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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.

The rollover threshold for a partially filled tanker truck carrying fluid cargo is of great importance due to the catastrophic nature of accidents involving such vehicles, particularly when payloads are toxic and flammable. In this paper, a method for determining the threshold of rollover stability of a specific tanker truck is presented using finite element analysis methods. This approach allows the consideration of many variables which had not been fully incorporated in past models, including nonlinear spring behavior and tank flexibility. The program uses simple mechanical pendulums to simulate the fluid sloshing affects, beam elements to match the torsional and bending stiffness of the tank, and spring damper elements to simulate the suspension. The finite element model of the tanker truck has been validated using data taken by the U.S. Army Aberdeen Test Center (ATC) on a M916A1 tractor/ Etnyre model 60PRS 6000 gallon trailer combination.

A quasi-dimensional model for a direct injection diesel engine was developed based on experiments at Sandia National Laboratory. The Sandia researchers obtained images describing diesel spray evolution, spray mixing, premixed combustion, mixing controlled combustion, soot formation, and NOx formation. Dec [1] combined all of the available images to develop a conceptual diesel combustion model to describe diesel combustion from the start of injection up to the quasi-steady form of the jet. The end of injection behavior was left undescribed in this conceptual model because no clear image was available due to the chaotic behavior of diesel combustion. A conceptual end-of-injection diesel combustion behavior model was developed to capture diesel combustion throughout its life span. The compression, expansion, and gas exchange stages are modeled via zero-dimensional single zone calculations.

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.

New York City Department of Sanitation has operated natural gas fueled refuse haulers in a pilot study: a major goal of this study was to compare the emissions from these natural gas vehicles with their diesel counterparts. The vehicles were tandem axle trucks with GVW (gross vehicle weight) rating of 69,897 pounds. The primary use of these vehicles was for street collection and transporting the collected refuse to a landfill. West Virginia University Transportable Heavy Duty Emissions Testing Laboratories have been engaged in monitoring the tailpipe emissions from these trucks for seven-years. In the later years of testing the hydrocarbons were speciated for non-methane and methane components. Six of these vehicles employed the older technology (mechanical mixer) Cummins L-10 lean burn natural gas engines.

The paper discusses the benefits of a four stroke engine having one intake and one exhaust rotary valve. The rotary valve has a speed of rotation half the crankshaft and defines an open passage that may permit up to extremely sharp opening or closing and very large gas exchange areas. The dual rotary valve design is applied to a racing engine naturally aspirated V-four engine of 1000cc displacement, gasoline fuelled with central direct injection and spark ignition. The engine is then modeled by using a 1D engine & gas dynamics simulation software package to assess the potentials of the solution. The improved design produces much larger power densities than the version of the engines with traditional poppet valves revving at higher speeds, with reduced frictional losses, and with larger gas exchange areas while also improving the fuel conversion efficiency thanks to the sharpness of opening or closing events.

Hydrogen Internal Combustion Engine (ICE) vehicles using a traditional ICE that has been modified to use hydrogen fuel are an important mid-term technology on the path to the hydrogen economy. Hydrogen-powered ICEs that can run on pure hydrogen or a blend of hydrogen and compressed natural gas (CNG) are a way of addressing the widespread lack of hydrogen fuelling infrastructure in the near term. Hydrogen-powered ICEs have operating advantages as all weather conditions performances, no warm-up, no cold-start issues and being more fuel efficient than conventional spark-ignition engines. The Wankel engine is one of the best ICE to be converted to run hydrogen. The paper presents some details of an initial investigation of the CAD and CAE modeling of a novel design where two jet ignition devices per rotor are replacing the traditional two spark plugs for a faster and more complete combustion.

Until a proper fueling infrastructure is established, vehicles powered by natural gas must have bi-fuel capability in order to avoid a limited vehicle range. Although bi-fuel conversions of existing gasoline engines have existed for a number of years, these engines do not fully exploit the combustion and knock properties of both fuels. Much of the power loss resulting from operation of an existing gasoline engine on compressed natural gas (CNG) can be recovered by increasing the compression ratio, thereby exploiting the high knock resistance of natural gas. However, gasoline operation at elevated compression ratios results in severe engine knock. The use of variable intake valve timing in conjunction with ignition timing modulation and electronically controlled exhaust gas recirculation (EGR) was investigated as a means of controlling knock when operating a bi-fuel engine on gasoline at elevated compression ratios.

Machine learning models were shown to provide faster results but with similar accuracy to multidimensional computational fluid dynamics or in-depth experiments. This study used a support-vector machine (SVM), a set of related supervised learning methods, to predict the dynamic performance (i.e., engine power and torque) of a heavy-duty natural gas spark ignition engine. The single-cylinder four-stroke test engine was fueled with methane. The engine was operated at different spark timings, mixture equivalence ratios, and engine speeds to provide the data for training and testing the proposed SVM. The results indicated that the performance and accuracy of the built regression model were satisfactory, with correlation coefficient quantities all larger than 0.95 and root-mean-square errors close to zero for both training and validation datasets.

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.

Diesel particulate filters (DPFs) are recognized as the most efficient technology for particulate matter (PM) reduction, with filtration efficiencies in excess of 90%. Design guidelines for DPFs typically are: high removal efficiency, low pressure drop, high durability and capacity to resist high temperature excursions during regeneration events. The collected mass inside the trap needs to be periodically oxidized to regenerate the DPF. Thus, an in-depth understanding of filtration and regeneration mechanisms, together with the ability of predicting actual DPF conditions, could play a key role in optimizing the duration and number of regeneration events in case of active DPFs. Thus, the correct estimation of soot loading during operation is imperative for effectively controlling the whole engine-DPF assembly and simultaneously avoidingany system failure due to a malfunctioning DPF. A viable way to solve this problem is to use DPF models.

Safety, fuel economy and uptime are key requirements for the operation of heavy-duty line-haul trucks within a fleet. With the penetration of connectivity and automation technologies, energy optimal and safe operation of the trucks are further improved through Advanced Driver Assistance System (ADAS) features and automated technologies as in truck platooning. Understanding the braking capability of the vehicle is very important for optimal ADAS and platooning control system design and integration. In this paper, the importance of tire connectivity and tire conditions on truck stopping distance are demonstrated through testing. The test data is further utilized to develop tire models for integration in an optimal vehicle automation for platooning. New ways to produce and use the tire related information in real-time optimal control of platooning trucks are proposed and the contribution of tire information in fuel economy is quantified through simulations.

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).

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.

The objective of this project, which is supported by the U.S. Department of Energy (DOE) through the National Renewable Energy Laboratory (NREL), is to provide a comprehensive comparison of heavy-duty trucks operating on alternative fuels and diesel fuel. Data collection from up to eight sites is planned. This paper summarizes the design of the project and early results from the first two sites. Data collection is planned for operations, maintenance, truck system descriptions, emissions, duty cycle, safety incidents, and capital costs and operating costs associated with the use of alternative fuels in trucking.

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.

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.

In the early years of antifreeze/coolants (1920s & 30s) glycerin saw some usage, but because of higher cost and weaker freeze point depression, it was not competitive with ethylene glycol. Glycerin is a by-product of the manufacture of biodiesel (fatty acid methyl esters) made by reacting natural vegetable or animal fats with methanol. Biodiesel fuel is becoming increasingly important and is expected to gain a large market share in the next several years. Regular diesel fuels blended with 2%, 5%, and 20% biodiesel are now commercially available. The large amount of glycerin generated from high volume usage of biodiesel fuel has resulted in this chemical becoming cost competitive with the glycols currently used in engine coolants. For this reason, and lower toxicity comparable to that of propylene glycol, glycerin deserves to be reconsidered as a base for antifreeze/coolant.