Search Results

The thermal performance of an engine coolant system is efficient when the engine head temperature is maintained within its optimum working range. For this, it is desired that air should not be entrapped in the coolant system which can lead to localized hot spots at critical locations. However, it is difficult to eliminate the trapped air pockets completely. So, the target is to minimize the entrapped air as much as possible during the coolant filling and deaeration processes, especially in major components such as the radiator, engine head, pump etc. The filling processes and duration are typically optimized in an engine test stand along with design changes for augmenting the coolant filling efficiency. However, it is expensive and time consuming to identify air entrapped locations in tests, decide on the filling strategy and make the design changes in the piping accordingly.

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.

Commercial automotive diesel engine service and repair, post a diagnostic trouble code trigger, relies on standard troubleshooting steps laid down to identify or narrow down to a faulty engine component. This manual process is cumbersome, time-taking, costly, often leading to incorrect part replacement and most importantly usually associated with significant downtime of the vehicle. Current study aims to address these issues using a novel in-house simulation-based approach developed using a Digital Twin of the engine which is capable of conducting in-mission troubleshooting with real world vehicle/engine data. This cost-effective and computationally efficient solution quickly provides the cause of the trouble code without having to wait for the vehicle to reach the service bay. The simulation is performed with a one-dimensional fluid dynamics, detailed thermodynamics and heat transfer-based diesel engine model utilizing the GT-POWER engine performance tool.

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.

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.

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.

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.

With the capability of avoiding failure in advance, failure prediction model is important not only to end users, but also to the service engineers in vehicle industry. This paper proposes an approach based on anomaly detection algorithms and telematic data to predict the failure of the engine air system with Turbo charger. Firstly, the relationship between air system and all obtained features are analyzed by both physical mechanism and data-wise. Then, the features including altitude, air temperature, engine output power, and charger pressure are selected as the input of the model, with the sampling interval of 1 minute. Based on the selected features, the healthy state for each vehicle is defined by the model as benchmark. Finally, the ‘Medium surface’ is determined for specific vehicle, which is a hyperplane with the medium points of the healthy state located at, to detect the minor weakness symptom (sub-health state).

Measuring axial exhaust species concentration distributions within a wall-flow aftertreatment device provides unique and significant insights regarding the performance of complex devices like the SCR-on-filter. In this particular study, a less complex aftertreatment configuration which includes a DOC followed by two uncoated partial flow filters (PFF) was used to demonstrate the potential and challenges. The PFF design in this study was a particulate filter with alternating open and plugged channels. A SpaciMS [1] instrument was used to measure the axial NO2 profiles within adjacent open and plugged channels of each filter element during an extended passive regeneration event using a full-scale engine and catalyst system. By estimating the mass flow through the open and plugged channels, the axial soot load profile history could be assessed.

The majority of commercial diesel engines rely on EGR to meet increasingly stringent emissions standards, creating a potential issue for military applications that use JP-8 as a fuel. EGR components would be susceptible to corrosion from sulfur in JP-8, which can reach levels of 3000 ppm. Starting with a Cummins 2007 ISL 8.9L production engine, modifications to remove EGR and operate on JP-8 fuel are investigated with a key goal of demonstrating 48% brake thermal efficiency (BTE) at an emissions level consistent with 1998 EPA standards. The effects of injector cup flow, improved turbo match, increased compression ratio with revised piston bowl geometry, increased cylinder pressure, and revised intake manifold for improved breathing, are all investigated. Testing focused on a single operating point, full load at 1600 RPM. This engine uses a variable geometry turbo and high pressure common rail fuel system, allowing control over air fuel ratio, rail pressure, and start of injection.

This paper describes the methodology used to select an application-based fan that has optimum operating characteristics in terms of cooling air flow rate, fan power, and noise. The selected fan is then evaluated for structural strength. To evaluate different fans, complete rail coach under-hood simulations were carried out using steady-state 3D computational fluid dynamics (CFD) approach. These simulations considered an actual, highly non-uniform flow field. For each fan option, fan power, air flow rate, and surface acoustic power was evaluated. Pressure profiles on the fan blades were studied to assess the effect of non-uniform downstream air passage designs. Surface acoustic power was calculated using broadband noise source (BNS) model in ANSYS Fluent®. Surface pressure profiles over fan blades imported from 3D CFD were used in finite element analysis (FEA) in ANSYS. Analyses were carried out for blade linear and non-linear properties.

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.

Diesel engine cylinder deactivation (CDA) can be used to reduce petroleum consumption and greenhouse gas (GHG) emissions of the global freight transportation system. Heavy duty trucks require complex exhaust aftertreatment (A/T) in order to meet stringent emission regulations. Efficient reduction of engine-out emissions require a certain A/T system temperature range, which is achieved by thermal management via control of engine exhaust flow and temperature. Fuel efficient thermal management is a significant challenge, particularly during cold start, extended idle, urban driving, and vehicle operation in cold ambient conditions. CDA results in airflow reductions at low loads. Airflow reductions generally result in higher exhaust gas temperatures and lower exhaust flow rates, which are beneficial for maintaining already elevated component temperatures. Airflow reductions also reduce pumping work, which improves fuel efficiency.

A spread sheet based parametric tool is developed to design the base frame for a marine generator-set. Factors such as engine details, generator details, anti-vibration mount (AVM) etc., that determine the design of the base frame, are set as parameters in the spreadsheet. The spreadsheet has formulae to calculate channel specifications, and AVM deflections. It is linked to channel standards database and selects the optimal channel based on calculations. Similarly, the tool provides guidance in selection of AVM from supplier catalogues, helps to predict number of anti-vibration mounts required and their location on base frame. This spread sheet is integrated with a generic base frame 3D model and 2D print in “Creo 3d modelling software” (Creo), which is auto-updated based on calculated parameters in the spreadsheet. Using this tool, the user can generate a 3D-model and 2D print. This tool helps to standardize the design process and reduces design turnaround time considerably.

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.

An existing pass by noise data acquisition system was upgraded to provide the sophisticated data analysis techniques and test site efficiency required to comply with the current and future drive by noise regulations. Use of six sigma tool such as voice of the customer helped in defining the customer requirements which were then translated into the desired engineering characteristics using QFD. Pugh concept matrix narrowed down the best option suitable for the test site modifications taking into account the critical constraints such as test complexity, system cost & transparency to the existing drive by noise setup. Features of the new system include data telemetry, frequency analysis, portability and efficient data management through the use of advanced data acquisition system. Wireless mode of the data transmission helped significantly avoid most of the test site modifications, which in turn helped to reduce the overall system implementation cost.

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.

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.

The prediction accuracy of a three-way catalyst (TWC) model is highly associated with the ability of the model to incorporate the reaction kinetics of the emission process as a lambda function. In this study, we investigated the O2 and H2 concentration profiles of TWC reactions and used them as critical inputs for the development of a global TWC model. We presented the experimental data and global kinetic model showing the impact of thermal degradation on the performance of the TWC. The performance metrics investigated in this study included CH4, NOx, and CO conversions under lean, rich, and dithering light-off conditions to determine the kinetics of oxidation reactions and reduction/reforming/water-gas shift reactions as a function of thermal aging. The O2 and H2 concentrations were measured using mass spectrometry to track the change in the oxidation state of the catalyst and to determine the mechanism of the reactions under these light-off conditions.

Countries around the world are expected to continue to adopt more stringent emissions standards for heavy-duty markets for both oxides of nitrogen (NOx) and greenhouse gases (GHG). While there is uncertainty about the timing and extent of these regulations, it is clear that significant reductions will be required to address urban air pollution and climate change concerns. The rate and pace of technology evolution and how it will affect the energy pathways for commercial transportation and industrial use are dependent on multiple variables such as national energy and environmental policies and public-private partnerships. Although it adds complexity, the engine system has great potential to evolve as it continues to be highly integrated into the super system for which it is producing power. This paper examines the potential opportunities and challenges for engine manufacturers to continue to be the supplier of power to vehicles and equipment of the future.