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Reducing the high cost of hardware testing with analytical methods has been highly accelerated in the automotive industry. This paper discusses an analytical model to simulate the driveline boom test for the transverse engine with all wheel drive configuration on a front-wheel drive base (TFWD/AWD). Driveline boom caused by engine firing frequency that excites the bending mode of the propeller shaft becomes a noise and vibration issue for the design of TFWD/AWD driveline. The major source of vibrations and noise under the investigation in this paper is the dominant 3rd order engine torque pulse disturbance that excites the bending of the propeller shaft, the bending of the powertrain and possible the bending of the rear halfshaft. All other excitation sources in this powertrain for a 60° V6 engine with a pushrod type valvetrain are assessed and NVH issues are also considered in this transient dynamic model.

Accurate perception of the driving environment and a highly accurate position of the vehicle are paramount to safe Autonomous Vehicle (AV) operation. AVs gather data about the environment using various sensors. For a robust perception and localization system, incoming data from multiple sensors is usually fused together using advanced computational algorithms, which historically requires a high-compute load. To reduce AV compute load and its negative effects on vehicle energy efficiency, we propose a new infrastructure information source (IIS) to provide environmental data to the AV. The new energy–efficient IIS, chip–enabled raised pavement markers are mounted along road lane lines and are able to communicate a unique identifier and their global navigation satellite system position to the AV. This new IIS is incorporated into an energy efficient sensor fusion strategy that combines its information with that from traditional sensor.

Developing a complete understanding of the structure and behavior of the near-wall region (NWR) in reciprocating, internal combustion (IC) engines and of its interaction with the core flow is needed to support the implementation of advanced combustion and engine operation strategies, as well as predictive computational models. The NWR in IC engines is fundamentally different from the canonical steady-state turbulent boundary layers (BL), whose structure, similarity and dynamics have been thoroughly documented in the technical literature. Motivated by this need, this paper presents results from the analysis of two-component velocity data measured with particle image velocimetry near the head of a single-cylinder, optical engine. The interaction between the NWR and the core flow was quantified via statistical moments and two-point velocity correlations, determined at multiple distances from the wall and piston positions.

Today’s Advanced Driver Assistance Systems (ADAS) predominantly utilize cameras to increase driver and passenger safety. Computer vision, as the enabler of this technology, extracts two key environmental features: the drivable region and surrounding objects (e.g., vehicles, pedestrians, bicycles). Lane lines are the most common characteristic extracted for drivable region detection, which is the core perception task enabling ADAS features such as lane departure warnings, lane-keeping assistance, and lane-centering. However, when subject to adverse weather conditions (e.g., occluded lane lines) the lane line detection algorithms are no longer operational. This prevents the ADAS feature from providing the benefit of increased safety to the driver. The performance of one of the leading computer vision system providers was tested in conditions of variable snow coverage and lane line occlusion during the 2020-2021 winter in Kalamazoo, Michigan.

The US Environmental Protection Agency (EPA)’s heavy duty diesel emission standard was tightened beginning from 2007 with the introduction of ultra-low-sulfur diesel fuel. Most heavy duty diesel applications were required to equip Particulate Matter (PM) after-treatment systems to meet the new tighter, emission standard. Systems utilizing Diesel Oxidation Catalyst (DOC) and Catalyzed-Diesel Particulate Filter (DPF) are a mainstream of modern diesel PM after-treatment systems. To ensure appropriate performance of the system, periodic cleaning of the PM trapped in DPF by its oxidation (a process called “regeneration”) is necessary. As a result, of this regeneration, DOC’s and DPF’s can be exposed to hundreds of thermal cycles during their lifetime. Therefore, to understand the thermo-mechanical performance of the DOC and DPF is an essential issue to evaluate the durability of the system.

A new high output supercharged Northstar DOHC 4.4L V8 engine has been developed for new “V” series Cadillac performance models. The new engine combines the highest power rating of any production Cadillac engine to date with operating refinement uncommon at this power level. The new engine incorporates a high capacity airflow system including a unique GM Powertrain (GMPT) patented supercharger. The design integrates the intake manifold and supercharger (SC) into a supercharger module (SCM) supplied with throttle body (TB) and intercoolers (IC). The new engine architecture is based on the naturally aspirated (NA) rear wheel drive (RWD) engine released in 2004, but has been specifically designed and upgraded from the NA version for the greater structural and thermal loads that result from supercharging.

A new generation Northstar DOHC V8 engine has been developed for a new family of rear-wheel-drive (RWD) Cadillac vehicles. The new longitudinal engine architecture includes strategically selected technologies to enable a higher level of performance and refinement. These technologies include four-cam continuously variable valve timing, low restriction intake and exhaust manifolds and cylinder head ports, a steel crankshaft, electronic throttle control, and close-coupled catalysts. Additional design features beyond those required for RWD include optimized block ribbing, improved coolant flow, and a newly developed lubrication and ventilation system for high-speed operation and high lateral acceleration. This new design results in improved performance over the entire operating range, lower emissions, improved fuel economy, improved operating refinement, and reduced noise/vibration/harshness (NVH).

Tensile measurements and fracture surface analysis of low carbon heat-treated boron steel are reported. Tensile coupons were quasi-statically deformed to fracture in a miniature tensile testing stage with custom data acquisition software. Strain contours were computed via a digital image correlation method that allowed placement of a digital strain gage in the necking region. True stress-true strain data corresponding to the standard tensile testing method are presented for comparison with previous measurements. Fracture surfaces were examined using scanning electron microscopy and the deformation mechanisms were identified.

Estimated engine torque is an important parameter used by automotive systems for automated transmission and clutch control. Heavy-duty engine and transmission manufacturers widely use SAE J -1939 based ECU torque calculation based on mass air/fuel flow steady state maps created during calibration of the engine for this purpose. As an alternative, to enhance the accuracy of this important control variable, a virtual flywheel torque sensor (VFTS) was developed. It measures the engine torque based on the harmonics of the instantaneous flywheel speed signal. Initial dynamometer testing showed the VFTS estimated torque values exhibited a maximum inaccuracy of 12% of the actual measured torque over the range of conditions tested. In this paper we report the results of on road truck testing of the VFTS. A loaded heavy truck with a gross vehicle weight rating of 80,000 pounds was used.

Under the initiative of the United States Council for Automotive Research LLC (USCAR§) Transmission Working Group, a collaborative effort was made with LuK USA LLC to study the influence of the friction interface parameters on the shudder durability of a wet launch clutch. A test bench was designed. Clutch configurations with different combinations of four friction materials (A, B, C and D), three groove patterns (waffle, radial and waffle–parallel) and two separator plate conditions (nitrided and non–nitrided) were considered. Considerable improvement in performance was seen by changing from CVT fluid* to DCT fluid*. A thermal analysis based on thermal model predictions and measurement correlations was conducted. Comparisons of clutch configurations with four and five friction plates were done. The waffle and radial groove pattern showed better heat transfer than the waffle–parallel groove pattern.

Modern vehicles use automated driving assistance systems (ADAS) products to automate certain aspects of driving, which improves operational safety. In the U.S. in 2020, 38,824 fatalities occurred due to automotive accidents, and typically about 25% of these are associated with inclement weather. ADAS features have been shown to reduce potential collisions by up to 21%, thus reducing overall accidents. But ADAS typically utilize camera sensors that rely on lane visibility and the absence of obstructions in order to function, rendering them ineffective in inclement weather. To address this research gap, we propose a new technique to estimate snow coverage so that existing and new ADAS features can be used during inclement weather. In this study, we use a single camera sensor and historical weather data to estimate snow coverage on the road. Camera data was collected over 6 miles of arterial roadways in Kalamazoo, MI.

Major emphasis on the use of lightweight components in engines has lead to widespread use of polymer intake manifolds. The pulsed flow through these manifolds combined with the lower elastic modulus materials can result in excessive noise under certain speed load conditions. Using full-field optical techniques allowed for the detection and analysis of the resonance behavior in polymer intake manifolds. The test procedures involved techniques including time-averaged holography, with variable excitation sources to identify resonating regions and associated critical frequencies. The results clearly indicate the development of an efficient test methodology to analyze manifold designs for resonance and structural characteristics

Lane detection plays a critical role in autonomous vehicles for safe and reliable navigation. Lane detection is traditionally accomplished using a camera sensor and computer vision processing. The downside of this traditional technique is that it can be computationally intensive when high quality images at a fast frame rate are used and has reliability issues from occlusion such as, glare, shadows, active road construction, and more. This study addresses these issues by exploring alternative methods for lane detection in specific scenarios caused from road construction-induced lane shift and sun glare. Specifically, a U-Net, a convolutional network used for image segmentation, camera-based lane detection method is compared with a radar-based approach using a new type of sensor previously unused in the autonomous vehicle space: radar retro-reflectors.

Practical applications of recently developed sensor fusion algorithms perform poorly in the real world due to a lack of proper evaluation during development. Existing evaluation metrics do not properly address a wide variety of testing scenarios. This issue can be addressed using proactive performance measurements such as the tools of resilience engineering theory rather than reactive performance measurements such as root mean square error. Resilience engineering is an established discipline for evaluating proactive performance on complex socio-technical systems which has been underutilized for automated vehicle development and evaluation. In this study, we use resilience engineering metrics to assess the performance of a sensor fusion algorithm for vehicle localization. A Kalman Filter is used to fuse GPS, IMU and LiDAR data for vehicle localization in the CARLA simulator.

Contemporary ADS and ADAS localization technology utilizes real-time perception sensors such as visible light cameras, radar sensors, and lidar sensors, greatly improving transportation safety in sufficiently clear environmental conditions. However, when lane lines are completely occluded, the reliability of on-board automated perception systems breaks down, and vehicle control must be returned to the human driver. This limits the operational design domain of automated vehicles significantly, as occlusion can be caused by shadows, leaves, or snow, which all occur in many regions. High-definition map data, which contains a high level of detail about road features, is an alternative source of the required lane line information. This study details a novel method where high-definition map data are processed to locate fully occluded lane lines, allowing for automated path planning in scenarios where it would otherwise be impossible.

Automotive companies are constantly looking to increase the fuel efficiency, shift quality, passenger comfort, and to reduce wear and tear on the components. Most of these aspects depend on the accuracy of torque used for transmission control, which determines the required operational gear position at a given speed and road conditions. Currently, SAE J-1939 CAN bus torque estimation relies on steady state maps that are generated during the calibration of the engine for different speeds and loads. In this paper we report the development of a Virtual Flywheel Torque Sensor (VFTS) useful for real time torque measurement based on an engine speed harmonics analysis. The VFTS uses a signal from the flywheel speed sensor to estimate the flywheel angular acceleration, which and provides a proportional torque value which corresponds to torque at the flywheel.

PEM Fuel Cell technology has been advancing rapidly during the last several years as evidenced by various vehicle demonstrations by the major automotive companies. As the development continues to bring hardware to automotive system level solutions, many engineering challenges arise. This paper will deal with two (2) of these areas from an automotive system level perspective: Thermal Management and the Fuel Cell Stack. Both of these sub-system areas are critical to the success of the technology in meeting the requirements of tomorrow's automotive customer.

An optimum combustion chamber was designed for a reverse-tumble wall-controlled gasoline direct-injection engine by systematically optimizing each design element of the combustion system. The optimization was based on fuel-economy, hydrocarbon, combustion-stability and smoke measurements at a 2000 rev/min test-point representation of road-load operating condition. The combustion-chamber design parameters that were optimized in this study included: piston-bowl depth, piston-bowl opening width, piston-bowl-volume ratio, exhaust-side squish height, bowl-lip draft angle, distance between spark-plug electrode and piston-bowl lip, spark-plug-electrode length, and injector spray-cone angle. No attempt was made to optimize the gross engine parameters such as bore and stroke or the intake system, since this study focused on optimizing a reverse-tumble wall-controlled gasoline direct-injection variant of an existing port-fueled injection engine.

Diesel engines offer better fuel economy compared to their gasoline counterpart, but simultaneous control of NOx and particulates is very challenging. The blended 2-way SCR/DPF is recently emerging as a compact and cost-effective technology to reduce NOx and particulates from diesel exhaust using a single aftertreatment device. By coating SCR catalysts on and inside the walls of the conventional wall-flow filter, the 2-way SCR/DPF eliminates the volume and mass of the conventional SCR device. Compared with the conventional diesel aftertreatment system with a SCR and a DPF, the 2-way SCR/DPF technology offers the potential of significant cost saving and packaging flexibility. In this study, an engine dynamometer test cell was set up to repeatedly load and regenerate the SCR/DPF devices to mimic catalyst aging experienced during periodic high-temperature soot regenerations in the real world.

Heat transfer to the combustion chamber walls constitutes a significant portion of the overall energy losses over the working cycle of a direct injection (DI) diesel engine. In the last few decades, numerous research efforts have been devoted to investigating the prospects of boosting efficiency by insulating the combustion chamber. Relatively few studies have focused on the prospects of reducing emissions by applying combustion chamber insulation. A main purpose of this study is to assess the potential of reducing in-cylinder soot as well as boosting aftertreatment performance by means of partially insulating the combustion chamber. Based on the findings from a conceptual study, a Low Heat Rejection (LHR) design, featuring a Nimonic 80A insert into an Aluminum piston, was developed and tested experimentally at various loads in a single-cylinder Hatz-engine.