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Abstract Exhaust manifolds are one of the most important components on the engine assembly, which is mounted on engine cylinder head. Exhaust manifolds connect exhaust ports of cylinders to the turbine for turbocharged diesel engine therefore they play a significant role in the performance of engine system. Exhaust manifolds are subjected to very harsh thermal loads; extreme heating under very high temperatures and cooling under low temperatures. Therefore designing a durable exhaust manifold is a challenging task. Computer aided engineering (CAE) is an effective tool to drive an exhaust manifold design at the early stage of engine development. Thus advanced CAE methodologies are required for the accurate prediction of temperature distribution. However, at the end of the development process, for the design verification purposes, various tests have to be carried out in engine dynamometer cells under severe operating conditions.

Abstract A kinematic modeling framework was established to predict status (position, displacement, velocity, acceleration, and shape) of a towing vehicle system with different driver inputs. This framework consists of three components: (1) a state space model to decide position and velocity for the vehicle system based on Newton’s second law; (2) an angular acceleration transferring model, which leads to a hypothesis that the each towed unit follows the same path as the towing vehicle; and (3) a polygon model to draw instantaneous polygons to envelop the entire system at any time point.

Abstract Real-time reconstruction of 3D environment attributed with semantic information is significant for a variety of applications, such as obstacle detection, traffic scene comprehension and autonomous navigation. The current approaches to achieve it are mainly using stereo vision, Structure from Motion (SfM) or mobile LiDAR sensors. Each of these approaches has its own limitation, stereo vision has high computational cost, SfM needs accurate calibration between a sequences of images, and the onboard LiDAR sensor can only provide sparse points without color information. This paper describes a novel method for traffic scene semantic segmentation by combining sparse LiDAR point cloud (e.g. from Velodyne scans), with monocular color image. The key novelty of the method is the semantic coupling of stereoscopic point cloud with color lattice from camera image labelled through a Convolutional Neural Network (CNN).

Abstract The innovations of vehicle connectivity have been increasing dramatically to enhance the safety and user experience of driving, while the rising numbers of interfaces to the external world also bring security threats to vehicles. Many security countermeasures have been proposed and discussed to protect the systems and services against attacks. To provide an overview of the current states in this research field, we conducted a systematic mapping study (SMS) on the topic area “security countermeasures of in-vehicle communication systems.” A total of 279 papers are identified based on the defined study identification strategy and criteria. We discussed four research questions (RQs) related to the security countermeasures, validation methods, publication patterns, and research trends and gaps based on the extracted and classified data. Finally, we evaluated the validity threats and the whole mapping process.

Abstract This work introduces the concept of a dual-layer specification structure for standards that separate interoperability functions, such as backward compatibility, localization, and deployment, from those essential to reliability, security, and functionality. The latter group of features, which constitute the actual standard, make up the baseline layer for instructions, while all the elements required for interoperability are specified in a second layer, known as a Protocols, Operations, Usage, and Formats (POUF) document. We applied this technique in the development of a standard for Uptane [1], a security framework for over-the-air (OTA) software updates used in many automobiles. This standard is a good candidate for a dual-layer specification because it requires communication between entities, but does not require a specific format for this communication.

Abstract Modern vehicles integrate Internet of Things (IoT) components to bring value-added services to both drivers and passengers. These components communicate with the external world through different types of interfaces including the on-board diagnostics (OBD-II) port, a mandatory interface in all vehicles in the United States and Europe. While this transformation has driven significant advancements in efficiency and safety, it has also opened a door to a wide variety of cyberattacks, as the architectures of vehicles were never designed with external connectivity in mind, and accordingly, security has never been pivotal in the design. As standardized, the OBD-II port allows not only direct access to the internal network of the vehicle but also installing software on the Electronic Control Units (ECUs).

Abstract In the automotive domain, the overall complexity of technical components has increased enormously. Formerly isolated, purely mechanical cars are now a multitude of cyber-physical systems that are continuously interacting with other IT systems, for example, with the smartphone of their driver or the backend servers of the car manufacturer. This has huge security implications as demonstrated by several recent research papers that document attacks endangering the safety of the car. However, there is, to the best of our knowledge, no holistic overview or structured description of the complex automotive domain. Without such a big picture, distinct security research remains isolated and is lacking interconnections between the different subsystems. Hence, it is difficult to draw conclusions about the overall security of a car or to identify aspects that have not been sufficiently covered by security analyses.

Abstract More than a decade ago, we proposed combined use of direct injection (DI) and jet ignition (JI) to produce high efficiency, high power-density, positive-ignition (PI), lean burn stratified, internal combustion engines (ICEs). Adopting this concept, the latest FIA F1 engines, which are electrically assisted, turbocharged, directly injected, jet ignited, gasoline engines and work lean stratified in a highly boosted environment, have delivered peak power fuel conversion efficiencies well above 46%, with specific power densities more than 340 kW/liter. The concept, further evolved, is here presented for unmanned aerial vehicle (UAV) applications. Results of simulations for a new DI JI ICE with rotary valve, being super-turbocharged and having gasoline or methanol as working fuel, show the opportunity to achieve even larger power densities, up to 430 kW/liter, while delivering a near-constant torque and, consequently, a nearly linear power curve over a wide range of speeds.

Abstract Joining titanium (Ti) alloys with conventional processes is difficult due to their complex structural properties and ability of phase transformation. Concerning all the difficulties, diffusion bonding is considered as an appropriate process for joining Ti alloys. Ti6Al4V, which is an α+β alloy widely used for aero engine component manufacturing, is diffusion bonded in this investigation. The diffusion bonding process parameters such as bonding temperature, bonding pressure, and holding time were optimized to achieve desired bonding characteristics such as shear strength, bonding strength, bonding ratio, and thickness ratio using response surface methodology (RSM). Empirical relationships were developed for the prediction of the bond characteristics, and sensitivity analysis was performed to determine the increment and decrement tendency of the shear strength with respect to the bonding parameters.

Abstract The main focus of this article is the online estimation of the terminal airspace sector capacity from the Air Traffic Controller 0ATC) dynamical neural model using Neural Partial Differentiation (NPD) with permissible safe separation and affordable workload. For this purpose, a primarily neural model of a multi-input-single-output (MISO) ATC dynamical system is established, and the NPD method is used to estimate the model parameters from the experimental data. These estimated parameters have a less relative standard deviation, and hence the model validation results show that the predicted neural model response is well matched with the intervention of the ATC workload. Moreover, the proposed neural network-based approach works well with the experimental data online as it does not require the initial values of model parameters, which are unknown in practice.

Abstract Although ground grading is one of the most common tasks that hydraulic excavators perform in typical work sites, proper grading is not easy for less-skilled operators as it requires coordinated manipulation of multiple hydraulic cylinders. In order to help alleviate this difficulty, automated grading systems are considered as an effective alternative to manual operations of hydraulic excavators. In this article, a sliding mode controller design is presented for automated grading control of a hydraulic excavator. First, an excavator manipulator model is developed in Simulink by using SimMechanics and SimHydraulics toolboxes. Then, a sliding mode controller is designed to control the manipulator to trace a predefined trajectory for a grading task. For a comparison study, a PI controller is used to control the manipulator to perform a grading task following the same desired trajectory and the performance is compared with those obtained by the sliding mode controller.

Abstract Vehicle cabin air quality depends on various parameters such as number of passengers, fan speed, and vehicle speed. In addition to controlling the temperature inside the vehicle, HVAC control system has evolved to improve cabin air quality as well. However, there is no standard test method to ensure reliable and repeatable comparison among different cars. The current study defined Cabin Air Quality Index (CAQI) and proposed a test method to determine CAQI. CAQIparticles showed dependence on the choice of metrics among particle number (PN), particle surface area (PS), and particle mass (PM). CAQIparticles is less than 1 while CAQICO2 is larger than 1. The proposed test method is promising but needs further improvement for smaller coefficient of variations (COVs).

Abstract This study investigates methods to precisely control a coolant pump in an internal combustion engine. The goal of this research is to minimize power consumption while still meeting optimal performance, reliability and durability requirements for an engine at all engine-operating conditions. This investigation achieves reduced fuel consumption, reduced emissions, and improved powertrain performance. Secondary impacts include cleaner air for the earth, reduced operating costs for the owner, and compliance with US regulatory requirements. The study utilizes mathematical modeling of the cooling system using heat transfer, pump laws, and boiling analysis to set limits to the cooling system and predict performance changes.

Abstract The preliminary gas turbine combustor design process uses a huge amount of empirical correlations to achieve more optimized designs. Combustion efficiency, in relation to the basic dimensions of the combustor, is one of the most critical performance parameters. In this study, semi-empirical correlations for combustion efficiencies are examined and correlation coefficients have been revised using an experimental air-blasted tubular combustor that uses JP8 kerosene aviation fuel. Besides, droplet diameter and effective evaporation constant parameters have been investigated for different operating conditions. In the study, it is observed that increased air velocity significantly improves the atomization process and decreases droplet diameters, while increasing the mass flow rate has a positive effect on the atomization—the relative air velocity in the air-blast atomizer increases and the fuel droplets become finer.

Abstract There are already a number of cybersecurity activities introduced in the development process in the automotive industry. For example, security testing of automotive components is often performed at the late stages of development. Fuzz testing is often performed as part of the security testing activity. However, since testing occurs late in the development process, it is expensive and, in some cases, may be too late to fix certain identified issues. Another challenge is that some testing requires hardware that is costly and may not be available until late in the development. We suggest fuzz testing virtual ECUs, which overcomes these challenges and allows for more efficient and effective security testing.

Abstract Management of expressway networks has been mainly focused on defect management without looking at the correlations with accidental risks. This causes unsustainability in expressway infrastructure maintenance since such defects may not be a contributing factor toward public safety. Thus it is necessary to incorporate accidental events for decision-making in infrastructure management. This study has developed a novel approach to machine learning (ML) that incorporates actual primary data from the last 10 years of single-vehicle accidents (SVA) by collisions with motorway facilities, or so-called single-vehicle collisions with fixed objects. The ML is firstly aimed at identifying the influential factors of SVA in relation to finding effective countermeasures for accidents by integrating the correlation analysis, multiple regression analysis, and ML techniques. The study reveals that wet pavement conditions have a significant effect on SVA.

Abstract Due to the increasing requirements for efficiency, the wide range of characteristics and the improved possibilities of modern development and production processes, compressors in turbochargers have become more individualized in order to adapt to the requirements of internal combustion engines. An understanding of the working mechanisms as well as an understanding of the way that losses occur in the flow allows a reduced development effort during the optimization process. This article presents three-dimensional (3D) Computational Fluid Dynamics (CFD) investigations of the loss mechanisms and quantitative calculations of individual losses. The 3D-CFD method used in this article will reduce the drawbacks of one-dimensional calculation as far as possible. For example, the twist of the blades is taken into account and the “discrete” method is used for loss calculation instead of the “average” method.

Abstract Automotive cybersecurity is steadily becoming a key factor in the worldwide adoption of connected and self-driving vehicles. Following the trend set by legislation mandating standardized vehicle safety, international standards and legislation are being put into place to mandate vehicle security. Due to cultural and legal system differences, the priorities of different countries’ legislation often differ. This article seeks to explore the different approaches taken by countries in some of the major automotive markets, with a special emphasis on that of the Japanese automotive security landscape.

Abstract TOC

Abstract Connected vehicle technology consisting of Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication falls under the umbrella of V2X, or Vehicle-to-Everything, communication. This enables vehicles and infrastructure to exchange safety-related information to enable smarter, safer roads. If driver alerts are raised or automated action is taken as a result of these messages, it is critical that messages are trustworthy and reliable. To this end, the Security Credential Management System (SCMS) and Cooperative Intelligent Transportation Systems (C-ITS) Credential Management System (CCMS) have been proposed to enable authentication and authorization of V2X messages without compromising individual user privacy. This is accomplished by issuing each vehicle a large set of “pseudonyms,” unrelated to any real-world identity. During operation, the vehicle periodically switches pseudonyms, thereby changing its identity to others in the network.