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Testing of ducted fuel injection (DFI) in a single-cylinder engine with production-like hardware previously showed that adding a duct structure increased soot emissions at the full load, rated speed operating point [1]. The authors hypothesized that the DFI flame, which travels faster than a conventional diesel combustion (CDC) flame, and has a shorter distance to travel, was being re-entrained into the on-going fuel injection around the lift-off length (LOL), thus reducing air entrainment into the on-going injection. The engine operating condition and the engine combustion chamber geometry were duplicated in a constant pressure vessel. The experimental setup used a 3D piston section combined with a glass fire deck allowing for a comparison between a CDC flame and a DFI flame via high-speed imaging. CH* imaging of the 3D piston profile view clearly confirmed the re-entrainment hypothesis presented in the previous engine work.

The SAE AutoDrive Challenge II is a four-year collegiate competition dedicated to developing a Level 4 autonomous vehicle by 2025. In January 2023, the participating teams each received a Chevy Bolt EUV. Within a span of five months, the second phase of the competition took place in Ann Arbor, MI. The authors of this contribution, who participated in this event as team Wisconsin Autonomous representing the University of Wisconsin–Madison, secured second place in static events and third place in dynamic events. This has been accomplished by reducing reliance on the actual vehicle platform and instead leveraging physical analogs and simulation. This paper outlines the software and hardware infrastructure of the competing vehicle, touching on issues pertaining sensors, hardware, and the software architecture employed on the autonomous vehicle. We discuss the LiDAR-camera fusion approach for object detection and the three-tier route planning and following systems.

Brake pulsation is a low frequency vibration phenomenon in brake judder. In this study, a simulation approach has been developed to understand the physics behind brake pulsation employing a full vehicle dynamics CAE model. The full vehicle dynamic model was further studied to understand the impact of suspension tuning variation to brake pulsation performance. Brake torque variation (BTV) due to brake thickness variation from uneven rotor wear was represented mathematically in a sinusoidal form. The wheel assembly vibration from the brake torque variation is transmitted to driver interface points such as the seat track and the steering wheel. The steering wheel lateral acceleration at the 12 o’clock position, driver seat acceleration, and spindle fore-aft acceleration were reviewed to explore the physics of brake pulsation. It was found that the phase angle between the left and right brake torque generated a huge variation in brake pulsation performance.

The influence of a split-injection strategy on energy-assisted compression-ignition (EACI) combustion of low-cetane number sustainable aviation fuels was investigated in a single-cylinder direct-injection compression-ignition engine using a ceramic ignition assistant (IA). Two low-cetane number fuels were studied: a low-cetane number alcohol-to-jet (ATJ) sustainable aviation fuel (SAF) with a derived cetane number (DCN) of 17.4 and a binary blend of ATJ with F24 (Jet-A fuel with military additives, DCN 45.8) with a blend DCN of 25.9 (25 vol.% F24, 75 vol.% ATJ). A pilot injection mass sweep (3.5-7.0 mg) with constant total injection mass and an injection dwell sweep (1.5-3.0 ms) with fixed main injection timing was performed. Increasing pilot injection mass was found to reduce cycle-to-cycle combustion phasing variability by promoting a shorter and more repeatable combustion event for the main injection with a shorter ignition delay.

This paper presents a virtual analysis method for pressure spike estimation and optimization of hydraulic system architecture for off-highway applications with hydraulically actuated clutch. This pressure spike leads to a very high torque spike in driveline components during clutch pop-up conditions in puddling operations. These torque spikes lead to potential failure of driveline components i.e., gear, shaft, bearing and torsional damper during sudden engagement events. To assess the hydraulic system performance during clutch pop-up cornering conditions is very challenging and leads to compromise on operator safety in the paddy field. It is essential to develop a simulation methodology in a virtual environment to understand the system behavior during clutch pop-up condition and impact of various hydraulic system parameters. This paper describes a Model Based System Design (MBSD) approach for understanding hydraulic system pressure spike phenomenon and dynamic response.

A typical cab used on agriculture machines is made up of a metal frame structure with large enclosing panels of glass, plastic, and metal. Acoustic treatments such as coatings, textiles and foams are used within the cab for aesthetics but also to mediate undesired noise. To develop effective designs for the cab to combat noise, accurate tools for measurement, and predictive methods for sound transmission loss are needed. This paper focuses on Sound Transmission Loss (STL) of the rear upper panel of a cab used in agriculture machines. Results from CAE based tools such as Statistical Energy Analysis (SEA), Finite Element Analysis (FEA) and Hybrid FE-SEA methods are compared to measurements. The panel studied included features such as curvature, deep drawn beads with a glass window and a damping coating. The simulation results are refined by incorporating methods for accurate modeling of ribs stiffness, curvature effect and radiation efficiency by synthetic modal approach.

This work experimentally investigates the impact of premixed fuel composition (methane/ethane, methane/propane, and methane/hydrogen mixtures having equivalent chemical energy) and pilot reactivity (cetane number) on diesel-pilot injection (DPI) combustion performance and emissions, with an emphasis on the pilot ignition delay (ID). To support the experimental pilot ignition delay trends, an analysis technique known as Mixing Line Concept (MLC) was adopted, where the cold diesel surrogate and hot premixed charge are envisioned to mix in a 0-D constant volume reactor to account for DPI mixture stratification. The results show that the dominant effect on pilot ignition is the pilot fuel cetane number, and that the premixed fuel composition plays a minor role. There is some indication of a physical effect on ignition for cases containing premixed hydrogen.

Lithium-ion and Lithium polymer batteries are fast becoming ubiquitous in high-discharge rate applications for military and non-military systems. Applications such as small aerial vehicles and energy transfer systems can often function at C-rates greater than 1. To maximize system endurance and battery health, there is a need for models capable of precisely estimating the battery state-of-charge (SoC) under all temperature and loading conditions. However, the ability to perform state estimation consistently and accurately to within 1% error has remained unsolved. Doing so can offer enhanced endurance, safety, reliability, and planning, and additionally, simplify energy management. Therefore, the work presented in this paper aims to study and develop experimentally validated mathematical models capable of high-accuracy battery SoC estimation.

In this study, the impacts of fuel volatility and reactivity on combustion stability and emissions were studied in a light-duty single-cylinder research engine for a three-injection catalyst heating operation strategy with late post-injections. N-heptane and blends of farnesane/2,2,4,4,6,8,8-heptamethylnonane were used to study the impacts of volatility and reactivity. The effect of increased chemical reactivity was also analysed by comparing the baseline #2 diesel operation with a pure blend of mono-ether components (CN > 100) representative of potential high cetane oxygenated bioblendstocks and a 25 vol.% blend of the mono-ether blend and #2 diesel with a cetane number (CN) of 55. At constant reactivity, little to no variation in combustion performance was observed due to differences in volatility, whereas increased reactivity improved combustion stability and efficiency at late injection timings.

The combined impacts of engine speed and fuel reactivity on energy-assisted compression-ignition (EACI) combustion using a commercial off-the-shelf (COTS) ceramic glow plug for low-load operation werexxz investigated. The COTS glow plug, used as the ignition assistant (IA), was overdriven beyond its conventional operation range. Engine speed was varied from 1200 RPM to 2100 RPM. Three fuel blends consisting of a jet-A fuel with military additives (F24) and a low cetane number alcohol-to-jet (ATJ) sustainable aviation fuel (SAF) were tested with cetane numbers (CN) of 25.9, 35.5, and 48.5. The ranges of engine speed and fuel cetane numbers studied are significantly larger than those in previous studies of EACI or glow-plug assisted combustion, and the simultaneous variation of engine speed and fuel reactivity are unique to this work. For each speed and fuel, a single-injection of fixed mass was used and the start of injection (SOI) was swept for each IA power.

A non-intrusive sensing technique to determine start of combustion for mixing-controlled compression-ignition engines was developed based on an accelerometer mounted to the engine block of a 4-cylinder automotive turbo-diesel engine. The sensing approach is based on a physics-based conceptual model for the signal generation process that relates engine block acceleration to the time derivative of heat release rate. The frequency content of the acceleration and pressure signals was analyzed using the magnitude-squared coherence, and a suitable filtering technique for the acceleration signal was selected based on the result. A method to determine start of combustion (SOC) from the acceleration measurements is presented and validated.

Ducted fuel injection (DFI), a concept that utilizes fuel injection through ducts, was implemented in a constant pressure High Temperature Pressure Vessel at 60 bar ambient pressure, 800-1000 K ambient temperature, and 21 % oxygen. The ducts were 14 mm long and placed 3-4.7 mm from the orifice exit. The duct diameters ranged from 1.6-3.2 mm and had a rounded inlet and a tapered outlet. Diesel fuel was used in single-orifice fuel injectors operating at 250 MPa rail pressure. The objective of this work was to study soot reduction for various combinations of orifice and duct diameters. A complete data set was taken using the 150 μm orifice. A smaller data set was acquired for a 219 μm orifice, showing similar trends. Soot reduction peaked at an optimal duct diameter of 2-2.25 mm, corresponding to an 85-90 % spray area reduction for the 150 μm orifice. Smaller or larger duct diameters were less effective. Duct diameter had a minimal effect on ignition delay.

RADAR Sensors are going to be an integral part of autonomous vehicles. One of the main objectives of these sensors in autonomous vehicles is to get the Doppler range profile for surrounding traffic. In this paper, we use a similar RADAR for ground speed sensing in the off-highway scenario. There are several challenges in integrating the RADAR sensor with vehicles such as sensor position from ground, location on vehicle, electromagnetic interference with other electronic devices, enclosure design etc. Ground conditions and properties are also critical in the off-highway scenario for speed sensing. We propose to use the physics based electromagnetic field solvers to understand and mitigate some of these challenges and speed up the design. Electromagnetic field solvers tend to scale poorly with distance of propagation, especially in 3D modeling.

Identifying edge cases for designed algorithms is critical for functional safety in autonomous driving deployment. In order to find the feasible boundary of designed algorithms, simulations are heavily used. However, simulations for autonomous driving validation are expensive due to the requirement of visual rendering, physical simulation, and AI agents. In this case, common sampling techniques, such as Monte Carlo Sampling, become computationally expensive due to their sample inefficiency. To improve sample efficiency and minimize the number of simulations, we propose a tailored active learning approach combining the Support Vector Machine (SVM) and the Gaussian Process Regressor (GPR). The SVM learns the feasible boundary iteratively with a new sampling point via active learning. Active Learning is achieved by using the information of the decision boundary of the current SVM and the uncertainty metric calculated by the GPR.

The presence of residual stresses affects the fatigue response of welded components. In the present study of thick welded cantilever specimens, residual stresses were measured in two A36 steel samples, one in the as-welded condition, and one subjected to a short history of bending loads where substantial local plasticity is expected at the fatigue hot-spot weld toe. Extensive X-Ray Diffraction (XRD) measurements describe the residual stress state in a large region above the weld toe both in an untested as-welded sample and in a sample subjected to a short load history that generated an estimated 0.01 strain amplitude at the stress concentration zone at the weld toe. The results show that such a test will significantly alter the welding-induced residual stresses. Fatigue life prediction methods need to be aware that such alterations are possible and incorporate the effects of such cyclic stress relaxation in life computations.

Opposed-piston 2-stroke (OP-2S) engines have the potential to achieve higher thermal efficiency than a typical diesel engine. However, the uniflow scavenging process is difficult to control over a wide range of speeds and loads. Scavenging performance is highly sensitive to pressure dynamics, port timings, and port design. This study proposes an analysis of the effects of port vane angle on the scavenging performance of an opposed-piston 2-stroke engine via simulation. A CFD model of a three-cylinder opposed-piston 2-stroke was developed and validated against experimental data collected by Achates Power Inc. One of the three cylinders was then isolated in a new model and simulated using cycle-averaged and cylinder-averaged initial/boundary conditions. This isolated cylinder model was used to efficiently sweep port angles from 12 degrees to 29 degrees at different pressure ratios.

Traffic state identification is a key problem in intelligent transportation system. As a new technology, connected and automated vehicle can play a role of identifying traffic state with the installation of onboard sensors. However, research of lane level traffic state identification is relatively lacked. Identifying lane level traffic state is helpful to lane selection in the process of driving and trajectory planning. In addition, traffic state identification precision with low penetration of connected and automated vehicles is relatively low. To fill this gap, this paper proposes a novel method of identifying traffic state in the presence of connected and automated vehicles with low penetration rate. Assuming connected and automated vehicles can obtain information of surrounding vehicles’, we use the perceptible information to estimate imperceptible information, then traffic state of road section can be inferred.

Pass-by/exterior noise of earth moving machines (EMM) and forestry machines is becoming a focus at early product development stages. ISO 6395 (2) or EC/2000/14 (1) standards defines exterior noise test procedure for EMM. However, these standards do not provide insights for diagnosing any noise issues which may arise. The analysis challenges are posed by the moving machine and acoustic sources with respect to the stationary hemisphere target microphone on the ground and changing operating condition of sources as function of time. There is need to develop a seamless methodology to identify acoustic sources, quantify respective source strengths and rank partial contributions from each source to the total target microphone response in order to overcome the aforementioned challenges.

To improve overall customer experience, it is imperative to minimize the noise levels inside agricultural equipment cab. Up-front prediction of acoustic performance in product development is critical to implement the noise control strategies optimally. This paper discusses the methodology used for virtual modeling of a cab on agricultural equipment for prediction of interior noise. The Statistical Energy Analysis (SEA) approach is suitable to predict high frequency interior noise and sound quality parameters such as articulation index and loudness. The cab SEA model is developed using a commercial software. The structural and acoustic excitations are measured through physical testing in various operating conditions. The interior noise levels predicted by the virtual model are compared with the operator ear noise levels measured in the test unit. The resultant SPL spectrum from SEA correlates well with the test.

The demands on improving the noise, vibration and harshness of the golf mowing machines are growing rapidly. Low frequency vibrations at the human touchpoints are one of the important factors leading to the discomfort of operators on these machines. In the present work, low frequency vibrations experienced by the operator of the golf mowing machine are reduced using finite element analysis (FEA) and validated by a physical test. Initially, testing observed high vibration at the command arm, where some of the operating controls are placed. FEA was carried out on a frame level assembly and the design was iterated to affect these vibration levels. The golf mowing machine considered in this work is powered by a gasoline engine, which is the source of excitation in the current scenario. The operational forces of the engine were measured by using blocked-force transfer path analysis at its mounts. The modal frequency response analysis used these calculated forces as an input excitation.