Search Results

In order to detect degradation of engine oil lubricant, bench testing along with a number of diesel-powered Ford trucks were instruments and tested. The purpose of the bench testing was primarily to determine performance aspects such as repeatability, hysteresis effects and so on. Vehicle testing was conducted by designing and installing a separate oil reservoir along with a circulation system which was mounted in the vicinity of the oil pan. An innovative oil sensor was directly installed on the reservoir which can measure five (5) independent oil parameters (viscosity, density, permittivity, conductance, temperature). In addition, the concept is capable of detecting the oil level continuously during normal engine operation. The sensing system consists of an ultrasonic transducer for the oil level detection as well as a Tuning Fork mechanical resonator for the oil condition measurement.

Exhaust manifold design is one of the more challenging tasks for the engine engineer due to the harsh thermal and severe vibration environment. Extremely high exhaust gas temperatures and dynamic loading combine to subject the manifold to high cyclic stress when the material has reduced fatigue strength due to the high temperature. A long service life before a fatigue failure is the objective in exhaust manifold design. Accumulation of fatigue damage can occur from dynamic loading and thermal loading combined. Thermal mechanical fatigue (TMF) is a primary mechanism for accumulating fatigue damage. TMF typically occurs when a vehicle driving cycle has operating conditions that repeatedly change the exhaust gas temperature between hot and cold. Another way to experience temperature cycling is through splash quenching. Splash quenching was analyzed and found to rapidly accumulate fatigue damage.

This work reports on measurement and analysis of the galvanic interaction between steel self-piercing rivets (SPRs) having several different surface conditions and magnesium alloy substrates under consideration for use in automotive structural assemblies. Rivet surface conditions included uncoated steel, conventional Zn-Sn barrel plating and variations of commercial aluminizing processes, including supplemental layers and sealants. Coating characteristics were assessed using open circuit potential (OCP) measurement, potentiodynamic polarization scanning (PDS), and electrochemical impedance spectroscopy (EIS). The degree of galvanic coupling was determined using zero-resistance ammeter (ZRA) and the scanning vibrating electrode technique (SVET), which also permitted characterization of galvanic current flows in situ.

Vehicle to Vehicle Communication use case performance heavily relies on market penetration rate. The more vehicles support a use case, the better the customer experience. Enabling these use cases with acceptable quality on vehicles without built-in navigation systems, elaborate map matching and highly accurate sensors is challenging. This paper introduces a simulation framework to assess system performance in dependency of vehicle positioning accuracy for matching approach path traces in Decentralized Environmental Notification Messages (DENMs) in absence of navigation systems supporting map matching. DENMs are used for distributing information about hazards on the road network. A vehicle without navigation system and street map can only match its position trajectory with the trajectory carried in the DENM.

With the trending electrification of vehicle accessory drives brings new control concepts useful in many cases to optimize energy management within the powertrain system. Considering that direct engine drives do not have as much flexibility as independent electric drives, it is apparent that several advantages are to be expected from electric drives. New developed high efficient electric drives can be implemented when considering many vehicle sub-systems. Combinations of continuous varying and discrete flow control devices offer thermal management opportunities across several vehicle attributes including fuel economy, drivability, performance, and cabin comfort. Often new technologies are integrated with legacy systems to deliver maximum value. Leveraging both electrical and mechanical actuators in some cases presents control challenges in optimizing energy management while delivering robust system operation.

The usage of the universal exhaust gas oxygen (UEGO) sensor to control the air-fuel ratio (AFR) in gasoline engines allowed to significantly improve the efficiency of the combustion process and reduce tailpipe emissions. The diagnostics of this sensor is very important to ensure proper operation and indicate the need for service when the sensor fails to accurately determine the AFR upstream of the catalyst. California air resources board (CARB) has imposed several legislations around the operation of the UEGO sensor and particularly when specific faults would cause tailpipe emissions to exceed certain limits. In this paper, the possible sensor faults are reviewed, and a non-intrusive diagnostics monitor is proposed to detect, identify and estimate the magnitude of the fault present. This paper extends the approach in [4] where technical details are emphasized and algorithm improvements are discussed.

This paper focuses on finding and analyzing the relevant parameters affecting traffic flow when autonomous vehicles are introduced for ride hailing applications and autonomous shuttles are introduced for circulator applications in geo-fenced urban areas. For this purpose, different scenarios have been created in traffic simulation software that model the different levels of autonomy, traffic density, routes, and other traffic elements. Similarly, software that specializes in vehicle dynamics, physical limitations, and vehicle control has been used to closely simulate realistic autonomous vehicle behavior under such scenarios. Different simulation tools for realistic autonomous vehicle simulation and traffic simulation have been merged together in this paper, creating a realistic simulator with Hardware-in-the-Loop (HiL), Traffic-in-the-Loop (TiL), and Software in-the-Loop (SiL) simulation capabilities.

Autonomous Vehicles (AVs) operate based on image information and 3D maps generated by sensors like cameras, LIDARs and RADARs. This information is processed by the on-board processing units to provide the right actuation signals to drive the vehicle. For safe operation, these sensors should provide continuous high quality data to the processing units without interruption in all driving conditions like dust, rain, snow and any other adverse driving conditions. Any contamination on the sensor surface/lens due to rain droplets, snow, and other debris would result in adverse impact to the quality of data provided for sensor fusion and this could result in error states for autonomous driving. In particular, snow is a common contamination condition during driving that might block a sensor surface or camera lens. Predicting and preventing snow accumulation over the sensor surface of an AV is important to overcome this challenge.

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.

Progress in the design and application of the magneto-elastic torque sensor to automotive drivetrain systems has taken the technology from the concept level to the point where it is considered production feasible. The latest generation of the sensors shows promising results regarding both the capabilities and applications to powertrain controls. Sensor designs, electronics and packaging layout are maturing. Well-defined component specifications and requirements are becoming available. The sensor utilities for real-time shift analysis and friction element control are established through vehicle-level investigation to demonstrate the production feasibility of the technology for transmission torque sensing.

An advanced powertrain cooling system with appropriate control strategy and active actuators allows greater flexibility in managing engine temperatures and operating near constraints. An organized controls development process is necessary to allow comparison of multiple configurations to select the best way forward. In this work, we formulate, calibrate and validate a Model Predictive Controller (MPC) for temperature regulation and constraint handling in an advanced cooling system. A model-based development process was followed; where the system model was used to develop and calibrate a gain scheduled linear MPC. The implementation of MPC for continuous systems and the modification related to implementing switching systems has been described. Multiple hardware configurations were compared with their corresponding control system in simulations. The system level requirements were translated into MPC calibration parameters for consistent comparison between multiple configurations.

With the rapid development of artificial intelligence, the autonomous vehicles (AV) have attracted considerable attention in the automotive industry. However, different factors negatively impact the adoption of the AVs, delaying their successful commercialization. Accretion of atmospheric icing, especially wet snow, on AV sensors causes blockage on their lenses, making them prone to lose their sight, in turn, increasing potential chances of accidents. In this study, two different designs are proposed in order to prevent snow accretion on the lenses of AVs via air flow across the lens surface. In both designs, lenses made of plain glass and superhydrophobic coated glass surfaces are tested. While some researchers have shown promise of water repellency on superhydrophobic surfaces, more snow accretion is observed on the superhydrophobic surfaces, when compared to the plain glass lenses.

One-dimensional simulation tools are used extensively in the automotive industry to improve and optimize engine design for WOT performance. They are useful in target setting and in assessing the effects of certain design changes (e.g. intake manifold, valve timing, exhaust manifold, etc.). Generally the inputs to these models are “nominal” values or curves from a particular set of data and, therefore, do not take into account design or assembly variations. Often times, performance expectations are not met due to these “real world” effects and may result in significant re-design and testing efforts. The purpose of this paper is to assess the impact of typical model input variation on engine performance and to instill greater confidence in the use of these models in forecasting performance. The approach taken is to collect, analyze, and categorize actual build measurements from a 4.6L 4V Ford engine that are considered important inputs for a one-dimensional modeling.

The interface between a plenum and primary runner in log-style intake manifolds is one of the dominant sources of flow losses in the breathing system of Internal Combustion Engines (ICE). A right-angled T-junction is one such interface between the plenum (main duct) and the primary runner (sidebranch) normal to the plenum's axis. The present study investigates losses associated with the combining flow through these junctions, where fluid from both sides of the plenum enters the primary runner. Steady, incompressible-flow experiments for junctions with circular cross-sections were conducted to determine the effect of (1) runner interface radius of 0, 10, and 20% of the plenum diameter, (2) plenum-to-runner area ratio of 1, 2.124, and 3.117, and (3) runner taper area ratio of 2.124 and 3.117. Mass flow rate in each branch was varied to obtain a distribution of flow ratios, while keeping the total flow rate constant.

An assessment tool was developed for rollover CAE signals evaluation to assess primarily the qualities of CAE generated sensor waveforms. This is a key tool to be used to assess CAE results as to whether they can be used for algorithm calibration and identify areas for further improvement of sensor. Currently, the method is developed using error estimates on mean, peak and standard deviation. More metrics, if necessary, can be added to the assessment tool in the future. This method has been applied to various simulated signals for laboratory-based rollover test modes with rigid-body-based MADYDO models.

Optical based sensor systems for vehicle based detection and warning systems are under development to reduce accidents and limit injuries caused by accidents. (1, 2, 3) In order to validate these types of detection systems, it is necessary to perform real world tests. In the case of pedestrian detection systems, this is very difficult in the field for safety reasons. Instead, simulated tests are more desirable. This paper describes work to understand the effectiveness of using virtual pedestrians as surrogates for real world pedestrian detection.

Understanding the variation in the deployment times for crash sensor systems is important to ensure robust performance of a crash sensor system. Increases in both the numbers of crash modes and deployable devices have reduced the margins for the decisions about when to deploy any given device. Currently, the industry practice is to run a sweep over the potential sources of variation, recording the minimum and maximum deployment time. Questions such as: “How often do the extremes occur?” or “Are there multiple peaks in the deployment time?” can not be answered. This work uses numerical analysis methods to build on the current sweep methodology to obtain information on the distribution of the deployment times so that questions such as these can be answered when evaluating sensor calibrations. The end result is better informed engineering decisions during the calibration development.

This study measures, during various transients of speed and load, in-cylinder-, intake-/exhaust- (manifold) pressures and engine torque. The tests were conducted on a typical high power-density, passenger car powertrain (common-rail diesel engine, of in-line 4-cylinder configuration equipped with a Variable Geometry Turbocharger). The objective was to quantify the deterioration (relative to a steady-steady condition) in transient Specific Fuel Consumption (SFC) that may occur during lagged-boost closed-loop control and thus propose an engine control strategy that minimises the transient SFC deterioration. The results, from transient characterisation and the analysis method applied in this study, indicate that transient SFC can deteriorate up to 30% (function of load transient) and is primarily caused by excessive engine pumping-loss.

Current methods of storing critical engine operating parameters often rely on lookup interpolation functions. A drawback to lookup interpolations is that as the number of independent variables increases, the function's dimensions increase from tables to cubes to hypercubes of data. A sparser collection of data may serve if the strict orthogonal structure of lookup functions is not required. Instead of forming a matrix of data for every combination of input variables, a few critical data points are stored with their independent variables. The available data can be used to estimate parameters at new input values (typically from current measurements) by relating the available data by its distance from the new inputs. An inverse distance weighting scheme is used to calculate the output of the function.

One of the dominant sources of flow losses in the intake system of internal combustion engines (ICE) with log-style manifolds is the interface between the plenum and primary runner. The present study investigates such losses associated with the dividing flow at the entry to primary runner with geometries representative of those used in ICE. An experimental setup was constructed to measure the flow loss coefficients of T-junctions with all branches of circular cross-section. Experiments were conducted with seven configurations on a steady-flow bench to determine the effects of: (1) interface radius equal to 0, 10, and 20% of the primary runner diameter, (2) plenum to primary runner area ratios of 1, 2.124, and 3.117, and (3) primary runner taper including taper area ratios of 2.124 and 3.117. The last two categories employed 20% interface radii. The total mass flow rate was also varied to investigate the effect of Reynolds number Re on loss coefficients.