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In a Spark-Ignited engine, there will come a point, as load is increased, where the unburned air-fuel mixture undergoes auto-ignition (knock). The onset of knock represents the upper limit of engine output, and limits the extent of engine downsizing / boosting that can be implemented for a given application. Although effective at mitigating knock, requiring high octane fuel is not an option for most markets. Retarding spark timing can extend the high load limit incrementally, but is still bounded by limits for exhaust gas temperature, and spark retard results in a notable loss of efficiency. Likewise, enriching the air-fuel mixture also decreases efficiency, and has profound negative impacts on engine out emissions. In this current work, a Direct-Injected, Boosted, Spark-Ignited engine with Variable Valve Timing was tested under steady state high load operation. Comparisons were made among three fuels; an 87 AKI, a 91 AKI, and a 110 AKI off-road only race fuel.

Autonomous vehicle operation is dependent upon accurate position estimation and thus a major concern of implementing the autonomous navigation is obtaining robust and accurate data from sensors. This is especially true, in case of Inertial Measurement Unit (IMU) sensor data. The IMU consists of a 3-axis gyro, 3-axis accelerometer, and 3-axis magnetometer. The IMU provides vehicle orientation in 3D space in terms of yaw, roll and pitch. Out of which, yaw is a major parameter to control the ground vehicle’s lateral position during navigation. The accelerometer is responsible for attitude (roll-pitch) estimates and magnetometer is responsible for yaw estimates. However, the magnetometer is prone to environmental magnetic disturbances which induce errors in the measurement.

In-cylinder ion sensing is a subject of interest due to its application in spark-ignited (SI) engines for feedback control and diagnostics including: combustion knock detection, rate and phasing of combustion, and mis-fire On Board Diagnostics (OBD). Further advancement and application is likely to continue as the result of the availability of ignition coils with integrated ion sensing circuitry making ion sensing more versatile and cost effective. In SI engines, combustion knock is controlled through closed loop feedback from sensor metrics to maintain knock near the borderline, below engine damage and NVH thresholds. Combustion knock is one of the critical applications for ion sensing in SI engines and improvement in knock detection offers the potential for increased thermal efficiency. This work analyzes and characterizes the ionization signal in reference to the cylinder pressure signal under knocking and non-knocking conditions.

This paper evaluates the potential of adding higher alcohols to gasoline blendstock in an attempt to improve overall fuel performance. The alcohols considered include ethanol, normal- and iso-structures of propanol, butanol and pentanol as well as normal-hexanol (C2-C6). Fuel performance is quantified based on energy content, knock resistance as well as petroleum displacement and promising multi-component blends are systematically identified based on property prediction methods. These promising multi-component blends, as well as their respective reference fuels, are subsequently tested for efficiency and emissions performance utilizing a gasoline direct injection, spark ignition engine. The engine test results confirm that combustion and efficiency of tailored multi-component blends closely match those of the reference fuels. Regulated emissions stemming from combustion of these blends are equal or lower compared to the reference fuels across the tested engine speed and load regime.

An accurate estimation of cycle-by-cycle in-cylinder mass and the composition of the cylinder charge is required for spark-ignition engine transient control strategies to obtain required torque, Air-Fuel-Ratio (AFR) and meet engine pollution regulations. Mass Air Flow (MAF) and Manifold Absolute Pressure (MAP) sensors have been utilized in different control strategies to achieve these targets; however, these sensors have response delay in transients. As an alternative to air flow metering, in-cylinder pressure sensors can be utilized to directly measure cylinder pressure, based on which, the amount of air charge can be estimated without the requirement to model the dynamics of the manifold.

The characteristics of combustion knock metrics over a number of engine cycles can be an essential reference for knock detection and control in internal combustion engines. In a Spark-Ignition (SI) engine, the stochastic nature of combustion knock has been shown to follow a log-normal distribution. However, this has been derived from experiments done with gasoline only and applicability of log-normal distribution to dual-fuel combustion knock has not been explored. To evaluate the effectiveness and accuracy of log-normal distributed knock model for methane-gasoline blended fuel, a sweep of methane-gasoline blend ratio was conducted at two different engine speeds. Experimental investigation was conducted on a single cylinder prototype SI engine equipped with two fuel systems: a direct injection (DI) system for gasoline and a port fuel injection (PFI) system for methane.

Higher carbon number alcohols offer an opportunity to meet the Renewable Fuel Standard (RFS2) and improve the energy content, petroleum displacement, and/or knock resistance of gasoline-alcohol blends from traditional ethanol blends such as E10 while maintaining desired and regulated fuel properties. Part II of this paper builds upon the alcohol selection, fuel implementation scenarios, criteria target values, and property prediction methodologies detailed in Part I. For each scenario, optimization schemes include maximizing energy content, knock resistance, or petroleum displacement. Optimum blend composition is very sensitive to energy content, knock resistance, vapor pressure, and oxygen content criteria target values. Iso-propanol is favored in both scenarios' suitable blends because of its high RON value.

The U.S. Renewable Fuel Standard (RFS2) requires an increase in the use of advanced biofuels up to 36 billion gallons by 2022. Longer chain alcohols, in addition to cellulosic ethanol and synthetic biofuels, could be used to meet this demand while adhering to the RFS2 corn-based ethanol limitation. Higher carbon number alcohols can be utilized to improve the energy content, knock resistance, and/or petroleum displacement of gasoline-alcohol blends compared to traditional ethanol blends such as E10 while maintaining desired and regulated fuel properties. Part I of this paper focuses on the development of scenarios by which to compare higher alcohol fuel blends to traditional ethanol blends. It also details the implementation of fuel property prediction methods adapted from literature. Possible combinations of eight alcohols mixed with a gasoline blendstock were calculated and the properties of the theoretical fuel blends were predicted.

A new press/die system for restraining force control has been developed in order to facilitate an increased level of process control in sheet metal forming. The press features a built-in system for controlling drawbead penetration in real time. The die has local force transducers built into the draw radius of the lower tooling. These sensors are designed to give process information useful for the drawbead control. This paper focuses on developing models of the drawbead actuators and the die shoulder sensors. The actuator model is useful for developing optimal control methods. The sensor characterization is necessary in order to develop a relationship between the raw sensor outputs and a definitive process characteristic such as drawbead restraining force (DBRF). Closed loop control of local specific punch force is demonstrated using the die shoulder sensor and a PID controller developed off-line with the actuator model.

Combustion knock detection and control in internal combustion engines continues to be an important feature in engine management systems. In spark-ignition engine applications, the frequency of occurrence of combustion knock and its intensity are controlled through a closed-looped feedback system to maintain knock at levels that do not cause engine damage or objectionable audible noise. Many methods for determination of the feedback signal for combustion knock in spark-ignition internal combustion engines have been employed with the most common technique being measurement of engine vibration using an accelerometer. With this technique single or multiple piezoelectric accelerometers are mounted on the engine and vibrations resulting from combustion knock and other sources are converted to electrical signals. These signals are input to the engine control unit and are processed to determine the signal strength during a period of crank-angle when combustion knock is expected.

Today's advanced technology engines have a high content of electronic actuation requiring sophisticated real-time embedded software sensing and control. To enable research on such engines, a system with a flexible engine control unit (ECU) that can be rapidly configured and programmed is desired. Such a system is being used in the Advanced Internal Combustion Engine (AICE) Laboratories at Michigan Tech University (MTU) for research on a multi-cylinder spark-ignited gasoline, a high pressure common rail diesel and a single cylinder alternative fuels research engine. The system combines a production ECU with a software development system utilizing Mathworks Simulink/Stateflow © modeling tools. The interface in the Simulink modeling environment includes a library of modeling and interface blocks to the production Operating System (OS), Low Level Drivers (LLD) and CAN-based calibration tool.

The effect of high pressure injection (using an accumulator type unit injector with peak injection pressure of approximately 20,000 psi, having a decreasing injection rate profile) on combustion was studied. Combustion results were obtained using a DDA Series 3–53 diesel engine with both conventional analysis techniques and high speed photography. Diesel No. 2 fuel and a low viscosity - high volatility fuel, similar to gasoline were used in the study. Results were compared against baseline data obtained with standard injectors. Some of the characteristics of high pressure injection used with Diesel No. 2 fuel include: substantially improved ignition, shorter ignition delay, and higher pressure rise. Under heavy load - high speed conditions, greater smokemeter readings were achieved with the high pressure injection system with Diesel No. 2 fuel. Higher flame speeds and hence, greater resistance to knock were observed with the high volatility low cetane fuel.

This is the second part of a study on using port water injection to quantifiably enhance the knock performance of fuels. In the United States, the metric used to quantify the anti-knock performance of fuels is Anti Knock Index (AKI), which is the average of Research Octane Number (RON) and Motor Octane Number (MON). Fuels with higher AKI are expected to have better knock mitigating properties, enabling the engine to run closer to Maximum Brake Torque (MBT) spark timing in the knock limited region. The work done in part I of the study related increased knock tolerance due to water injection to increased fuel AKI, thus establishing an ‘effective AKI’ due to water injection. This paper builds upon the work done in part I of the study by repeating a part of the test matrix with Primary Reference Fuels (PRFs), with iso-octane (PRF100) as the reference fuel and lower PRFs used to match its performance with the help of port water injection.

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.

The drive of Design for the Environment is to reduce the environmental impact of both design and manufacturing processes. The most frequent method recommended is to substitute better materials and processes. However, there are processes that will continue to have undesirable environmental impacts due to the lack of knowledge of better methods. These processes are critical to manufacturing of products and can not be eliminated. All possible substitutions appear to have worse impacts. This paper explores modeling these processes and imposing a control method which permits an improvement of the environmental impact.

To model sprays from pressure-swirl atomizers, the connection between the injector and the downstream spray must be considered. A new model for pressure-swirl atomizers is presented which assumes little knowledge of the internal details of the injector, but instead uses available observations of external spray characteristics. First, a correlation for the exit velocity at the injector exit is used to define the liquid film thickness. Next, the film must be modeled as it becomes a thin, liquid sheet and breaks up, forming ligaments and droplets. A linearized instability analysis of the breakup of a viscous, liquid sheet is used as part of the spray boundary condition. The spray angle is estimated from spray photographs and patternator data. A mass averaged spray angle is calculated from the patternator data and used in some of the calculations.

The increased availability of natural gas (NG) in the United States (US), and its relatively low cost compared to diesel fuel has heightened interest in the conversion of medium duty (MD) and heavy duty (HD) engines to NG fueled combustion systems. The aim is to realize fuel cost savings and reduce harmful emissions, while maintaining durability. This is a potential path to help the US reduce dependence on crude oil. Traditionally, port-fuel injection (PFI) or premixed NG spark-ignited (SI) combustion systems have been used for MD and HD engines with widespread use in the US and Europe; however, this technology exhibits poor cycle efficiency and is load limited due to knock phenomenon. Direct Injection of NG during the compression stroke promises to deliver improved thermal efficiency by avoiding excessive premixing and extending the lean limits which helps to extend the knock limit.

The Electronic Control Unit (ECU) of an Electric Power Steering (EPS) system is a core device to decide how much assistance an electric motor applies on a steering wheel. The EPS ECU plays an important role in EPS systems. The effectiveness of an ECU needs to be thoroughly tested before mass production. Hardware-in-the-loop simulation provides an efficient way for the development and testing of embedded controllers. This paper focuses on the development of a HiL system for testing EPS controllers. The hardware of the HiL system employs a dSPACE HiL simulator. The EPS plant model is an integrated model consisting of a Vehicle Dynamics model of the dSPACE Automotive Simulation Model (ASM) and the Nexteer Steering model. The paper presents the design of an EPS HiL system, the simulation of sensors and actuators, the functions of the ASM Vehicle Dynamics model, and the integration method of the ASM Vehicle Dynamics model with a Steering model.

To reduce the number and severity of accidents, automakers have invested in active safety systems to detect and track neighboring vehicles to prevent accidents. These systems often employ RADAR and LIDAR, which are not degraded by low lighting conditions. In this research effort, reflections from deer were measured using two sensors often employed in automotive active safety systems. Based on a total estimate of one million deer-vehicle collisions per year in the United States, the estimated cost is calculated to be $8,388,000,000 [1]. The majority of crashes occurs at dawn and dusk in the Fall and Spring [2]. The data includes tens of thousands of RADAR and LIDAR measurements of white-tail deer. The RADAR operates from 76.2 to 76.8 GHz. The LIDAR is a time-of-flight device operating at 905 nm. The measurements capture the deer in many aspects: standing alone, feeding, walking, running, does with fawns, deer grooming each other and gathered in large groups.

At the onset of soak, air and surface temperatures in an engine bay enclosure are elevated since temperature of heat sources are high while convective cooling is sharply reduced as a result of airflow being shut off from the inlet grilles of the vehicle leading to temperature spikes. Accurate simulation of this important thermal and flow regime that is natural convection driven, highly transient and complex is therefore very important. In this investigation, we simulate flow in the engine bay at the onset of soak with fixed thermal boundary conditions where the geometries representing the engine bay and components are simplified. Good agreement was observed with detailed experimental data available in references for both velocities and temperatures.