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Viewing 1 to 30 of 3163
2017-10-08
Technical Paper
2017-01-2283
Anand Prabu Kalaivanan, Gnanasekaran Sakthivel
Electronic Fuel Injection Systems have revolutionised Fuel Delivery and Ignition timing in the past two decades and have reduced the Fuel Consumption and Exhaust Emissions, ultimately enhancing the Economy and Ecological awareness of the engines. But the ignition/injection timing that commands the combustion is mapped to a fixed predefined table which is best suited during the stock test conditions. However continuous real time adjustments by monitoring the combustion characteristics prove to be highly efficient and be immune to varying fuel quality, lack of transient performance and wear related compression losses. Addressing Fuel Quality Issues: For developing countries, Automobile Manufacturers have been Tuning the Ignition/Injection timing Map assuming the worst possible fuel quality. Conventional knock control system focus on engine protection only and doesn't contribute much in improving thermal efficiency.
2017-09-23
Technical Paper
2017-01-1954
Peng Hang, Xinbo Chen, Fengmei Luo
Abstract Path tracking is the rudimentary capability and primary task for autonomous ground vehicles (AGVs). In this paper, a novel four-wheel-independent-steering (4WIS) and four-wheel-independent-drive (4WID) electric vehicle (EV) is proposed which is equipped with steer-by-wire (SBW) system. For path-tracking controller design, the nonlinear vehicle model with 2 degrees of freedom (DOF) is built utilizing the nonlinear Dugoff tire model. The nonlinear dynamic model of SBW system is conducted as well considering the external disturbances. As to the path-tracking controller design, an integrated four-wheel steering (4WS) and direct yaw-moment control (DYC) system is designed based on the model predictive control (MPC) algorithm to track the target path described by desired yaw angle and lateral displacement. Then, the fast terminal sliding mode controller (FTSMC) is proposed for the SBW system to suppress disturbances.
2017-09-23
Technical Paper
2017-01-1971
Sihan Chen, Libo Huang, Xin Bi, Jie Bai
Abstract For sensing system, the trustworthiness of the variant sensors is the crucial point when dealing with advanced driving assistant system application. In this paper, an approach to a hybrid camera-radar application of vehicle tracking is presented, able to meet the requirement of such demand. Most of the time, different types of commercial sensors available nowadays specialize in different situations, such as the ability of offering a wealth of detailed information about the scene for the camera or the powerful resistance to the severe weather for the millimeter-wave (MMW) radar. The detection and tracking in different sensors are usually independent. Thus, the work here that combines the variant information provided by different sensors is indispensable and worthwhile. For the real-time requirement of merging the measurement of automotive MMW radar in high speed, this paper first proposes a fast vehicle tracking algorithm based on image perceptual hash encoding.
2017-09-23
Technical Paper
2017-01-1989
Yi Chen, Gaoxiang Lin, Ying He
Abstract Chinese National projects “13th Five Year Plan” and “Made in China 2025” have both put forward a goal of developing Intelligent and Connected Vehicles(ICV). Shanghai is a typical city of automobile industry which spearhead the development of China’s ICV industry. After the adjustment and transition of industrial structure, Shanghai has initially formed the industrialization layout of ICV covering core areas including environmental perception, intelligent decision-making, actuator, human-computer interaction and vehicle integration. However, currently Shanghai is still in the beginning stage and there exists a large gap with world advanced level in both the core technology and marketization. This article is based on former qualitative survey combined with quantitative analysis which uses the Analytic Hierarchy Process(AHP) method to objectively evaluate the status quo and development trend of Shanghai’s ICV.
2017-09-23
Technical Paper
2017-01-1953
Manfei Bai, Lu Xiong, Zhiqiang Fu, Renxie Zhang
Abstract In this paper, a speed tracking controller is designed for the All-terrain vehicles. The method of feedforward with state variable feedback based on conditional integrators is adopted by the proposed control algorithm. The feedforward is designed considering the influence of the road slope on the longitudinal dynamics, which makes the All-terrain vehicles satisfy the acceleration demand of the upper controller when it tracks the desired speed on the road with slope varying greatly. The road slope is estimated based on a combined kinematic and dynamic model. This method solves the problem that road slope estimation requires an accurate vehicle dynamic model and are susceptible to acceleration sensor bias. Based on the vehicle dynamic model and the nonlinear tire model, the method of conditional integration is used in the state variable feedback, which considers the saturation constraint of the actuator with the intention of preventing the divergent integral operation.
2017-09-19
Technical Paper
2017-01-2109
Kiran Thupakula
Abstract Airport environments consist of several moving objects both in the air and on the ground. In air moving objects include aircraft, UAVs and birds etc. On ground moving objects include aircraft, ground vehicles and ground personnel etc. Detecting, classifying, identifying and tracking these objects are necessary for avoiding collisions in all environmental situations. Multiple sensors need to be employed for capturing the object shape and position from multiple directions. Data from these sensors are combined and processed for object identification. In current scenario, there is no comprehensive traffic monitoring system that uses multisensor data for monitoring in all the airport areas. In this paper, for explanation purposes, a hypothetical airport traffic monitoring system is presumed that uses multiple sensors for avoiding collisions.
2017-09-19
Technical Paper
2017-01-2030
Benjamin Cheong, Paolo Giangrande, Patrick Wheeler, Pericle Zanchetta, Michael Galea
In effort to reduce environmental impact of the aerospace industry, More Electric Aircraft (MEA) concepts with electrical systems for fuel pumping, wing ice protection, environmental control systems and aircraft actuation are becoming more and more widely researched. The replacement of hydraulic actuators by motor drives for flight control surfaces is particularly attractive for maintainability, reduction in operating costs and to eliminate the hydraulic fluid. High power density of aerospace motor drives is a key factor in the successful realization of these concepts. An integrated system design approach offer optimization opportunities for further improvements in power density however the challenge lies in its multi-disciplinary modelling and the handling of numerous optimization variables or constraints that are discrete and non-linear in nature. A 4-level modelling paradigm has been proposed by multiple authors to represent a motor drive.
2017-09-19
Technical Paper
2017-01-2063
Patrick Browning, Bryan Shambaugh, Joseph Dygert
The dielectric barrier discharge (DBD) has been studied significantly in the past 2 decades for its applications to various aerodynamic problems. The most common aerodynamic applications have been stall/separation control and boundary layer modification. Recently several researchers have proposed utilizing the DBD in various configurations to act as viable propulsion systems for micro and nano aerial vehicles. The DBD produces stable atmospheric-pressure non-thermal plasma in a thin sheet with a preferred direction of flow. The plasma flow, driven by electrohydrodynamic body forces, entrains the quiescent air around it and thus develops into a low speed jet on the order of 10-1 to 101 m/s. Several researchers have utilized DBDs in an annular geometric setup as a propulsion device. Other researchers have used them to alter rectangular duct flows and directional jet devices. This study investigates 2-D duct flows for applications in micro plasma thrusters.
2017-09-04
Technical Paper
2017-24-0003
Andreas Sidorow, Vincent Berger, Ghita Elouazzani
Abstract Gasoline engines have typically a waste gate actuator to control the boost pressure. The electrification of the vehicle and combustion engine components leads to new challenges of application of electric actuators in engine components, like turbochargers, which are faced with relatively high ambient temperatures. Another challenge is a simulation and prediction of the mechanical load on the actuator and kinematic components at different application scenarios, which can help to find the optimal solution which fulfills the durability, controllability, etc. targets. This paper deals with a physical dynamic model of an electric waste-gate actuator and kinematic components. The modeling includes a thermal, electrical and mechanical parts of the turbocharger control system and is validated on test-bench and engine measurements including pulsation effects.
2017-09-04
Technical Paper
2017-24-0050
Anjan Rao Puttige, Robin Hamberg, Paul Linschoten, Goutham Reddy, Andreas Cronhjort, Ola Stenlaas
Abstract Improving turbocharger performance to increase engine efficiency has the potential to help meet current and upcoming exhaust legislation. One limiting factor is compressor surge, an air flow instability phenomenon capable of causing severe vibration and noise. To avoid surge, the turbocharger is operated with a safety margin (surge margin) which, as well as avoiding surge in steady state operation, unfortunately also lowers engine performance. This paper investigates the possibility of detecting compressor surge with a conventional engine knock sensor. It further recommends a surge detection algorithm based on their signals during transient engine operation. Three knock sensors were mounted on the turbocharger and placed along the axes of three dimensions of movement. The engine was operated in load steps starting from steady state. The steady state points of operation covered the vital parts of the engine speed and load range.
2017-09-04
Technical Paper
2017-24-0130
Antonio Paolo Carlucci, Marco Benegiamo, Sergio Camporeale, Daniela Ingrosso
Abstract 1 Nowadays, In-Cylinder Pressure Sensors (ICPS) have become a mainstream technology that promises to change the way the engine control is performed. Among all the possible applications, the prediction of raw (engine-out) NOX emissions would allow to eliminate the NOX sensor currently used to manage the after-treatment systems. In the current study, a semi-physical model already existing in literature for the prediction of engine-out nitric oxide emissions based on in-cylinder pressure measurement has been improved; in particular, the main focus has been to improve nitric oxide prediction accuracy when injection timing is varied. The main modification introduced in the model lies in taking into account the turbulence induced by fuel spray and enhanced by in-cylinder bulk motion.
2017-09-04
Technical Paper
2017-24-0137
Zhen Zhang, Luigi del Re, Richard Fuerhapter
Abstract During transients, engines tend to produce substantially higher peak emissions like soot - the main fraction of particular matter (PM) - which are the longer the more important as the steady state emissions are better controlled. While Diesel particulate filters are normally able to block them, preventing their occurrence would of course be more important. In order to achieve this goal, however, they must be measurable. While for most emissions commercial sensors of sufficient speed and performance are available, the same is not true for PMs, especially for production engines. Against this background, in the last years the possible use of a full stream 50Hz sensor based on Laser Induced Incandescence (LII) was investigated, and the results were very encouraging, showing that the sensor could recognize transient changes undetected by conventional measurement systems (like the AVL Opacimeter) but confirmed by the analysis of combustion.
2017-09-04
Technical Paper
2017-24-0153
Sergey Shcherbanev, Alexandre De Martino, Andrey Khomenko, Svetlana Starikovskaia, Srinivas Padala, Yuji Ikeda
Abstract Requirements for reducing consumption of hydrocarbon fuels, as well as reducing emissions force the scientific community to develop new ignition systems. One of possible solutions is an extension of the lean ignition limit of stable combustion. With the decrease of the stoichiometry of combustible mixture the minimal size of the ignition kernel (necessary for development of combustion) increases. Therefore, it is necessary to use some special techniques to extend the ignition kernel region. Pulsed microwave discharge allows the formation of the ignition kernels of larger diameters. Although the microwave discharge igniter (MDI) was already tested for initiation of combustion and demonstrated quite promising results, the parameters of plasma was not yet studied before. Present work demonstrates the results of the dynamics of spatial structure of the MDI plasma with nanosecond time resolution.
2017-09-04
Journal Article
2017-24-0045
Blane Scott, Christopher Willman, Ben Williams, Paul Ewart, Richard Stone, David Richardson
Abstract In-cylinder temperature measurements are vital for the validation of gasoline engine modelling and useful in their own right for explaining differences in engine performance. The underlying chemical reactions in combustion are highly sensitive to temperature and affect emissions of both NOx and particulate matter. The two techniques described here are complementary, and can be used for insights into the quality of mixture preparation by measurement of the in-cylinder temperature distribution during the compression stroke. The influence of fuel composition on in-cylinder mixture temperatures can also be resolved. Laser Induced Grating Spectroscopy (LIGS) provides point temperature measurements with a pressure dependent precision in the range 0.1 to 1.0 % when the gas composition is well characterized and homogeneous; as the pressure increases the precision improves.
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
2017-01-1728
Nitin Singh, Aayoush Sharma, Sameer Shah, Balakumar Gardampaali
Abstract In any unlikely event of accidents or vehicle breakdown, there is accumulation of traffic which results in road-blockage and causes in convenience to other vehicles. If this happens in remote areas, the accidents victims are left unattended and there is delay in providing emergency services. In case of traffic, it obstructs the entry of ambulance and rescue team which results in death of passengers. To prevent this mishap, a mechatronics based road block avoidance and accident alarming system is designed which is automated by the use of sensors. The road-block is detected with the help sensors located at regular intervals on road. This input is given to a Local Control Unit (LCU) which is integrated on every road. Several such LCUs are connected to a Main Control Unit (MCU) which is located at the nearest police station. A single MCU covers the area administered by that police station. Additional CCTV cameras are present to give graphical view of accident.
2017-03-28
Technical Paper
2017-01-1727
Yumin Lin, Bo-Chiuan Chen, Hsien-Chi Tsai, Bi-Cheng Luan
Abstract A model-based sensor fault detection algorithm is proposed in this paper to detect and isolate the faulty sensor. Wheel speeds are validated using the wheel speed deviations before being employed to check the sensor measurements of the vehicle dynamics. Kinematic models are employed to estimate yaw rate, lateral acceleration, and steering wheel angle. A Kalman filter based on a point mass model is employed to estimate longitudinal speed and acceleration. The estimated vehicle dynamics and sensor measurements are used to calculate the residuals. Adaptive threshold values are employed to identify the abnormal increments of residuals. Recursive least square method is used to design the coefficients of the expressions for adaptive threshold values, such that the false alarms caused by model uncertainties can be prevented. Different combinations of estimations are employed to obtain 18 residuals.
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
2017-01-0067
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
2017-01-0070
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
2017-01-0069
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
2017-01-0117
Raja Sekhar Dheekonda, Sampad Panda, Md Nazmuzzaman khan, Mohammad Hasan, Sohel Anwar
Accuracy in detecting a moving object is critical to autonomous driving or advanced driver assistance systems (ADAS). By including the object classification from multiple sensor detections, the model of the object or environment can be identified more accurately. The critical parameters involved in improving the accuracy are the size and the speed of the moving object. All sensor data are to be used in defining a composite object representation so that it could be used for the class information in the core object’s description. This composite data can then be used by a deep learning network for complete perception fusion in order to solve the detection and tracking of moving objects problem. Camera image data from subsequent frames along the time axis in conjunction with the speed and size of the object will further contribute in developing better recognition algorithms.
2017-03-28
Technical Paper
2017-01-0102
Mahdi Heydari, Feng Dang, Ankit Goila, Yang Wang, Hanlong Yang
In this paper, a sensor fusion approach is introduced to estimate lane departure. The proposed algorithm combines the camera, inertial navigation sensor, and GPS data with the vehicle dynamics to estimate the vehicle path and the lane departure time. The lane path and vehicle path are estimated by using Kalman filters. This algorithm can be used to provide early warning for lane departure in order to increase driving safety. By integrating inertial navigation sensor and GPS data, the inertial sensor biases can be estimated and the vehicle path can be estimated where the GPS data is not available or is poor. Additionally, the algorithm can be used to reduce the latency of information embedded in the controls, so that the vehicle lateral control performance can be significantly improved during lane keeping in Advanced Driver Assistance Systems (ADAS) or autonomous vehicles. Furthermore, it improves lane detection reliability in situations when camera fails to detect lanes.
2017-03-28
Technical Paper
2017-01-0108
Zaydounr Y. Rawashdeh, Trong-Duy Nguyen, Anoop Pottammal, Rajesh Malhan
Abstract In this work, Dedicated Short Range Communication (DSRC) capabilities combined with classical autonomous vehicles’ on-board sensors (Camera) are used to trigger a Comfortable Emergency Brake (CEB) for urban traffic light intersection scenario. The system is designed to achieve CEB in two phases, the Automated Comfortable Brake (ACB) and the full stop Automated Emergency Brake (AEB). The ACB is triggered first based on the content of the Signal Phase and Timing (SPaT) / Map data (MAP) messages received from the Road Side Unit (RSU) at larger distances. And, once the traffic light becomes in the detection field of view of the camera, the output of the Camera-based Traffic Light Detection (TLD) and recognition software is fused with the SPaT/MAP content to decide on triggering the full stop AEB. In the automated vehicle, the current traffic light color and duration received in the SPaT message is parsed; and compared with the TLD output for color matching.
2017-03-28
Technical Paper
2017-01-0071
Vahid Taimouri, Michel Cordonnier, Kyoung Min Lee, Bryan Goodman
Abstract While operating a vehicle in either autonomous or occupant piloted mode, an array of sensors can be used to guide the vehicle including stereo cameras. The state-of-the-art distance map estimation algorithms, e.g. stereo matching, usually detect corresponding features in stereo images, and estimate disparities to compute the distance map in a scene. However, depending on the image size, content and quality, the feature extraction process can become inaccurate, unstable and slow. In contrast, we employ deep convolutional neural networks, and propose two architectures to estimate distance maps from stereo images. The first architecture is a simple and generic network that identifies which features to extract, and how to combine them in a multi-resolution framework.
2017-03-28
Technical Paper
2017-01-0072
Yang Zheng, Navid Shokouhi, Amardeep Sathyanarayana, John Hansen
Abstract With the embedded sensors – typically Inertial Measurement Units (IMU) and GPS, the smartphone could be leveraged as a low-cost sensing platform for estimating vehicle dynamics. However, the orientation and relative movement of the smartphone inside the vehicle yields the main challenge for platform deployment. This study proposes a solution of converting the smartphone-referenced IMU readings into vehicle-referenced accelerations, which allows free-positioned smartphone for the in-vehicle dynamics sensing. The approach is consisted of (i) geometry coordinate transformation techniques, (ii) neural networks regression of IMU from GPS, and (iii) adaptive filtering processes. Experiment is conducted in three driving environments which cover high occurrence of vehicle dynamic movements in lateral, longitudinal, and vertical directions. The processing effectiveness at five typical positions (three fixed and two flexible) are examined.
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
2017-01-1654
Arun Ganesan, Jayanthi Rao, Kang Shin
Abstract Modern vehicles house many advanced components; sensors and Electronic Control Units (ECUs) — now numbering in the 100s. These components provide various advanced safety, comfort and infotainment features, but they also introduce additional attack vectors for malicious entities. Attackers can compromise one or more of these sensors and flood the vehicle’s internal network with fake sensor values. Falsified sensor values can confuse the driver, and even cause the vehicle to misbehave. Redundancy can be used to address compromised sensors, but adding redundant sensors will increase the cost per vehicle and is therefore less attractive. To balance the need for security and cost-efficiency, we exploit the natural redundancy found in vehicles. Natural redundancy occurs when the same physical phenomenon causes symptoms in multiple sensors. For instance, pressing the accelerator pedal will cause the engine to pump faster and increase the speed of the vehicle.
2017-03-28
Technical Paper
2017-01-1653
Jon Barton Shields, Jörg Huser, David Gell
Abstract This paper discusses the merits, benefits and usage of autonomous key management (with implicit authentication) (AKM) solutions for securing ECU-to-ECU communication within the connected vehicle and IoT applications; particularly for transmissions between externally exposed, edge ECU sensors connected to ECUs within the connected vehicle infrastructure. Specific benefits addressed include reductions of communication latency, implementation complexity, processing power and energy consumption. Implementation issues discussed include provisioning, key rotation, synchronization, re-synchronization, digital signatures and enabling high entropy.
Viewing 1 to 30 of 3163