Search Results

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.

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.

Powertrain development requires an efficient development process with no rework and model-based development (MBD). In addition, to performance design that achieves low CO2 emissions is also required. Furthermore, it also demands fuel economy performance considering real-world usage conditions, and in North America, the EPA (U.S. Environmental Protection Agency) 5-cycle, which evaluates performance in a combination of various environments, is applied. This evaluation mode necessitates predicting performance while considering engine heat flow. Particularly, simulation technology that considers behavior based on engine temperature for Hybrid Electric Vehicle (HEV) is necessary. Additionally, in the development trend of vehicle aerodynamic improvement, variable devices like Active Grille Shutter (AGS) are utilized to contribute to reducing CO2 emissions.

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.

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.

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.

In-cylinder thermal barrier coatings (TBCs) have the capability to reduce fuel consumption by reducing wall heat transfer and to increase exhaust enthalpy. Low thermal conductivity, low volumetric heat capacity thermal barrier coatings tend to reduce the gas-wall temperature difference, the driving potential for heat transfer from the gas to the combustion chamber surfaces. This paper presents a coupling between an analytical methodology for multi-layer coated wall surface temperature prediction with a fully calibrated production model in a commercial system-level simulation software package (GT-Power). The wall surface temperature at each time step was calculated efficiently by convolving the engine wall response function with the time-varying surface boundary condition, i. e., in-cylinder heat flux and coolant temperature. This tool allows the wall to be treated either as spatially uniform with one set of properties, or with independent head/piston/liner components.

According to some papers, the label fuel economy and the actual fuel economy experienced by the customers may exhibit a gap. One of the reasons may stem from the aerodynamic drag variations due to the natural wind. The fuel consumption is measured through bench test under several driving modes by using the road load as input condition. The road load is measured through the coast down test under less wind ambient conditions as determined by each regulation. The present paper aims to analyze the natural wind conditions encountered by the vehicle on public roads and to operate a comparison between the fuel consumptions and the driving energy. In this paper, the driving energy is calculated by the aerodynamic drag from the natural wind specifications and driving conditions. This driving energy and the fuel consumptions show good correlation. The fuel consumption is obtained from the vehicle Engine control unit(ECU) data.

Bioethanol is being used as an alternative fuel throughout the world based on considerations of reduction of CO2 emissions and sustainability. It is widely known that ethanol has an advantage of high anti-knock quality. In order to use the ethanol in ethanol-blended gasoline to control knocking, the research discussed in this paper sought to develop a fuel separation system that would separate ethanol-blended gasoline into a high-octane-number fuel (high-ethanol-concentration fuel) and a low-octane-number fuel (low-ethanol-concentration fuel) in the vehicle. The research developed a small fuel separation system, and employed a layout in which the system was fitted in the fuel tank based on considerations of reducing the effect on cabin space and maintaining safety in the event of a collision. The total volume of the components fitted in the fuel tank is 6.6 liters.

There is significant potential for connected and autonomous vehicles to impact vehicle efficiency, fuel economy, and emissions, especially for hybrid-electric vehicles. These improvements could have large-scale impact on oil consumption and air-quality if deployed in large Mobility-as-a-Service or ride-sharing fleets. As part of the US Department of Energy's current Advanced Vehicle Technology Competition (AVCT), EcoCAR: The Mobility Challenge, Mississippi State University’s EcoCAR Team is redesigning and doing the development work necessary to convert a conventional gasoline spark-ignited 2019 Chevy Blazer into a hybrid-electric vehicle with SAE Level 2 autonomy. The target consumer segments for this effort are the Mobility-as-a-Service fleet owners, operators and riders. To accomplish this conversion, the MSU team is implementing a P4 mild hybridization strategy that is expected to result in a 30% increase in fuel economy over the stock Blazer.

Since the operation of the powertrain system and the engine speed and torque are determined in the ECU in hybrid vehicles, control parameters in these vehicles are more sensitive to a variety of performance factors than those employed in conventional vehicles. The three performance factors acceleration performance, NVH and fuel consumption in particular are in a tradeoff relationship, the calibration of control parameters in order to satisfy these performance targets entail considerable development costs. Given this, it is possible to increase the efficiency of hybrid vehicle development by determining Pareto design solutions for the three performance factors via multi-objective optimization using CAE, and selecting target performance and control parameters based on these Pareto design solutions.

The effect of low level ethanol fuel on the power and emissions characteristics was studied in a small, mass produced, carbureted, spark-ignited, Briggs and Stratton Vanguard 19L2 engine. Ethanol has been shown to be an attractive renewable fuel by the automotive industry; having anti-knock properties, potential power benefits, and emissions reduction benefits. With increasing availability and the possible mandates of higher ethanol content in pump gasoline, there is interest in exploring the effect of using higher content ethanol fuels in the small utility engine market. The fuels in this study were prepared by gravimetrically mixing 98.7% ethanol with a balance of 87 octane no-ethanol gasoline in approximately 5% increments from pure gasoline to 25% ethanol. Alcor Petrolab performed fuel analysis on the blended fuels and determined the actual volumetric ethanol content was within 2%.

In recent years, electrification of powertrains has been promoted to improve fuel efficiency and CO2 emissions. Along with electrification, it is possible to reduce engine usage frequency and improve the fuel efficiency in traveling. Especially in a hybrid electric vehicle (HEV), the state changes from motor assist mode to engine firing mode. As a result, stay time in eigenvalue of a powertrain is shortened, and vibration of the vehicle body at the engine start situation is able to be reduced as compared with conventional engine-driven vehicle. However, since the HEV is equipped with a high compression ratio engine for improving fuel economy, there is cause for concern that excitation force generated by the powertrain at the time of engine start increases. Also, the vehicle body vibration at engine start situations requires further consideration, because the operation frequency of engine decreases.

In recent years, fuel efficiency has been improved by using many technologies such as downsizing engine, turbocharger and direct injection to reduce CO2 emissions from vehicle. However, the temperature of the exhaust gas from the engines using these technologies becomes lower than that form conventional one. That increases the difficulty for three-way catalyst (TWC) to purify CO, HC and NOx enough because TWC is not warmed up just after engine starting. In order to reduce cold emission mentioned above, we have been studying the warmup strategy of which the key property is thermal mass of TWC. To achieve early warmup, thermal mass of TWC is reduced by lightening the weight of (1) substrate and (2) catalytic materials, namely washcoat amount. Along with the strategy, we have developed TWC with lightweight substrate and applied it from the 2016 model year CIVIC.

We studied a simple and cost effective controlled auto ignition (CAI) combustion engine in order to achieve simultaneous reduction of NOx and soot, which are issues in diffusion combustion. The engine type was a uniflow scavenging 2-stroke engine, and the fuel used was diesel, as is common in diesel engines. We examined the position of the injector that effectively forms the premixture and realized stable operation with diesel fuel by the low pressure fuel injection device for port fuel injection (PFI), and it was found that the CAI combustion ignition timing can be controlled through setting the air/fuel ratio that obtains the optimal ignition timing per operation conditions.

In motorcycles, the mass difference between a vehicle and a rider is small and motions of a rider impose a great influence on the vehicle behaviors as a consequence. Therefore, dynamic properties of motorcycles should be evaluated not merely dealing with a vehicle but considering with a man-machine system. In the studies of a simulation for vehicle dynamics, various types of rider models have been proposed and it has already been reported that rider motions have a significant influence on the dynamic properties. However, the mechanism of the interaction between a rider and a vehicle has not been clarified yet. In our study, we focused on weave motion and constructed a full vehicle simulation model that can reflect the influences of the movements of the rider’s upper body and lower body. To construct the rider model, we first measured the vibrational characteristics of a human body using a vibration test bench.

Honda has developed the 2018 model CLARITY PLUG-IN HYBRID. Honda’s new plug-in hybrid is a midsize sedan and shares a body platform with the CLARITY FUEL CELL and the CLARITY ELECTRIC. The vehicle’s electric powertrain boosts driving performance as an electric vehicle (EV) over Honda’s previous plug-in hybrid. The CLARITY PLUG-IN HYBRID’s electric powertrain consists of a traction motor and generator built into the transmission, a Power Control Unit (PCU) positioned above the transmission, an Intelligent Power Unit (IPU) fitted under the floor, and an onboard charger fitted below the rear trunk. The PCU integrates an inverter that drives the traction motor, an inverter that drives the generator, and a DC-DC converter to boost battery voltage (referred to as a “Voltage Control Unit (VCU)” below).

The purpose of this research was to predict the amount of wear on exhaust valve seats in durability testing of gasoline engines. Through the rig wear test, a prediction formula was constructed with multiple factors as variables. In the rig test, the wear rate was measured in some cases where a number of factors of valve seat wear were within a certain range. Through these tests, sensitivity for each factor was determined from the measured wear data, and then a prediction formula for calculating the amount of wear was constructed with high sensitivity factors. Combining the wear amount calculation formula with the operation mode of the actual engine, the wear amount in that mode can be calculated. The calculated wear amount showed a high correlation with the wear amount measured in bench tests and the wear amount measured in vehicle tests.

Although turbocharging can extend the high load limit of low temperature combustion (LTC) strategies such as reactivity controlled compression ignition (RCCI), the low exhaust enthalpy prevalent in these strategies necessitates the use of high exhaust pressures for improving turbocharger efficiency, causing high pumping losses and poor fuel economy. To mitigate these pumping losses, the divided exhaust period (DEP) concept is proposed. In this concept, the exhaust gas is directed to two separate manifolds: the blowdown manifold which is connected to the turbocharger and the scavenging manifold that bypasses the turbocharger. By separately actuating the exhaust valves using variable valve actuation, the exhaust flow is split between two manifolds, thereby reducing the overall engine backpressure and lowering pumping losses. In this paper, results from zero-dimensional and one-dimensional simulations of a multicylinder RCCI light-duty engine equipped with DEP are presented.