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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.

Diesel engines are far more efficient than gasoline engines of comparable size, and emit less greenhouse gases that have been implicated in global warming. In 2000, the US EPA proposed very stringent emissions standards to be introduced in 2007 along with low sulfur (< 15 ppm) diesel fuel. The California Air Resource Board (CARB) has also established the principle that future diesel fueled vehicles should meet the same low emissions standards as gasoline fueled vehicles and the EPA followed suit with its Tier II emissions regulation. Achieving such low emissions cannot be done through engine development and fuel reformulation alone, and requires application of NOx and particulate matter (PM) aftertreatment control devices. There is a widespread consensus that NOx adsorbers and particulate filter are required in order for diesel engines to meet the 2007 emissions regulations for NOx and PM. In this paper, the key exhaust characteristics from an advanced diesel engine are reviewed.

This oil category was driven by two new cooled exhaust gas recirculation (EGR) engine tests operating with 15% EGR, with used oil soot levels at the end of the test ranging from 6 to 9%. These tests are the Mack T-10 and Cummins M11 EGR, which address ring, cylinder liner, bearing, and valve train wear; filter plugging, and sludge. In addition to these two new EGR tests, there is a Caterpillar single-cylinder test without EGR which measures piston deposits and oil consumption control using an articulated piston. This test is called the Caterpillar 1R and is included in the existing Global DHD-1 specification. In total, the API CI-4 category includes eight fired-engine tests and seven bench tests covering all the engine oil parameters. The new bench tests include a seal compatibility test for fresh oils and a low temperature pumpability test for used oils containing 5% soot. This paper provides a review of the all the tests, matrix results, and limits for this new oil category.

Future light duty vehicles in the United States are required to be certified on the FTP-75 cycle to meet Tier 3 or LEV III emission standards [1, 2]. The cold phase of this cycle is heavily weighted and mitigation of emissions during this phase is crucial to meet the low tail pipe emission targets [3, 4]. In this work, a novel aftertreatment architecture and controls to improve Nitrogen Oxides (NOx) and Hydrocarbon (HC) or Non Methane Organic gases (NMOG) conversion efficiencies at low temperatures is proposed. This includes a passive NOx & HC adsorber, termed the diesel Cold Start Concept (dCSC™) catalyst, followed by a Selective Catalytic Reduction catalyst on Filter (SCRF®) and an under-floor Selective Catalytic Reduction catalyst (SCR). The system utilizes a gaseous ammonia delivery system capable of dosing at two locations to maximize NOx conversion and minimize parasitic ammonia oxidation and ammonia slip.

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.

Cummins Westport Inc. (CWI) released for production the latest version of its C8.3G natural gas engine, the C Gas Plus, in July 2001. This engine has increased ratings for horsepower and torque, a full-authority engine controller, wide tolerance to natural gas fuel (the minimum methane number is 65), and improved diagnostics capability. The C Gas Plus also meets the California Air Resources Board optional low-NOx (2.0 g/bhp-h) emission standard for automotive and urban buses. Two pre-production C Gas Plus engines were operated in a Viking Freight fleet for 12 months as part of the U.S. Department of Energy's Fuels Utilization Program. In-use exhaust emissions, fuel economy, and fuel cost were collected and compared with similar 1997 Cummins C8.3 diesel tractors. CWI and the West Virginia University developed an ad-hoc test cycle to simulate the Viking Freight fleet duty cycle from in-service data collected with data loggers.

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.

Production PM sensors are now available and are likely to be key components of PM aftertreatment systems designed to meet 2013 OBD requirements. In this paper a highly simplified analysis is used to give insight into the sensor response of resistive-based devices, and to motivate possible diagnostic strategies. The method has been applied to successive sets of FTP data recorded with DPF's of different failure levels, and despite the very approximate nature of the underlying model, the method appears to discriminate reliably between them.

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).

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.

Euro VI regulations in Europe and its adaptors recently extended the regulation to include Particle Number (PN) for in-use conformity testing. However, the in-use PN Portable Emissions Measurement System (PEMS) is still evolving and has higher measurement uncertainty when compared against laboratory-grade PN systems. The PN systems for laboratory require a condensation particle counter (CPC). Thus, in this study, a CPC-based Horiba PN-PEMS was selected for performance evaluation against the laboratory-grade PN systems. This study was divided into four phases. The first two phases’ measurements were conducted from the Constant Volume Sampler (CVS) tunnel where the brake-specific particle number (BSPN) levels of 1010-12 and 1013 (#/bhp-h) were measured from the engines equipped with diesel particulate filter (DPF) and without DPF, respectively. In comparison against PN systems, PN-PEMS, on average, reported 14% lower BSPN from 82 various tests for the BSPN levels of 1010-11.

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.

Government agencies like EPA play an important role through regulation to reduce emissions and fuel consumption and to drive technological developments to reduce the environmental impact of burning petroleum fuels. Emissions testing and control is one of the leading and growing fields in the development of modern vehicles. Recently, Cummins Emissions Solutions (CES) and Southwest Research Institute (SwRI) worked jointly in order to achieve a method to conduct emissions testing efficiently and effectively. The collaborative work between the two organizations led to the usage of FOCAS HGTR™ (a diesel-based burner test rig at SwRI) to simulate the exhaust conditions generated by a 2010 ISX Cummins production engine operating over an EPA standard Ramped Modal Cycle Supplemental Emissions Test (RMC SET) cycle.

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.