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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.

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.

Sulfur containing species as well as other polar molecules provide lubricity and thermal stability to diesel fuels. During the refining process to produce low and ultra-low sulfur diesel fuels, these components are removed. As a result, fuel additives such as lubricity agents and antioxidant may be added to protect fuel stability and prevent fuel pump wear. Some lubricity additives, such as dimer acids, resulted in fuel filter plugging. The plugging mechanism was related to the capability of aliphatic acids to form agglomeration by interactions with the overbased detergents, delivered into the fuel as oil contaminants. Other sources of acids, derived from thermal degradation, can lead to the same problem. In this study, individual lubricant additives were mixed in the fuel to form single- and dual-component systems. Levels of compatibility and amounts of interaction products were evaluated for individual solutions.

The interest for NOx estimators (also known as virtual sensors or inferential sensors) has increased over the recent years due to benefits attributed to cost and performance. NOx estimators are typically installed to improve On-Board Diagnostics (OBD) monitors or to lower bill of material costs by replacing physical NOx sensors. This paper presents initial development results of a virtual engine-out NOx estimator planned for the implementation on an ECM. The presented estimator consists of an airpath observer and a NOx combustion model. The role of the airpath observer is to provide input values for the NOx combustion model such as the states of the gas at the intake and exhaust manifolds. It contains a nonlinear mean-value model of the airpath suitably transformed for an efficient and robust implementation on an ECM. The airpath model uses available sensory information in the vehicle to correct predictions of the gas states.

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.

Good understanding and accurate prediction of component fatigue strength is crucial in the development of modern engine. In this paper a detail analysis was conducted on an engine component made of gray cast iron with finite element method to evaluate the fatigue strength. This component has notches that cause local stress concentration. It is well known that fatigue behavior of a notch is not uniquely defined by the local maximum stress but depends on other factors determined by notch geometry and local stress distribution. The component fatigue strength was underestimated by only considering the stresses on the notch surface for fatigue life prediction. The critical distance approach was adopted to predict the fatigue behavior of this component. Good agreements are observed between predicted life by the critical distance method and actual field data.

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.

Sustained NOx reduction at low temperatures, especially in the 150-200 °C range, shares some similarities with the more commonly discussed cold-start challenge, however, poses a number of additional and distinct technical problems. In this project, we set a bold target of achieving and maintaining 90% NOx conversion at the SCR catalyst inlet temperature of 150 °C. This project is intended to push the boundaries of the existing technologies, while staying within the realm of realistic future practical implementation. In order to meet the resulting challenges at the levels of catalyst fundamentals, system components, and system integration, Cummins has partnered with the DOE, Johnson Matthey, and Pacific Northwest National Lab and initiated the Sustained Low-Temperature NOx Reduction program at the beginning of 2015 and completed in 2017.

The influence of big-end bore fretting on connecting rod fatigue fracture is investigated. A finite element model, including rod-bearing contact interaction, is developed to simulate a fatigue test rig where the connecting rod is subjected to an alternating uniaxial load. Comparison of the model results with a rod fracture from the fatigue rig shows good correlation between the fracture location and the peak ‘Ruiz’ criterion, rather than the peak tensile stress location, indicating the potential of fretting to initiate a fatigue fracture and the usefulness of the ‘Ruiz’ criterion as a measure of location and severity. The model is extended to simulate a full engine cycle using pressure loads from a bearing EHL analysis. A fretting map and a ‘Ruiz’ criterion map are developed for the full engine cycle, giving an indication of a safe ‘Ruiz’ level from an existing engine which has been in service for more than 5 years.

The automotive industry drives some of the most stringent product requirements to ensure long product life and customer satisfaction. To demonstrate compliance with these requirements new and more accurate evaluation methods are needed. Thermal fatigue life in EGR coolers for heavy duty diesel applications have historically been a critical focus for engine OEMs. Being able to accurately evaluate product return rates due to thermal fatigue failures gives the OEM confidence that all end users will be satisfied, and allows program management to properly make fiscal decisions. Additionally, weight and cost optimization can be conducted with greater confidence. This is accomplished by accounting for product variation and application variation in thermal fatigue life evaluations. Including these variations requires a simplified numerical method to calculate product life, as tens of thousands of samples will be run through the analysis to represent real life random variation.

NVH development of light duty diesel engines require significant collaboration with the OEM as compared to medium duty and heavy duty diesel engines. Typically, competitive benchmark studies and customer expectations define the NVH targets at the vehicle level and are subsequently cascaded down to the powertrain level. For engine manufacturing companies like Cummins Inc., it is imperative to work closely with OEM to deliver on the NVH expectations. In certain situations, engine level NVH targets needs to be demonstrated in the OEM or 3rd party acoustic test facility for customer satisfaction or commercial purposes. Engine noise tests across different noise test facilities may introduce some variation due to differences in the acoustic test facilities, test hardware, instrumentation differences, etc. In addition, the engine itself is a major source of variation.

This study is a continuation of previous work assessing the robustness of a Cummins XPI common rail injection system operating with gasoline-like fuel. All the hardware from the original study was retained except for the high pressure pump head and check valves which were replaced due to cavitation damage. An additional 400 hour NATO cycle was run on the refurbished fuel system to achieve a total exposure time of 800 hours and detect any other significant failure modes. As in the initial investigation, fuel system parameters including pressures, temperatures and flow rates were logged on a test bench to monitor performance over time. Fuel and lubricant samples were taken every 50 hours to assess fuel consistency, metallic wear, and interaction between fuel and oil. High fidelity driving torque and flow measurements were made to compare overall system performance when operating with both diesel and light distillate fuel.

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.

Shafaat and Kenley in 2015 identified the opportunity to improve System Engineering Standards by incorporating the design principle of learning. The System Level Assessment (SLA) Methodology is an approach that fulfills this need by efficiently capturing the learnings of a team of subject matter experts in the early stages of product system design. By gathering expertise, design considerations are identified that when used with market and business requirements improve the overall quality of the product system. To evaluate the effectiveness of this approach, the methodology has been successfully applied over 400 times within each realm of the New Product Introduction process, including most recently to a Technology Development program (in the earliest stages of the design process) to assess the viability of various electrification technologies under consideration by an automotive Tier 1 supplier.

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).