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The characterization of fuel injector orifices is important for engine performance engineers, combustion engineers, and as input into 3-D spray and combustion simulations. Typical steady flow measurements done by fuel injector manufacturers are not indicative of their flow at engine injection pressures. Orifice characterization is commonly done on a rate bench or for further detail by using momentum rate measurements. The common Bernoulli equation assumptions made for momentum rate measurements are not always proper. This work compares the common approach with a more detailed approach for calculating the nozzle flow coefficients and sac pressure. The detailed approach includes friction and contraction pressure losses. A discussion on sac velocity is included. A non-iterative calculation of the Darcy friction factor is reviewed and an uncertainty analysis is also provided.

Selective Catalytic Reduction (SCR) is a leading aftertreatment technology for the removal of nitrogen oxide (NOx) from exhaust gases (DeNOx). It presents an interesting control challenge, especially at high conversion, because both reagents (NOx and ammonia) are toxic, and therefore an excess of either is highly undesirable. Numerous system layouts and control methods have been developed for SCR systems, driven by the need to meet future emission standards. This paper summarizes the current state-of-the-art control methods for the SCR aftertreatment systems, and provides a structured and comprehensive overview of the research on SCR control. The existing control techniques fall into three main categories: traditional SCR control methods, model-based SCR control methods, and advanced SCR control methods. For each category, the basic control technique is defined. Further techniques in the same category are then explained and appreciated for their relative advantages and disadvantages.

The United States Environmental Protection Agency’s (U.S. EPA’s) National Vehicle and Fuel Emissions Laboratory (NVFEL) has been developing new approaches for use in screening emissions from various types of new and in-use (used) engines to investigate if their exhaust emissions comply with federal emission standards. If the results from screening tests suggest anything unusual, EPA’s compliance program could investigate further to determine if that particular engine group or family should receive more rigorous compliance testing and analysis. In 2019, the EPA finished developing a means to screen the emissions of marine outboard engines, including the use of specialized equipment, laboratory methods, and procedures capable of controlling outboard marine engines to screen whether their exhaust is in line with appropriate emission standards.

An inexpensive system was designed that would allow repair shops to verify the adequacy of repairs made to cars that had previously failed the new high-tech I/M test (IM240). Before and after repair tests on a limited number of vehicles were performed with both official IM240 and prototype repair grade (RG240) equipment systems. Analyses were performed to determine if the RG240 system concept is capable of determining if the repairs performed resulted in adequate emissions reductions to assure a passing IM240 retest. This study focuses on development of a prototype RG240 system consisting of a 100 SCFM CVS, a dynamometer with an eddy current power absorber and non-adjustable 2000 pound inertia flywheel, and a BAR 90 emissions analyzer with an additional nitric oxide analyzer.

Three alternatives to internal combustion vehicles currently being researched, developed, and commercialized are electric, hybrid electric, and fuel-cell vehicles. A total life-cycle inventory for an alternative vehicle must include factors such as the impacts of car body materials, tires, and paints. However, these issues are shared with gasoline-powered vehicles; the most significant difference between these vehicles is the power source. This paper focuses on the most distinct and challenging aspect of alternative-fuel vehicles, the power sources. The life-cycle impacts of battery systems for electric and hybrid vehicles are assessed. Less data is publicly available on the fuel cell; however, we offer a preliminary discussion of the environmental issues unique to fuel cells. For each of these alternative vehicles, a primary environmental hurdle is the consumption of materials specific to the power sources.

The ability to accurately predict exhaust system acoustics, including transmission loss (TL) and tailpipe noise, based on CAD geometry has long been a requirement of most OEM’s and Tier 1 exhaust suppliers. Correlation to measurement data has been problematic under various operating conditions, including flow. This study was undertaken to develop robust modelling technique, ensuring sensible correlation between the 1-D models and test data. Ford use Ricardo WAVE as one of their 1-D NVH tools, which was chosen for the purpose of this benchmark study. The most commonly used metrics for evaluating the acoustical performance of mufflers are insertion loss (IL), TL, and noise reduction (NR). TL is often the first step of analysis, since it represents the inherent capability of the muffler to attenuate sound if both the source and termination are assumed to be anechoic. It can also be reliably measured and numerically simulated without having to connect to an engine.

Engine manufacturers are increasingly concerned about oil consumption due to its implications for operating costs, emissions, and durability in both diesel and natural gas-powered engines. As future engines aim for low or near-zero emissions while utilizing low/zero carbon fuels, lubricant oil consumption will play a critical role in achieving decarbonization and emissions targets. Hydrogen-fuelled engines, in particular, will be more vulnerable to oil droplet and oil ash-based pre-ignition. Traditionally, the influence of key design parameters on oil consumption has been determined during the validation phase of an engine development program, which entails extensive testbed hours and time-consuming hardware iterations. As a result, development programs may be unable to optimize oil consumption due to cost and time constraints.

Hydrogen has been identified as a promising decarbonization fuel in internal combustion engine (ICE) applications in many areas including heavy-duty on- and off-road, power-generation, marine, etc. Hydrogen ICEs can achieve high power density and very low tailpipe emissions. However, there are challenges; designing systems for a gaseous fuel with its own specific mixing, burn rate and combustion control needs, which can differ from legacy products. The primary pollutant of concern for Hydrogen ICEs is NOx which can be addressed by running the engine at very lean equivalence ratios and the use of Exhaust Gas Recirculation (EGR). Computation Fluid Dynamics (CFD) is a valuable tool to model the combustion characteristics under different conditions, as presented in SAE-2023-01-0197 [1], which can also be used to predict thermal loading.

For modern vehicle development, on-board vehicle Mass and road Gradient Estimation (MGE) can offer great benefit to many sub-systems on the vehicle, such as vehicle control system, transmission control system, and active safety system etc. However, there are still several challenges that need to be solved. Firstly, thanks to good accuracy, reliability, and robustness, regression analysis-based approaches: Recursive Least Squares (RLS) and Kalman Filter (KF) are very popular for MGE, but the trade-off between estimator’s accuracy and converge time is challenging. Furthermore, depending on vehicle and powertrain types, the implementation of MGE function could be very different. It is desired to have a structured approach for various vehicle applications’ MGE development. Lastly, good reliability of MGE does not always satisfy for complicated real-world driving maneuvers and road conditions.

A 2001 General Motors 4.3 liter V-6 marine engine was baseline emissions tested and then equipped with catalysts. Emission reduction effects of exhaust gas recirculation (EGR) were also explored. Because of a U.S. Coast Guard requirement that inboard engine surface temperatures be kept below 200°F, the engine's exhaust system, including the catalysts, was water-cooled. Engine emissions were measured using the ISO-8178-E4 5-mode steady-state test for recreational marine engines. In baseline configuration, the engine produced 16.6 g HC+NOx/kW-hr, and 111 g CO/kW-hr. In closed-loop control with catalysts, HC+NOx emissions were reduced by 75 percent to 4.1 g/kW-hr, and CO emissions were reduced by 36 percent to 70 g/kW-hr of CO. The catalyzed engine was then installed in a Sea Ray 190 boat, and tested for water reversion on both fresh and salt water using National Marine Manufacturers Association procedures.

For electric vehicles (EVs), driving range is one of the major concerns for wider customer acceptance and the cabin climate system represents the most significant auxiliary load for battery consumption. Unlike internally combustion engine (ICE) vehicles, EVs cannot utilize the waste heat from an engine to heat the cabin through the heating, ventilation and air conditioning (HVAC) system. Instead, EVs use battery energy for cabin heating, this reduces the driving range. To mitigate this situation, one of the most promising solutions is to optimize the recirculation of cabin air, to minimize the energy consumed by heating the cold ambient air through the HVAC system, whilst maintaining the same level of cabin comfort. However, the development of this controller is challenging, due to the coupled, nonlinear and multi-input multi-output nature of the HVAC and thermal systems.

In recent years, climate protection has become as important as ozone layer protection was in the late 1980's and early 1990s. Concerns about global warming and climate change have culminated in the Kyoto Protocol, a treaty requiring its signatories to limit their total emission of greenhouse gases to pre-1990 levels by 2008. The inclusion of hydrofluorocarbons (HFCs) as one of the controlled substances in the Kyoto Protocol has increased global scrutiny of the global warming impact of HFC-134a (called R-134a when used as a refrigerant), the current mobile air conditioning refrigerant. Industry's first response was to begin improving current R-134a systems to reduce leakage, reduce charge, and increase system energy efficiency, which in turn reduces tailpipe CO2 emissions. An additional option would be to replace the current R-134a with a refrigerant of lower global warming impact. This paper documents the use of another HFC, R-152a, in a mobile A/C system.

In 2015 the U.S. Environmental Protection Agency (EPA) and the U.S. Department of Transportation's National Highway Traffic Safety Administration (NHTSA) proposed a new steady-state engine dynamometer test procedure by which heavy-duty engine manufacturers would be required to create engine fuel rate versus engine speed and torque “maps”.[1] These maps would then be used within the agencies' Greenhouse Gas Emission Model (GEM)[2] for full vehicle certification to the agencies' proposed heavy-duty fuel efficiency and greenhouse gas (GHG) emissions standards. This paper presents an alternative to the agencies' proposal, where an engine is tested over the same duty cycles simulated in GEM. This paper explains how a range of vehicle configurations could be specified for GEM to generate engine duty cycles that would then be used for engine testing.

In designing a regulatory vehicle simulation program for determining greenhouse gas (GHG) emissions and fuel consumption, it is necessary to estimate the performance of technologies, verify compliance with the regulatory standards, and estimate the overall benefits of the program. The agencies (EPA/NHTSA) developed the Greenhouse Gas Emissions Model (GEM) to serve these purposes. GEM is currently being used to certify the fuel consumption and CO2 emissions of the Phase 1 rulemaking for all heavy-duty vehicles in the United States except pickups and vans, which require a chassis dynamometer test for certification. While the version of the GEM used in Phase 1 contains most of the technical and mathematical features needed to run a vehicle simulation, the model lacks sophistication. For example, Phase 1 GEM only models manual transmissions and it does not include engine torque interruption during gear shifting.

The authors have published SAE paper 2008-01-0088 on the analytical comparison between 4 and 8 counterweight crankshafts for an I4 gasoline engine. This paper showed that for a particular design of a 4 counterweight crankshaft, the differences in bearing force and oil film thickness were very small and the only major difference in terms of bearing shaft tilt angle occurred at mains 2 and 4 (increase of ∼20% compared with 8 counterweight version). The 4 counterweight crankshaft has a significant mass advantage as it was 1.42kg lighter than the 8 counterweight crankshaft. This new paper addresses the testing performed to validate the analysis results in bearing durability by subjecting the engine to a mixture of high speed and general durability cycles. A comparison was made on the bearing conditions after running a total of 100 hours through prescribed durability cycles on a gasoline engine with both 4 and 8 counterweight crankshafts.

Upcoming regulations from CARB and EPA will require diesel engine manufacturers to validate aftertreatment durability with full useful life aged components. To this end, the Diesel Aftertreatment Accelerated Aging Cycle (DAAAC) protocol was developed to accelerate aftertreatment aging by accounting for hydrothermal aging, sulfur, and oil poisoning deterioration mechanisms. Two aftertreatment systems aged with the DAAAC protocol, one on an engine and the other on a burner system, were directly compared to a reference system that was aged to full useful life using conventional service accumulation. After on-engine emission testing of the fully aged components, DOC and SCR catalyst samples were extracted from the aftertreatment systems to compare the elemental distribution of contaminants between systems. In addition, benchtop reactor testing was conducted to measure differences in catalyst performance.

Objective of this project was to establish very comprehensive, robust vehicle model of three wheeler electric vehicle. This was achieved by simulating vehicle operation and performance on standard as well as realistic driving cycles. Purpose of building a virtual electric three wheeler vehicle model was to validate the mathematical model with respect to real time road load testing. Electric 3 wheeler vehicle model was built in Ricardo-IGNITE. This model includes advanced vehicle which consists of detailed vehicle parameters like mass & CG locations, suspension, brakes and aerodynamic input parameters. Also other parameter includes road load resistances, rotational, transnational inertial effects and power-train efficiencies and detailed battery and motor model with its thermal & inertial properties respectively. Simulation results of performance and range are validated by actual vehicle testing on dynamo-meter and road for standard and realistic driving-cycles respectively.

The proposed Euro 7 emission standard foresees that the emission behaviour of Euro 7 vehicles is monitored via an on-board monitoring (OBM) system. In Euro 7 vehicles, OBM systems will monitor the emissions of nitrogen oxides (NOX), ammonia (NH3) and particulate matter (PM) for every trip through a combination of measured and modelled data. Sensors employed to support on-board diagnostics (OBD) in current vehicles may be used to support OBM. According to the Euro 7 OBM concept presented in this paper, OBM will serve a dual purpose: the first is to warn the user of a vehicle about the need to perform repairs on the engine or the pollution control systems when these are needed. If these repairs are not performed in a timely manner, the OBM system will be able to ultimately prevent engine restart, akin to the existing low-reagent driver warning system in some compression ignition vehicles. The second purpose of OBM is to monitor the compliance of vehicle types with the emission limits.

As part of the U.S. Environmental Protection Agency’s (EPA’s) continuing assessment of advanced light-duty automotive technologies in support of regulatory and compliance programs, a development project was started to study various test methods to benchmark Electric Drive Units (EDUs) consisting of an electric motor, inverter and a speed-reduction gearset. Several test methods were identified for consideration, including both in-vehicle testing of the complete EDU and stand-alone testing of the EDU and its subcomponents after removal from the vehicle. In all test methods explored, sweeps of speed and torque test points were conducted while collecting key EDU data required to determine efficiency, including motor torque and speed, direct current (DC) battery voltage and current into the inverter, and three-phase alternating current (AC) phase voltages and currents out of the inverter and into the electric motor.

The high-frequency whining noise produced by motors in modern electric vehicles causes a significant issue, leading to annoyance among passengers. This noise becomes even more noticeable due to the quiet nature of electric vehicles, which lack other noises to mask the high-frequency whining noise. To improve the noise caused by motors, it is essential to optimize various motor design parameters. However, this task requires expert knowledge and a considerable time investment. In this study, we explored the application of artificial intelligence to optimize the NVH performance of motors during the design phase. Firstly, we selected and modeled three benchmark motor types using Motor-CAD. Machine learning models were trained using Design of Experiment methods to simulate batch runs of Motor-CAD inputs and outputs.