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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.

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.

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.

This paper demonstrates the use of a system level model that includes torsional models of a Cummins diesel engine and an Allison transmission to study and improve system NVH behavior. The study is a case where the two suppliers of key powertrain components, Cummins Inc. and Allison Transmission Inc., have collaborated to solve an observed NVH problem for a vehicle customer. A common commercial tool, Siemens' AMESim, was used to develop the drivetrain torsional system model. This paper describes a method of modelling and calibration of baseline engine and transmission models to identify the source of vibration. Natural frequencies, modal shapes, and forced response were calculated for each vehicle drive gear ratio to study the torsional vibration. Several parametric studies such as damping, inertia, and stiffness were carried out to understand their impact on torsional vibration of the system.

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 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.

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.

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.

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.

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.

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.

Optimizing the performance of the aftertreatment system used on heavy duty diesel engines requires a thorough understanding of the operational characteristics of the individual components. Within this, understanding the performance of the catalyzed particulate filter (CPF), and the development of an accurate CPF model, requires knowledge of the particulate matter (PM) distribution throughout the substrate. Experimental measurements of the PM distribution provide the detailed interactions of PM loading, passive oxidation, and active regeneration. Recently, a terahertz wave scanner has been developed that can non-destructively measure the three dimensional (3D) PM distribution. To enable quantitative comparisons of the PM distributions collected under different operational conditions, it is beneficial if the results can be discussed in terms of the axial, radial, and angular directions.

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.

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.

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 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.