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The Particle Number–Portable Emission Measurement System (PN-PEMS) came into force with Euro VI Phase E regulations starting January 1, 2022. However, positive ignition (PI) engines must comply from January 1, 2024. The delay was due to the unavailability of the PN-PEMS system that could withstand high concentrations of water typically present in the tailpipe (TP) of CNG vehicles, which was detrimental to the PN-PEMS systems. Thus, this study was designed to evaluate the condensation particle counter (CPC)-based PN-PEMS measurement capabilities that was upgraded to endure high concentration of water. The PN-PEMS measurement of solid particle number (SPN23) greater than 23 nm was compared against the laboratory-grade PN systems in four phases. Each phase differs based upon the PN-PEMS and PN system location and measurements were made from three different CNG engines. In the first phase, systems measured the diluted exhaust through constant volume sampler (CVS) tunnel.

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).

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.

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.

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.

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.

The application of cooperative adaptive cruise control (CACC) to heavy-duty trucks known as truck platooning has shown fuel economy improvements over test track ideal driving conditions. However, there are limited test data available to assess the performance of CACC under real-world driving conditions. As part of the Cummins-led U.S. Department of Energy Funding Opportunity Announcement award project, truck platooning with CACC has been tested under real-world driving conditions and the results are presented in this paper. First, real-world driving conditions are characterized with the National Renewable Energy Laboratory’s Fleet DNA database to define the test factors. The key test factors impacting long-haul truck fuel economy were identified as terrain and highway traffic with and without advanced driver-assistance systems (ADAS).

The present study examines the impact of using low thermal mass (LTM) turbine housing designs on the transient characteristics of the turbine outlet temperature for a light-duty diesel standard certification cycle (FTP75). For a controlled exhaust flow, the turbine outlet temperature will directly determine the impact on an aftertreatment system warm-up from a cold state, typical of engine-off and engine idling conditions. The performance of the aftertreatment system such as a Selective Catalytic Reduction (SCR) system is highly dependent on how quickly it warms up to its desirable temperature to be able to convert the harmful oxides of Nitrogen (NOx) to gaseous Nitrogen. Previous works have focused on mostly insulating the exhaust manifold and turbine housing to conserve the heat going into the aftertreatment system. The use of LTM turbine housing has not been previously considered as a means for addressing this requirement.

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.

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 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.

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.

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.

Effective control of exhaust emissions from modern diesel engines requires the use of aftertreatment systems. Elevated aftertreatment component temperatures are required for engine-out emissions reductions to acceptable tailpipe limits. Maintaining elevated aftertreatment components temperatures is particularly problematic during prolonged low speed, low load operation of the engine (i.e. idle, creep, stop and go traffic), on account of low engine-outlet temperatures during these operating conditions. Conventional techniques to achieve elevated aftertreatment component temperatures include delayed fuel injections and over-squeezing the turbocharger, both of which result in a significant fuel consumption penalty. Cylinder deactivation (CDA) has been studied as a candidate strategy to maintain favorable aftertreatment temperatures, in a fuel efficient manner, via reduced airflow through the engine.

Automotive timing gear trains, transmission gearboxes, and wind turbine gearboxes are some of the application examples known to use interference-fit to attach the gear to the rotating shaft. This paper discusses the interference-fit joint design and the finite element analysis to demonstrate the distortion. The mechanism of tooth profile distortion due to the interference-fit assembly in gear trains is discussed by demonstrating the before and after assembly gear profile measurements. An algorithm to calculate the profile slope deviation change is presented. The effectiveness of the computational algorithm to predict the distortion is demonstrated by comparing with measurements. Finally, steps to mitigate the interference assembly effects are discussed.

Engine noise is one of the significant aspects of product quality for light and medium duty diesel engine market applications. Gear whine is one of those noise issues, which is considered objectionable and impacts the customer’s perception of the product quality. Gear whine could result due to defects in the gear manufacturing process and/or due to inaccurate design of the gear macro and micro geometry. The focus of this technical paper is to discuss gear whine considerations from the production plant perspective. This includes quick overview of the measurement process, test cell environment, noise acceptance criteria considerations. A gear whine case study is presented based on the data collected in the test cell at the engine plant. Gear whine data acquired on current product and next generation of prototype engines is analyzed and presented. This paper concludes by highlighting the lessons learned from the case study.

Commercial Cu-Zeolite SCR catalyst can store and subsequently release significant amount of H2O. The process is accompanied by large heat effects. It is critical to model this phenomenon to design aftertreatment systems and to provide robust tuning strategies to meet cold start emissions and low temperature operation. The complex reaction mechanism of water adsorption and desorption over a Cu-exchanged SAPO-34 catalyst at low temperature was studied through steady state and transient experiments. Steady state isotherms were generated using a gravimetric method and then utilized to predict water storage interactions with respect to feed concentration and catalyst temperature. Transient temperature programmed desorption (TPD) experiments provided the kinetic information required to develop a global kinetic model from the experimental data. The model captures fundamental characteristics of water adsorption and desorption accompanied by the heat effects.