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Viewing 1 to 30 of 3149
2017-06-05
Technical Paper
2017-01-1783
Chris Todter, Olivier Robin, Paul Bremner, Christophe Marchetto, Alain Berry
Abstract Surface pressure measurements using microphone arrays are still challenging, especially in an automotive context with cruising speeds around Mach 0.1. The separated turbulent boundary layer excitation and the side mirror wake flow generate both acoustic and aerodynamic components, which have wavenumbers that differ by a factor of approximately 10. This calls for high spatial resolution measurements to fully resolve the wavenumber-frequency spectrum. In a previous publication [1], the authors reported a micro-electro-mechanical (MEMS) surface microphone array that successfully used wavenumber analysis to quantify acoustic versus turbulence loading. It was shown that the measured surface pressure at each microphone could be strongly influenced by self-noise induced by the microphone “packaging”, which can be attenuated with a suitable windscreen.
2017-06-05
Technical Paper
2017-01-1829
Guillaume Loussert
Abstract The new fuel efficiency and emission standards have forced OEMs to put emphasis on different strategies such as engine downsizing, cylinder deactivation… Unfortunately these new technologies may lead to increased powertrain vibrations generated by the engine and transmitted to the chassis and the car cabin, such that their reduction or elimination has become a key topic for the automotive industry. The use of active engine mounts, acting directly on the fluid of an hydromount, or active vibration dampers, acting as an inertial mass-spring system, are very effective solutions, particularly when using electromagnetic based actuators. Nevertheless, all electromagnetic actuators technologies are not equals and the choice of such actuators must be considered carefully by taking into account the full performances and the overall cost of the solutions.
2017-03-28
Technical Paper
2017-01-1140
Yang Xu, Yuji Fujii, Edward Dai, James McCallum, Gregory Pietron, Guang Wu, Hong Jiang
Abstract A transmission system model is developed at various complexities in order to capture the transient behaviors in drivability and fuel economy simulations. A large number of model parameters bring more degree of freedom to correlate with vehicular test data. However, in practice, it requires extensive time and effort to tune the parameters to satisfy the model performance requirements. Among the transmission model, a hydraulic clutch actuator plays a critical role in transient shift simulations. It is particularly difficult to tune the actuator model when it is over-parameterized. Therefore, it is of great importance to develop a hydraulic actuator model that is easy to adjust while retaining sufficient complexity for replicating realistic transient behaviors. This paper describes a systematic approach for reducing the hydraulic actuator model into a piecewise 1st order representation based on piston movement.
2017-03-28
Technical Paper
2017-01-1222
Jeongwon Rho, Jeongbin Yim, Daewoong Han, Gubae Kang, Seongyeop Lim
Abstract The current sensor for motor control is one of the main components in inverters for eco-friendly vehicles. Recently, as the higher performance of torque control has become required, the current sensor measurement error and accuracy of motor controls have become more significant. Since the response time of the sensor affects the motor output power, the response delay of the sensor causes measurement errors of the current. Accordingly, the voltage vector changes, and a motor output power deviation occurs. In the case of the large response delay of the sensor, as motor speed increases, then difference between motoring and generating output power becomes larger and larger. This results in the deterioration of power performance in high-speed operation. The deviation of the voltage vector magnitude is the main cause of motor output power deviation and imbalance through the simulation.
2017-03-28
Technical Paper
2017-01-1503
Jared Johan Engelbrecht, Tony Russell Martin, Piyush M. Gulve, Nagarjun Chandrashekar, Amol Dwivedi, Peter Thomas Tkacik, Zachary Merrill
Abstract Most commercial heavy-duty truck trailers are equipped with either a two sensor, one modulator (2S1M) or four sensors, two modulator (4S2M) anti-lock braking system (ABS). Previous research has been performed comparing the performance of different ABS modules, in areas such as longitudinal and lateral stability, and stopping distance. This study focuses on relating ABS module type and wheel speed sensor placement to trailer wheel lock-up and subsequent impact to tire wear for tandem axle trailers with the Hendrickson air-ride suspension. Prior to tire wear inspection, functionality of the ABS system was testing using an ABS scan tool communicating with the SAE J1587 plug access port on the trailer. Observations were documented on trailers using the 2S1M system with the wheel speed sensor placed on either the front or rear axle of a tandem pair.
2017-03-28
Technical Paper
2017-01-1572
Wesley Kerstens
Abstract The detection and diagnosis of sensor faults in real-time is necessary for satisfactory performance of vehicle Electronic Stability Control (ESC) and Roll Stability Control (RSC) systems. This paper presents an observer designed to detect faults of a roll rate sensor that is robust to model uncertainties and disturbances. A reference vehicle roll angle estimate, independent of roll-rate sensor measurement, is formed from available ESC inertial sensor measurements. Residuals are generated by comparing the reference roll angle and roll rate, with the observer outputs. Stopping rules based on the current state of the vehicle and the magnitude of the residuals are then used to determine if a sensor fault is present. The system’s low order allows for efficient implementation in real-time on a fixed-point microprocessor. Modification of the roll rate sensor signal during in vehicle experiments shows the algorithm’s ability to detect faults.
2017-03-28
Technical Paper
2017-01-1626
Tomas Poloni, Jianbo Lu
Abstract This paper proposes a method to make diagnostic/prognostic judgment about the health of a tire, in term of its wear, using existing on-board sensor signals. The approach focuses on using an estimate of the effective rolling radius (ERR) for individual tires as one of the main diagnostic/prognostic means and it determines if a tire has significant wear and how long it can be safely driven before tire rotation or tire replacement are required. The ERR is determined from the combination of wheel speed sensor (WSS), Global Positioning sensor (GPS), the other motion sensor signals, together with the radius kinematic model of a rolling tire. The ERR estimation fits the relevant signals to a linear model and utilizes the relationship revealed in the magic formula tire model. The ERR can then be related to multiple sources of uncertainties such as the tire inflation pressure, tire loading changes, and tire wear.
2017-03-28
Technical Paper
2017-01-1633
Eiji Kojima, Kazuhiko Kano, Hiroyuki Wado, Noriyuki Iwamori
Abstract In automotive applications, magnetic field sensors are widely used for detecting position and current. However, magnetic field sensors are required to be highly precise with good usability. To satisfy demand, we have developed a graphene Hall sensor that senses magnetic fields by the Hall effect. The sensitivity of a Hall sensor is proportional to the carrier mobility, and graphene has an extremely high carrier mobility compared with conventional materials like Si, GaAs and InSb. Thus, graphene Hall sensors are expected to give high sensitivity that will enable sensing of the Earth’s magnetic field. In addition, graphene has a low temperature dependence on carrier mobility due to its ballistic transport, so good usability in actual use is also anticipated. In this paper, we demonstrate a graphene Hall sensor made using conventional Si process technology.
2017-03-28
Technical Paper
2017-01-1636
Lukas Preusser
Abstract Along with the development and marketability of vehicles without an internal combustion engine, electrically heated surfaces within these vehicles are getting more and more important. They tend to have a quicker response while using less energy than a conventional electric heater fan, providing a comfortable temperature feel within the cabin. Due to the big area of heated surface it is important to spread the heating power in a way that different heat conduction effects to underlying materials are considered. In case an accurate sensor feedback of the targeted homogeneous surface temperature cannot be guaranteed, a thermal energy model of the heated system can help to set and maintain a comfortable surface temperature. For a heated steering wheel development project, different models have been created to meet that aim using mechanistic approaches starting with a predominantly first-order dynamics model and ending with a distributed parameter multi-feedback system.
2017-03-28
Technical Paper
2017-01-0445
Muthukumar Arunachalam, Arunkumar S, PraveenKumar Sampath, Abdul Haiyum, Yash Khakhar
Abstract In recent years, there is increasing demand for every CAE engineer on their confidence level of the virtual simulation results due to the upfront robust design requirement during early stage of an automotive product development. Apart from vehicle feel factor NVH characteristics, there are certain vibration target requirements at system or component level which need to be addressed during design stage itself in order to achieve the desired functioning during vehicle operating conditions. Vehicle passive safety system is one which primarily consists of acceleration sensors, control module and air-bag deployment system. Control module’s decision is based on accelerometer sensor signals so that its mounting locations should meet the sufficient inertance or dynamic stiffness performance in order to avoid distortion in signals due to its structural resonances.
2017-03-28
Technical Paper
2017-01-0050
Mario Berk, Hans-Martin Kroll, Olaf Schubert, Boris Buschardt, Daniel Straub
Abstract With increasing levels of driving automation, the perception provided by automotive environment sensors becomes highly safety relevant. A correct assessment of the sensors’ perception reliability is therefore crucial for ensuring the safety of the automated driving functionalities. There are currently no standardized procedures or guidelines for demonstrating the perception reliability of the sensors. Engineers therefore face the challenge of setting up test procedures and plan test drive efforts. Null Hypothesis Significance Testing has been employed previously to answer this question. In this contribution, we present an alternative method based on Bayesian parameter inference, which is easy to implement and whose interpretation is more intuitive for engineers without a profound statistical education. We show how to account for different environmental conditions with an influence on sensor performance and for statistical dependence among perception errors.
2017-03-28
Technical Paper
2017-01-0069
Venkatesh Raman, Mayur Narsude, Damodharan Padmanaban
Abstract This manuscript compares window-based data imputation approaches for data coming from connected vehicles during actual driving scenarios and obtained using on-board data acquisition devices. Three distinct window-based approaches were used for cleansing and imputing the missing values in different CAN-bus (Controller Area Network) signals. Lengths of windows used for data imputation for the three approaches were: 1) entire time-course for each vehicle ID, 2) day, and 3) trip (defined as duration between vehicle's ignition statuses ON to OFF). An algorithm for identification of ignition ON and OFF events is also presented, since this signal was not explicitly captured during the data acquisition phase. As a case study, these imputation techniques were applied to the data from a driver behavior classification experiment.
2017-03-28
Technical Paper
2017-01-0070
Longxiang Guo, Sagar Manglani, Xuehao Li, Yunyi Jia
Abstract Autonomous driving technologies can provide better safety, comfort and efficiency for future transportation systems. Most research in this area has mainly been focused on developing sensing and control approaches to achieve various autonomous driving functions. Very little of this research, however, has studied how to efficiently handle sensing exceptions. A simple exception measured by any of the sensors may lead to failures in autonomous driving functions. The autonomous vehicles are then supposed to be sent back to manufacturers for repair, which takes both time and money. This paper introduces an efficient approach to make human drivers able to online teach autonomous vehicles to drive under sensing exceptions. A human-vehicle teaching-and-learning framework for autonomous driving is proposed and the human teaching and vehicle learning processes for handling sensing exceptions in autonomous vehicles are designed in detail.
2017-03-28
Technical Paper
2017-01-0067
Wei Han, Xinyu Zhang, Jialun Yin, Yutong Li, Deyi Li
Abstract Safety of buses is crucial because of the large proportion of the public transportation sector they constitute. To improve bus safety levels, especially to avoid driver error, which is a key factor in traffic accidents, we designed and implemented an intelligent bus called iBus. A robust system architecture is crucial to iBus. Thus, in this paper, a novel self-driving system architecture with improved robustness, such as to failure of hardware (including sensors and controllers), is proposed. Unlike other self-driving vehicles that operate either in manual driving mode or in self-driving mode, iBus offers a dual-control mode. More specifically, an online hot standby mechanism is incorporated to enhance the reliability of the control system, and a software monitor is implemented to ensure that all software modules function appropriately. The results of real-world road tests conducted to validate the feasibility of the overall system confirm that iBus is reliable and robust.
2017-03-28
Technical Paper
2017-01-0028
Xin Li, Weiwen Deng
Abstract This paper proposes a Real-Time Estimation of Radar Cross Section for ADAS Simulation, aimed to enable math-based virtual development and test of ADAS. The electromagnetic scattering mechanism is firstly analyzed with targets to be typical objects in traffic. Then a geometric model is developed, in which the object surfaces are divided into multiple scattering zones corresponding to different scattering mechanism. According to different surface curvature radius and scattering mechanism, the scattering zones are approximately equivalent to plane, cylinder, sphere and so on. Using the ARD model based on an improved physical optics and diffraction theory, RCS value of a zone is estimated. Then the RCS of the object surface is obtained by vector superposition of all zones. Some typical simulation comparisons are carried out, which proves the practicability of our method.
2017-03-28
Technical Paper
2017-01-0027
Li Xu, Eric Tseng, Thomas Pilutti, Steven Schondorf
Abstract In the current Ford Pro-Trailer Backup Assist (TBA) system, trailer hitch angle is determined utilizing the reverse camera of the vehicle. In addition to being sensitive to environmental factors such as lighting conditions and occlusion, the vision-based approach is difficult to be applied to gooseneck or fifth wheel trailers. In this paper, a yaw rate based hitch angle observer is proposed as an alternative sensing solution for TBA. Based on the kinematic model of the vehicle-trailer, an instantaneous hitch angle is first derived by utilizing vehicle yaw rate, trailer yaw rate, vehicle velocity and vehicle/trailer parameters provided by the TBA system. Due to signal errors and parameter uncertainties, this instantaneous hitch angle may be noisy, especially at lower vehicle speed.
2017-03-28
Technical Paper
2017-01-0035
Binyu Mei, Xuexun Guo, Gangfeng Tan, Yongbing Xu, Mengying Yang
Abstract Vehicle speed is an important factor to driving safety, which is directly related to the stability and braking performance of the vehicle. Besides, the precise measurement of the vehicle speed is the basis of some vehicle active safety systems. Even in the future intelligent transportation, high quality speed information will also play an important role. The commonly used vehicle speed measurement techniques are based on the wheel speed sensors, which are not accurate, especially when the wheels’ slip rate is not equal to zero. Focusing on these issues, image matching technology has been used to measure the vehicle speed in this paper. The image information of the road in the front of the vehicle is collected, and the pixel displacement of the vehicle is calculated by the matching system, thus accurately vehicle speed can be obtained. Compared with conventional speed measure technology, it has the advantages of wide measuring range, and high accuracy.
2017-03-28
Technical Paper
2017-01-0038
Corwin Stout, Milos Milacic, Fazal Syed, Ming Kuang
Abstract In recent years we have witnessed increased discrepancy between fuel economy numbers reported in accordance with EPA testing procedures and real world fuel economy reported by drivers. The debates range from needs for new testing procedures to the fact that driver complaints create one-sided distribution; drivers that get better fuel economy do not complain about the fuel economy, but only the ones whose fuel economy falls short of expectations. In this paper, we demonstrate fuel economy improvements that can be obtained if the driver is properly sophisticated in the skill of driving. Implementation of SmartGauge with EcoGuide into the Ford C-MAX Hybrid in 2013 helped drivers improve their fuel economy on hybrid vehicles. Further development of this idea led to the EcoCoach that would be implemented into all future Ford vehicles.
2017-03-28
Technical Paper
2017-01-0030
Shunsuke Kogure, Takashi Kato, Shin Osuga
Abstract With the improved safety performance of vehicles, the number of accidents has been decreasing. However, accidents due to driver distraction still occur, which means that there is a high need to determine whether a driver is properly looking at the surroundings. Meanwhile, with the trend toward partial automatic driving of vehicles in recent years, it is also urgently required that the state of the driver be grasped. Even if automatic driving is not installed, it is desired that the state of the driver be grasped and an application for control be performed depending on the state of the driver. Under these circumstances, we have built an algorithm that determines of the direction a driver is looking, to make a basic determination of whether or not the driver is in a state suitable for safe driving of the vehicle.
2017-03-28
Technical Paper
2017-01-0043
Michael Smart, Satish Vaishnav, Steven Waslander
Abstract Robust lane marking detection remains a challenge, particularly in temperate climates where markings degrade rapidly due to winter conditions and snow removal efforts. In previous work, dynamic Bayesian networks with heuristic features were used with the feature distributions trained using semi-supervised expectation maximization, which greatly reduced sensitivity to initialization. This work has been extended in three important respects. First, the tracking formulation used in previous work has been corrected to prevent false positives in situations where only poor RANSAC hypotheses were generated. Second, the null hypothesis is reformulated to guarantee that detected hypotheses satisfy a minimum likelihood. Third, the computational requirements have been greatly reduced by computing an upper bound on the marginal likelihood of all part hypotheses upon generation and rejecting parts with an upper bound less likely than the null hypothesis.
2017-03-28
Technical Paper
2017-01-0046
Mohamed Aladem, Samir Rawashdeh, Nathir Rawashdeh
Abstract To reliably implement driver-assist features and ultimately self-driving cars, autonomous driving systems will likely rely on a variety of sensor types including GPS, RADAR, LASER range finders, and cameras. Cameras are an essential sensory component because they lend themselves to the task of identifying object types that a self-driving vehicle is likely to encounter such as pedestrians, cyclists, animals, other cars, or objects on the road. In this paper, we present a feature-based visual odometry algorithm based on a stereo-camera to perform localization relative to the surrounding environment for purposes of navigation and hazard avoidance. Using a stereo-camera enhances the accuracy with respect to monocular visual odometry. The algorithm relies on tracking a local map consisting of sparse 3D map points. By tracking this map across frames, the algorithm makes use of the full history of detected features which reduces the drift in the estimated motion trajectory.
2017-03-28
Technical Paper
2017-01-0040
Michael Hafner, Thomas Pilutti
Abstract We propose a steering controller for automated trailer backup, which can be used on tractor-trailer configurations including fifth wheel campers and gooseneck style trailers. The controller steers the trailer based on real-time driver issued trailer curvature commands. We give a stability proof for the hierarchical control system, and demonstrate robustness under a specific set of modeling errors. Simulation results are provided along with experimental data from a full-size pickup truck and 5th wheel trailer.
2017-03-28
Technical Paper
2017-01-1068
Jonathan Tigelaar, Krista Jaquet, David Cox, Albert Peter
Turbocharging is significantly changing design and control strategies for Diesel and gasoline engines. This paper will review new advances in the turbocharger speed measurement. Until recently, the highly accurate and fast turbocharger speed data, based on the physical speed sensor signal, has been mainly used to safely decrease conservative safety margins for turbocharger speed and surge limits. In addition to significantly increasing power and low end torque, new generation sensor technology is providing new opportunities to utilize turbocharger speed data.
2017-03-28
Technical Paper
2017-01-0044
Roman Schmied, Gunda Obereigner, Harald Waschl
Abstract In the field of advanced driver assistance systems (ADAS) the capability to accurately estimate and predict the driving behavior of surrounding traffic participants has shown to enable significant improvements of the respective ADAS in terms of economy and comfort. The interaction between the different participants can be an important aspect. One example for this interaction is the car following behavior in dense urban traffic situations. There are different phenomenological or psychological models of human car following which also consider variations between different participants. Unfortunately, these models can seldom be applied for control directly or prediction in vehicle applications. A different way is to follow a control oriented approach by modeling the human as a time delay controller which tracks the inter-vehicle distance. The parameters are typically chosen based on empirical rules and do not consider variations between drivers.
2017-03-28
Technical Paper
2017-01-1637
David Cheng
Abstract This is a new design for sensor extreme long travel range detection technology especially for clutch master cylinder piston position detection and fork position detection in transmission application to replace PLCD (Permanent magnetic Linear Contactless Displacement) platform with simple manufacturing process and high accuracy. The main innovation point includes integrating a ferromagnetic concentrator into sensor module to enhance magnetic flux density at remote area of travel range and applying 3D Hall array with microcontroller for signal post process to guarantee the accuracy of sensor. SPI mode is used for communication between 3D Hall array and microcontroller while a new signal post process method with self-learning calibration is applied in microcontroller algorithm.
2017-03-28
Technical Paper
2017-01-1625
Rajeev Kalamdani, Chandra Jalluri, Stephen Hermiller, Robert Clifton
Abstract Use of sensors to monitor dynamic performance of machine tools at Ford’s powertrain machining plants has proven to be effective. The traditional approach to convert sensor data to actionable intelligence consists of identifying single features from cycle based signatures and setting thresholds above acceptable performance limits based on trials. The thresholds are used to discriminate between acceptable and unacceptable performance during each cycle and raise alarms if necessary. This approach requires a significant amount of resource & time intensive set up work up-front and considerable trial and error adjustments. The current state does not leverage patterns that might be discernible using multiple features simultaneously. This paper describes enhanced methods for processing the data using supervised and unsupervised machine learning methods. The objective of using these methods is to improve the prediction accuracy and reduce up-front set up.
2017-03-28
Technical Paper
2017-01-0036
Michael Hafner, John Bales
Abstract We introduce a controller designed to stop a vehicle smoothly and accurately at a specified distance target, while being robust to unmeasured disturbances. This controller has a wide range of applications in instances where low speed longitudinal control of a vehicle is desired. Controller design was validated in a simulation using an ideal vehicle model based on first principles. Real world testing and tuning was performed on a full-size pickup truck to demonstrate controller performance.
2017-03-28
Technical Paper
2017-01-1065
Douglas R. Martin, Benjamin Rocci
Abstract Exhaust temperature models are widely used in the automotive industry to estimate catalyst and exhaust gas temperatures and to protect the catalyst and other vehicle hardware against over-temperature conditions. Modeled exhaust temperatures rely on air, fuel, and spark measurements to make their estimate. Errors in any of these measurements can have a large impact on the accuracy of the model. Furthermore, air-fuel imbalances, air leaks, engine coolant temperature (ECT) or air charge temperature (ACT) inaccuracies, or any unforeseen source of heat entering the exhaust may have a large impact on the accuracy of the modeled estimate. Modern universal exhaust gas oxygen (UEGO) sensors have heaters with controllers to precisely regulate the oxygen sensing element temperature. These controllers are duty cycle based and supply more or less current to the heating element depending on the temperature of the surrounding exhaust gas.
2017-03-28
Technical Paper
2017-01-1638
Felix Gow, Lifeng Guan, Jooil Park
Abstract Tire Pressure Monitoring System (TPMS) sensor measures air pressure and temperature in the tire and transmits tire information as wireless messages to TPMS central unit which consists of Radio Frequency (RF) receiver. TPMS central unit needs to determine the exact sensor locations (e.g. Front Left, Front Right, Rear Left or Rear Right) in order to correctly identify the location of the tire with pressure out of the desired range. The identified tire with abnormal pressure is highlighted on dash board in the car. Thus, determination of the location of a particular tire made automatically by the TPMS system itself or tire localization is required. TPMS tire localization is implemented currently in several methods. A new method is proposed in this paper. The proposed method uses at least two RF transceivers as repeaters. Each transceiver receives wireless messages (eg.
2017-03-28
Technical Paper
2017-01-1640
Peng Liu, Liyun Fan, Wenbo Peng, Xiuzhen Ma, Enzhe Song
Abstract A novel high-speed electromagnetic actuator for electronic fuel injection system (EFIS) of diesel engine is proposed in this paper. By using a permanent magnet and an annular flange, the design of the novel actuator aims to overcome the inherent drawbacks of the conventional solenoid electromagnetic actuator, such as high power consumption and so on. A method of multi-objective optimization combined with response surface methodology and Genetic Algorithm (GA) is employed to obtain the optimal design of the novel actuator. First, combined with design of experiments and finite element analysis, the second order polynomial response surface models (SOPRSM) of electromagnetic forces are produced by the least square principle. Second, the complete multi-objective optimization mathematical model (MOMM) of the novel actuator based on SOPRSM is built, aiming to maximize the net electromagnetic force on the armature and minimize the drive current.
Viewing 1 to 30 of 3149