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A study was performed to correlate the Sauter Mean Diameter (SMD), NOx and particulate emissions of a direct injection diesel engine with various injection pressures and different nozzle geometry. The spray experiments and engine emission tests were conducted in parallel using the same fuel injection system and same operating conditions. With high speed photography and digital image analysis, a light extinction technique was used to obtain the spray characteristics which included spray tip penetration length, spray angle, and overall average SMD for the entire spray. The NOx and particulate emissions were acquired by running the tests on a fully instrumented Caterpillar 3406 heavy duty engine. Experimental results showed that for higher injection pressures, a smaller SMD was observed, i.e. a finer spray was obtained. For this case, a higher NOx and lower particulate resulted.

Evaluations of the liner pitting protection performance provided by engine coolant corrosion inhibitors and supplemental coolant additives have presented many problems. Current practice involves the use of full scale engine tests to show that engine coolant inhibitors provide sufficient liner pitting protection. These are too time-consuming and expensive to use as the basis for industry-wide specifications. Ultrasonic vibratory test rigs have been used for screening purposes in individual labs, but these have suffered from poor reproducibility and insufficient additive differentiation. A new test procedure has been developed that reduces these problems. The new procedure compares candidate formulations against a good and bad reference fluid to reduce the concern for problems with calibration and equipment variability. Cast iron test coupons with well-defined microstructure and processing requirements significantly reduce test variability.

A computational methodology has been developed for loss prediction in intake regions of internal combustion engines. The methodology consists of a hierarchy of four major tasks: (1) proper computational modeling of flow physics; (2) exact geometry and high quality and generation; (3) discretization schemes for low numerical viscosity; and (4) higher order turbulence modeling. Only when these four tasks are dealt with properly will a computational simulation yield consistently accurate results. This methodology, which is has been successfully tested and validated against benchmark quality data for a wide variety of complex 2-D and 3-D laminar and turbulent flow situations, is applied here to a loss prediction problem from industry. Total pressure losses in the intake region (inlet duct, manifold, plenum, ports, valves, and cylinder) of a Caterpillar diesel engine are predicted computationally and compared to experimental data.

A test stand was developed to evaluate an 11.5 cc, two-stroke, internal combustion engine in anticipation of future combustion system modifications. Detailed engine testing and analysis often requires complex, specialized, and expensive equipment, which can be problematic for research budgets. This problem is compounded by the fact that testing “micro” engines involves low flow rates, high rotational speeds, and compact dimensions which demand high-accuracy, high-speed, and compact measurement systems. On a limited budget, the task of developing a micro-engine testing system for advanced development appears quite challenging, but with careful component selection it can be accomplished. The anticipated engine investigation includes performance testing, fuel system calibration, and combustion analysis. To complete this testing, a custom test system was developed.

Connected vehicles have the potential to transform the way we commute and travel in a multitude of ways. Vehicles will cooperate and coordinate with each other to solve problems appropriate for the environment in which they are operating. In this paper, we focus on the development of test equipment that includes the infrastructure and vehicles to measure and record all of the information necessary to quantify the performance of cooperative driving algorithms in realistic scenarios. The system allows tests to include real vehicles on the track and virtual vehicles in a digital twin. Real and virtual vehicles interact through the road-side units and test facility network, allowing each test vehicle to receive messages from virtual vehicles as well as the infrastructure. Messages transmitted from the test vehicles are received in the digital twin, allowing the real vehicle to interact with virtual vehicles.

In the recent years, the interest in heavy-duty engines fueled with Compressed Natural Gas (CNG) is increasing due to the necessity to comply with the stringent CO2 limitation imposed by national and international regulations. Indeed, the reduced number of carbon atoms of the NG molecule allows to reduce the CO2 emissions compared to a conventional fuel. The possibility to produce synthetic methane from renewable energy sources, or bio-methane from agricultural biomass and/or animal waste, contributes to support the switch from conventional liquid fuels to CNG. To drive the engine development and reduce the time-to-market, the employment of numerical analysis is mandatory. This requires a continuous improvement of the simulation models toward real predictive analyses able to reduce the experimental R&D efforts. In this framework, 1D numerical codes are fundamental tools for system design, energy management optimization, and so on.

Predictive Signal Phase and Timing (SPAT) message set is one fundamental building block for vehicle-to-infrastructure (V2I) applications such as Eco-Approach and Departure (EAD) at traffic signal controlled urban intersections. Among the two complementary communication methods namely short-range sidelink (PC5) and long-range cellular radio link (Uu), this paper documents the work with long-range link: the complete data chain includes connecting to the traffic signals via existing backhaul communication network, collecting the raw signal phase state data, predicting the signal state changes and delivering the SPAT data via a geofenced service to requests over HTTP protocols. An Application Programming Interface (API) library is developed to support various cellular data transmission reduction and latency improvement techniques.

In July 1997, the Pacific Northwest and Alaska Regional Bioenergy Program, in cooperation with several industrial and institutional partners initiated a long-haul 322,000 km (200,000 mile) operational demonstration using a biodiesel and diesel fuel blend in a 324 kW (435 HP), Caterpillar 3406E Engine, and a Kenworth Class 8 heavy duty truck. This project was designed to: develop definitive biodiesel performance information, collect emissions data for both regulated and non-regulated compounds including mutagenic activity, and collect heavy-duty operational engine performance and durability information. To assess long-term engine durability and wear; including injector, valve and port deposit formations; the engine was dismantled for inspection and evaluation at the conclusion of the demonstration. The fuel used was a 50% blend of biodiesel produced from used cooking oil (hydrogenated soy ethyl ester) and 50% 2-D petroleum diesel.

This paper describes a multi-sensor data set, suitable for testing algorithms to detect and track pedestrians and cyclists, with an autonomous vehicle’s sensor suite. The data set can be used to evaluate the benefit of fused sensing algorithms, and provides ground truth trajectories of pedestrians, cyclists, and other vehicles for objective evaluation of track accuracy. One of the principal bottlenecks for sensing and perception algorithm development is the ability to evaluate tracking algorithms against ground truth data. By ground truth we mean independent knowledge of the position, size, speed, heading, and class of objects of interest in complex operational environments. Our goal was to execute a data collection campaign at an urban test track in which trajectories of moving objects of interest are measured with auxiliary instrumentation, in conjunction with several autonomous vehicles (AV) with a full sensor suite of radar, lidar, and cameras.

This paper presents the development of a reduced-order powertrain model for energy and SOC estimation of a multi-mode plug-in hybrid electric vehicle using only vehicle speed profile and route elevation as inputs. Such a model is intended to overcome the computational inefficiencies of higher fidelity powertrain and vehicle models in short and long horizon energy optimization efforts such as Coordinated Adaptive Cruise Control (CACC), Eco Approach and Departure (EcoAND), Eco Routing, and PHEV mode blending. The reduced-order powertrain model enables Connected and Automated Vehicles (CAVs) to utilize the onboard sensor and connected data to quickly react and plan their maneuvers to highly dynamic road conditions with minimal computational resources.

The aim of this study is to investigate the parameters influencing the real driving emission monitoring with particular attention towards the influence of road gradient. For this purpose, an experimental activity was carried out with a Euro 5 Diesel light-duty vehicle, driven along two tracks of Naples characterized by a different road gradient: the first pattern is quite flat, the second includes positive (+2.9%) and negative (−3.6%) road gradient. Exhaust emissions of CO, THC, NOx, CO2 were acquired on road by using a portable emission measuring system (PEMS) connected also to the Engine Control Unit for saving the main engine parameters and to the GPS for the geographical coordinates and altitude. The acquired speed profiles were repeated on the chassis-dynamometer without simulating the road gradient.

This paper investigates abnormal combustion during the cranking phase of spark-ignition small engines, specifically the occurrence of backfire at the release of the starter motor during kickback. The research focusses on the influence of fuel composition, mainly in terms of ethanol percentage, on backfire occurrence. Interest in this abnormal combustion is growing due to the increased use of fuels with different chemical-physical properties with respect to gasoline. Moreover, this issue will become even more topical due to the implementation of simple control and fuel supply systems on low cost-engines, which are widely used in developing countries. Experimentation was carried out in an optically accessible engine derived from a 4-stroke spark ignition engine for two-wheel vehicles. The test bench was instrumented and adapted in order to simulate the engine conditions that lead to anomalous ignition in the intake duct (backfire) during the reverse rotation of the engine (kickback).

This paper reports an experimental and numerical investigation on the spatial and temporal liquid- and vapor-phase distributions of diesel fuel spray under engine-like conditions. The high pressure diesel spray was investigated in an optically-accessible constant volume combustion vessel for studying the influence of the k-factor (0 and 1.5) of a single-hole axial-disposed injector (0.100 mm diameter and 10 L/d ratio). Measurements were carried out by a high-speed imaging system capable of acquiring Mie-scattering and schlieren in a nearly simultaneous fashion mode using a high-speed camera and a pulsed-wave LED system. The time resolved pair of schlieren and Mie-scattering images identifies the instantaneous position of both the vapor and liquid phases of the fuel spray, respectively. The studies were performed at three injection pressures (70, 120, and 180 MPa), 23.9 kg/m3 ambient gas density, and 900 K gas temperature in the vessel.

An automobile seat’s thermal performance can be challenging to quantify since it requires comprehensive human subject testing. Seat manufacturers must rely on subjective ratings to understand how the construction of a seat and its underlying heating and cooling technology may compare to other seats. Other factors may influence seat ratings published by global marketing information services companies (e.g., JD Power and Associates). In particular, occupants may be biased by the vehicle class in which a seat is installed and by how much the contribution of a specific vehicle’s HVAC system performance affects the perception of seat thermal comfort. Therefore, there is a need for an objective testing methodology that does not rely on human participants but is still capable of producing a thermal performance rating in terms of established thermal comfort scales.

This work presents the results of an experimental investigation on a GDI injector, in order to analyze fuel injection process and atomization phenomenon, correlating imaging and vibro-acoustic diagnostic techniques. A single-hole, axially-disposed, 0.200 mm diameter GDI injector was used to spray commercial gasoline in a test chamber at room temperature and atmospheric backpressure. The explored injection pressures were ranged from 5.0 to 20.0 MPa. Cycle-resolved acquisitions of the spray evolution were acquired by a high-speed camera. Simultaneously, the vibro-acoustic response of the injector was evaluated. More in detail, noise data acquired by a microphone sensor were analyzed for characterizing the acoustic emission of the injection, while a spherical loudspeaker was used to excite the spray injection at a proper distance detecting possible fuel spray resonance phenomena.

Transmissions have multiple transient events that occur from gear shifting to torque converter clutch application. These transients can be difficult to capture and observe. A six speed front wheeled drive transmission was instrumented with pressure transducers to measure clutches and the torque converter. Due to size restrictions internal to the torque converter the data had to be multiplexed across three different transmitters. A method to capture a transient event through the use of multiplexed data was developed to create a data set with the transient event occurring on each channel. Once testing is completed, the data has to be split into individual channels and synced with the operational data. The data then can be used in both time and frequency domain analysis. It is important to understand that the data is not continuous and must be taken into consideration when post processing it for further results.

Sound power can be determined using a variety of methods, but precision methods require the volume of the noise source to be less than 1% of the chamber volume leading to relatively large test chambers. Automotive torque converter performance and noise testing is completed in an enclosed metallic test fixture which inhibits the use of precision methods due to volume and space limitations. This paper describes a new method developed to accurately determine sound power of an automotive torque converter in a relatively small enclosure through characterization of the test environment. The test environment was characterized using two reference noise sources designed to represent torque converter noise output and physical geometry. Sound pressure levels of the sources were measured at multiple microphone locations and at three source amplitude levels to characterize the environment.

Anti-knock index (AKI) is a metric that can be used to quantify the anti-knock performance of a fuel and is the metric used in the United States. AKI is the average of Research Octane Number (RON) and Motor Octane Number (MON), which are calculated for every fuel on a Cooperative Fuel Research (CFR) engine under controlled conditions according to ASTM test procedures. Fuels with higher AKI have better knock mitigating properties and can be run with a combustion phasing closer to MBT in the knock limited operating region of a gasoline engine. However, fuels with higher AKI tend to be costlier and less environmentally friendly to produce. As an alternative, the anti-knock characteristics of lower AKI fuels can be improved with water injection. In this sense, the water injection increases the ‘effective AKI’ of the fuel.