Search Results

Abstract Tire-pavement interaction noise (TPIN) dominates for passenger cars above 40 km/h and trucks above 70 km/h. Numerous studies have attempted to uncover and distinguish the basic mechanisms of TPIN. However, intense debate is still ongoing about the validity of these mechanisms. In this work, the physical mechanisms proposed in the literature were reviewed and divided into three categories: generation mechanisms, amplification mechanisms, and attenuation mechanisms. The purpose of this article is to gather the published general opinions for further open discussions.

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 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 This research developed methods for a virtual operator model (VOM) to learn the optimal control inputs for operation of a virtual excavator. Virtual design, used to model, simulate, and test new features, has often been limited by the fidelity of the virtual model of human operators. Human operator learns, over time, the capability, limits, and control characteristics of new vehicles to develop the best strategy to maximize the efficiency of operation. However, VOMs are developed with fixed strategies and for specific vehicle models (VMs) and require time-consuming re-tuning of the VOM for each new vehicle design. Thus, there typically is no capability to optimize strategies, taking account of variation in vehicle capabilities and limitations. A VOM learning capability was developed to optimize control inputs for the swing-to-pile task of a trenching operation. Different control strategies consisted of varied combinations of speed control, position control, and coast.

Abstract An accurate and rapid thermal model of an axle-brake system is crucial to the design process of reliable braking systems. Proper thermal management is necessary to avoid damaging effects, such as brake fade, thermal cracking, and lubricating oil degradation. In order to understand the thermal effects inside of a lubricated braking system, it is common to use Computational Fluid Dynamics (CFD) to calculate the heat generation and rejection. However, this is a difficult and time-consuming process, especially when trying to optimize a braking system. This article uses the results from several CFD runs to train a Stacked Ensemble Model (SEM), which allows the use of machine learning (ML) to predict the systems’ temperature based on several input design parameters. The robustness of the SEM was evaluated using uncertainty quantification.

Abstract The Friction stir welding (FSW) is recently presented so to join different materials without the melting process as a solid-state joining technique. A widely application for the FSW process is recently developed in automotive industries. To create the welded components by using the FSW, the plunged probe and shoulder as welding tools are used. The Finite Element Method (FEM) can be used so to simulate and analyze material flow during the FSW process. As a result, thermal and mechanical stresses on the workpiece and welding tool can be analyzed and decreased. Effects of the welding process parameters such as tool rotational speed, welding speed, tool tilt angle, depth of the welding tool, and tool shoulder diameter can be analyzed and optimized so to increase the efficiency of the production process. Material characteristics of welded parts such as hardness or grain size can be analyzed so to increase the quality of part production.

Abstract Automated guided vehicle systems (AGVS) are the prominent one in modern material handling systems used in small manufacturing enterprises (SMEs) due to their exciting features and benefits. This article pinpoints the need of AGVS in SMEs by describing the material handling selection in SMEs and enlightening recent technological developments and approaches of the AGVS. Additionally, it summarizes the analytical and simulation-based tools utilized in design problems of AGVS along with the influence of material handling management and key hurdles of AGVS. The current study provides a limelight towards making smart automated guided vehicles (AGVs) with the simplified and proper routing system and favorable materials and more importantly reducing the cost and increasing the flexibility.

Abstract Today’s explosive condition of the market is compelling the manufacturing organizations to switch from traditional manufacturing (TM) to lean manufacturing (LM) to create a footprint in this competitive era. In this article, 16 critical success factors (CSFs) for LM implementation are identified through a vast literature review, the opinion of academicians and industry experts and interpretive structural modeling (ISM) is used to create interrelationships among the identified CSFs, and interpretive ranking process (IRP) rank these CSFs based on dominance with respect to performance dimensions. Leadership and management made the foundation of an ISM model while the training and people development have secured the first rank in the IRP model. Implementation of such ISM- and IRP-based models of CSF would give a clear understanding of these CSFs so that LM researchers, decision-makers, managers, and practitioners of LM will use their resources more efficiently.

Abstract In this article, a hierarchical coordinated control algorithm for integrating active rear steering and driving/braking force distribution (ARS+D/BFD) was presented. The upper-level control was synthesized to generate the required rear steering angle and external yaw moment by using a sliding-mode controller. In the lower-level controller, a control allocation algorithm considering driving/braking actuators and tire forces constraints was designed to assign the desired yaw moment to the four wheels. To this end, an optimization problem including several equality and inequality constraints were defined and solved analytically. Finally, computer simulation results suggest that the proposed hierarchical control scheme was able to help to achieve substantial enhancements in handling performance and stability.

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 In the case of electric vehicles, due to the charging current limitation of lithium battery at low temperatures (below -20°C), it has been proposed to heat the battery pack up to a suitable temperature range before charging through a liquid-heating plate with PTC. However, at a low state of charge (SOC), there is a question which one could take the place of battery pack to supply power for PTC when heating. So that off-board charger (OFC) has been considered to supply power for PTC in this paper. In order to control the current charging into the battery pack as less as possible at low temperatures, three control schemes of battery management system (BMS) are proposed and compared. Scheme 1: BMS controls the value of charging current request close to the working current of PTC. Scheme 2: BMS controls the value of charging voltage request to reach a state of relative balance. Scheme 3: BMS disconnects the pack from the charger and keeps the connection between PTC and charger.

Abstract Off-highway equipment are subjected to diverse environmental conditions, severe duty cycles, and multiple simultaneous operations. Due to its continuous, high-power adverse operating conditions, equipment are exposed to high thermal loads, which result in the deterioration of its performance and efficiency. This article describes a model-based system simulation approach for thermal performance evaluation of a self-propelled off-highway vehicle. The objective of developing the simulation model including thermal fidelity is to quantify the impact of thermal loads on vehicular system/subsystems performance. This article also describes the use of simulation models for driving architectural design decisions and virtual test replication in all stages of product development.

Abstract Traditionally, Electronic Control Units (ECUs) in vehicles have been left unsecured. Ensuring cybersecurity in an ECU network is challenging as there is no centralized authority in the vehicle to provide security as a service. While progress has been made to address cybersecurity vulnerabilities, many of these approaches have focused on enterprise, software-centric systems and require more computational resources than typically available for onboard vehicular devices. Furthermore, vehicle networks have the additional challenge of mitigating security vulnerabilities while satisfying safety and performance constraints. This article introduces a blockchain framework to detect unauthorized modifications to vehicle ECUs. A proof of concept blockchain prototype framework is implemented on a set of microprocessors (comparable to those used by simple ECUs) as a means to assess the efficacy of using our blockchain approach to detect unauthorized updates.

Abstract ICVs are expected to make the transportation safer, cleaner, and more comfortable in the near future. However, the trend of connectivity has greatly increased the attack surfaces of vehicles, which makes in-vehicle networks more vulnerable to cyberattacks which then causes serious security and safety issues. In this article, we therefore systematically analyzed cyberattacks and corresponding countermeasures for in-vehicle networks of intelligent and connected vehicles (ICVs). Firstly, we analyzed the security risk of ICVs and proposed an in-vehicle network model from a hierarchical point of view. Then, we discussed possible cyberattacks at each layer of proposed network model.

Abstract The rapid development of connected and automated vehicle technologies together with cloud-based mobility services is transforming the transportation industry. As a result, huge amounts of consumer data are being collected and utilized to provide personalized mobility services. Using big data poses serious challenges to data privacy. To that end, the risks of privacy leakage are amplified by data aggregations from multiple sources and exchanging data with third-party service providers, in face of the recent advances in data analytics. This article provides a review of the connected vehicle landscape from case studies, system characteristics, and dataflows. It also identifies potential challenges and countermeasures.

Abstract The development of connected-vehicle technology, which includes vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications, opens the door for unprecedented active safety and driver-enhanced systems. In addition to exchanging basic traffic messages among vehicles for safety applications, a significantly higher level of safety can be achieved when vehicles and designated infrastructure locations share their sensor data. In this article, we propose a new system where cameras installed on multiple vehicles and infrastructure locations share and fuse their visual data and detected objects in real time. The transmission of camera data and/or detected objects (e.g., pedestrians, vehicles, cyclists, etc.) can be accomplished by many communication methods. In particular, such communications can be accomplished using the emerging Dedicated Short-Range Communications (DSRC) technology.

Abstract This research develops a hierarchical control strategy to improve the stability of multi-axle electric vehicles with in-wheel motors while driving at high speed or on low adhesion-coefficient roads. The yaw rate and sideslip angle are chosen as the control parameters, and the direct yaw-moment control (DYC) method is employed to ensure the yaw stability of the vehicle. On the basis of this methodology, a hierarchical yaw stability control architecture that consists of a state reference layer, a desired moment calculation layer, a longitudinal force calculation layer, and a torque distribution layer is proposed. The ideal vehicle steering state is deduced by the state reference layer according to a linear two-degree-of-freedom (2-DOF) vehicle dynamics model.

Abstract The driving safety performance of autonomous driving vehicles must be ensured before on-road implementation. Because it is not realistic to evaluate every single test condition in real-world traffic, computer simulation methods can be used. The driving safety performance can be evaluated by simulating various driving scenarios and calculating surrogate indicators representing dangerous collision risk. This study used a near-miss database and introduced a surrogate indicator that represents a potential risk in the driving scenarios for rear-end and cut-in collisions. The near-miss video database includes several driving scenarios experienced by human drivers, such as dangerous situations that lead to accidents, potentially dangerous situations that have a risk probability to escalate into dangerous situations, and normal driving situations. A skilled and attentive human driver foresees dangerous situations while driving and avoids them.

Abstract Despite more and more rigorous defense mechanisms in place for cyber-physical systems, cybercriminals are increasingly attacking systems for benefits using a variety of means including malware, phishing, ransomware, and denial of service. Cyberattacks could not only cause significant economic loss but also disastrous consequences for individuals and organizations. Therefore, it is advantageous to detect and fix potential cyber vulnerabilities before the system is fielded. To this end, this article presents a language, VERDICT, and a novel framework, Cyber Vulnerability Analysis Framework (CyVAF) to (i) define cyber threats and mitigation defenses based on system properties, (ii) detect cyber vulnerabilities of system architecture automatically, and also (iii) suggest mitigation defenses. VERDICT is developed as an annex to the Architecture Analysis and Design Language (AADL) but can also be used independently.

Abstract The study aims to design a roadmap of the turboelectric propulsion system’s power system architecture, which is based on the Inner Bus Tie Architecture proposed by the National Aeronautics and Space Administration (NASA). The single turboshaft engine shutdown failure mode is analyzed and simulated on MATLAB/Simulink. A General Electric (GE) T700 turboshaft engine is preferred in constructing a turboshaft engine mathematical model. The constructed mathematical model is integrated into NASA’s Inner Bus Tie Architecture. As a result, mechanical to electrical conversion efficiency and power balance of the system is derived. Element sizing is accomplished. Preliminary power requirements for generators, power converters, and electrical motors are calculated to generate a roadmap for future applications. Finally, it is observed that the simulations are found efficient and quite acceptable for such applications.