controller is also conducted. Finally, some conclusions are presented.

Wideband Acoustical Holography (WBH), which is a monopole-based, equivalent source procedure (J. Hald, “Wideband Acoustical Holography,” INTER-NOISE 2014), has proven to offer accurate noise source visualization results in experiments with a simple noise source: e.g., a loudspeaker (T. Shi, Y. Liu, J.S. Bolton, “The Use of Wideband Holography for Noise Source Visualization”, NOISE-CON 2016). From a previous study, it was found that the advantage of this procedure is the ability to optimize the solution in the case of an under-determined system: i.e., when the number of measurements is much smaller than the number of parameters that must be estimated in the model. In the present work, a diesel engine noise source was measured by using one set of measurements from a thirty-five channel combo-array placed in front of the engine.

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.

Development of quick and efficient numerical tools is key to the design of industrial machines. While Computational Fluid Dynamics (CFD) techniques based on Navier Stokes (N-S) and Lattice Boltzman methods are becoming popular, predicting aeroacoustic behavior for complex geometries remains computationally intensive for design process and iteration. The goal of this paper is to evaluate application Navier-Stokes approach coupled with Ffowcs Williams and Hawkings (FW-H), and Broad-band Noise Model (BNS) to evaluate noise levels and predict design direction for industrial applications. Steady-state RANS based approaches are used to evaluate under-hood cooling performance and fan power demand. At each design iteration, noise levels and strength of noise source are evaluated using Gutin’s and broad-band noise models, respectively along with cooling performance. Each design feature selected for the final design has lower fan power and noise level with improved cooling.

The aging impact on oxygen storage capacity (OSC) and catalyst performance was investigated on one degreened and one aged (hydrothermally aged at 955 °C for 50 h) commercial three-way catalyst (TWC) by experiments and modeling. The difference of OSC between the degreened and aged TWCs was dependent on catalyst temperature. The largest difference was found at 600 °C, at which the amount of OSC decreased by 45.5%. Catalyst performance was evaluated through lightoff tests at two simulated engine exhaust conditions (lean and rich) on a micro-reactor. The aging impact on the catalyst performance was different under lean and rich environments and investigated separately. At the lean condition, oxidation of CO and C3H6 was significantly suppressed while oxidation of C3H8 was relatively less degraded. At the rich condition, the inhibition effect was more pronounced on the aged TWC and inhibiting hydrocarbon species from C3H6 partial oxidation can survive at temperatures up to 450 °C.

This paper presents an experimental setup and an equivalent FEM simulation methodology to accurately predict the response of Engine Control Module (ECM) assembly mounted on a commercial vehicle subjected to road vibrations. Comprehensive vibration study is carried out. It involved Modal characteristics determination followed by random vibration characterization of the ECM assembly. A hammer impact experiment is first performed in lab to estimate the natural frequencies and mode shapes of ECM assembly. Mounting conditions in test specimen are kept similar to the actual mounting settings on vehicle. Natural frequencies and mode shapes predicted from free vibration experiment are compared with finite element (FE) based modal analysis. The importance of capturing the assembly stiffness more accurately by incorporating pre-stress effects like bolt-pretension and gravity, is emphasized.

Accurate estimation of catalyst bed temperatures is very crucial for effective control and diagnostics of aftertreatment systems. The architecture of most aftertreatment systems contains temperature sensors for measuring the exhaust gas temperatures at the inlet and outlet of the aftertreatment systems. However, the temperature that correctly reflects the temperature of the chemical reactions taking place on the catalyst surface is the catalyst bed temperature. From the Arrhenius relationship which governs the chemical reaction kinetics occurring in different aftertreatment systems, the rate of chemical reaction is very sensitive to the reaction temperature. Considerable changes in tailpipe emissions can result from small changes in the reaction temperature and robust emissions control systems should be able to compensate for these changes in reaction temperature to achieve the desired tailpipe emissions.

Dynamometer (dyno) durability testing plays a significant role in reliability and durability assessment of commercial engines. Frequently, durability test procedures are based on warranty history and corresponding component failure modes. Evolution of engine designs, operating conditions, electronic control features, and diagnostic limits have created challenges to historical-based testing approaches. A physics-based methodology, known as Load Matrix, is described to counteract these challenges. The technique, developed by AVL, is based on damage factor models for subsystem and component failure modes (e.g. fatigue, wear, degradation, deposits) and knowledge of customer duty cycles. By correlating dyno test to field conditions in quantifiable terms, such as customer equivalent miles, more effective and efficient durability test suites and test procedures can be utilized. To this end, application of Load Matrix to a heavy-duty diesel engine is presented.

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.