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.

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.

We developed a technique to measure oil film pressure distribution in engine main bearings using thin-film pressure sensors. The sensor is 7μm in thickness, and is processed on the surface of an aluminum alloy bearing. In order to increase the durability of the sensor, a layer of MoS2 and polyamide-imide was coated on thin-film sensors. This technique was applied to a 1.4L common-rail diesel engine operated at a maximum speed of 4,500r/min with a 100Nm full load, and the oil film pressure was monitored while the engine was operating. The measured pressure was compared with calculations based on hydrodynamic lubrication (HL) theory.

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.

The purpose of this paper is to construct the thermal analysis model by measuring and estimating the temperature at the traction contact area. For measurement of temperature, we have used a thin-film temperature sensor. For estimation of temperature, we have composed the thermal analysis model. The thin-film temperature sensor was formed on the contact surface using a spattering device. The sensor is constituted of three layers (sensor layer, insulation layer and intermediate layer). Dimensions of the sensor were sufficiently smaller than the traction contact area. The sensor featured high specific pressure capacity and high speed responsiveness. The thermal analysis model was mainly composed of three equations: Carslaw & Jaeger equation, Rashid & Seireg equation and heat transfer equation of shear heating in oil film. The heat transfer equation involved two models (local shear heating model at middle plane, homogeneous shear heating model).

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.

Crosscheck tests of fast electrical mobility spectrometers, Differential Mobility Spectroscopy (DMS) and Engine Exhaust Particle Sizer(EEPS), were conducted to evaluate the accuracy of fine particle measurement. Two kinds of particles were used as test particles for the crosscheck test of instruments: particles emitted from diesel vehicles and diluted in a full dilution tunnel, and particles generated by CAST. In the steady state tests, it was confirmed that the average concentration of each instrument was within the range of ±2σ from the average concentration of all the same type of instruments. In the transient tests, it is verified that the instruments have almost equal sensitivity. For application of the fast electrical mobility spectrometers to evaluation of particle number and size distributions, it is essential to develop a calibration method using reference particle counters and sizers (CPC, SMPS, etc.) and maintenance methods appropriate for each model.

This paper introduces the cruise control system with distance control function, that is called Adaptive Cruise Control (ACC), that uses a scanning laser radar as a sensor to detect preceding vehicles. With the goal of increasing the driving convenience and comfort when compared to the conventional cruise control, lots of ACC systems have been proposed and developed. This paper presents ACC system using the scanning laser radar which was developed by Toyota, and describes the adaptation of the system specifications. This ACC system was able to greatly reduce the driver's work load, and increased the driver's convenience and comfort when operating the cruise controls system. In addition, we were able to design this system to be highly dependable and inexpensive and supply it to the market as a result of incorporating various ideas for improvements.

In this paper, we will introduce a stereo vision system developed as a sensor for a vehicle's front monitor. This system consists of three parts; namely, a stereo camera that collects video images of the forward view of the vehicle, a stereo ECU that processes its output image, and a near-infrared floodlight for illuminating the front at night. We were able to develop an obstacle detection function for the Pre-Crash Safety System and also a traffic lane detection function for a Lane-Keeping Assist System. Especially in regard to the obstacle detection function, we were able to achieve real-time processing of the disparity image calculations that had formerly required long processing times by using two types of recently developed LSIs.

An obstacle recognition algorithm for the Pre-Crash Safety system has been newly developed with a stereo vision system and a millimeter wave radar with additional functions. This algorithm uses the merits of both the millimeter wave radar and the stereo vision system, and has two main features. One feature utilizes the merits of the stereo vision system detection with the detection results from the millimeter wave radar allowing for a more detailed horizontal position and width of the obstacle. This enables the equipment to operate at an earlier stage according to how well the relationship between the vehicle and the obstacle is understood. Another feature fuses detection from the millimeter wave radar and the stereo vision system. This system has succeeded in enhancing the detection performance of pedestrians who have been more difficult to detect than reflective objects such as cars.

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.

Due to regulations for even lower levels of pollutants in exhaust gas, development of advanced combustion techniques and increasingly efficient catalysts has become more crucial than ever. One of the essential technologies to achieve this goal is an advanced measurement method, which can detect the characteristics of exhaust gas, such as temperature and chemical compositions, in real-time to clarify their reaction mechanisms. A direct and fast response (1ms) measurement technique was developed based on diode laser absorption spectroscopy and applied to practical engine exhaust measurement to prove the validity of this technology for various applications such as clarification of engine start phenomena and improvement of EGR controls.