Search Results

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 Heat generation characteristics of lithium ion batteries are vital for both the optimization of the battery cells and thermal management system design of battery packs. Compared with other factors, internal resistance has great influence on the thermal behavior of Li-ion batteries. Focus on a 3 Ah pouch type battery cell with the NCM/C material system, this paper quantitatively evaluates the battery heat generation behavior using an Extended Volume-Accelerating Rate Calorimeter in combination with a battery cycler. Also, internal resistances of the battery cell are measured using both the hybrid pulse power characteristic (HPPC) and electro-chemical impedance spectroscopy (EIS) methods. Experimental results show that the overall internal resistance obtained by the EIS method is close to the ohmic resistance measured by the HPPC method. Heat generation power of the battery cell is small during discharge processes lower than 0.5 C-rate.

Abstract Battery Drain problems can occur in the vehicle due to improper network management between electronic control units (ECUs). Aim of this paper is to identify the factors that cause transmission and cease of transmission of a network management message of an ECU along with its application messages that controls the sleep/wake-up performance of other ECUs in the network. Strategy used here is, based on the root cause analysis of problems found in Display unit in vehicle environment, the functional CAN signals impacting sleep/wake-up behavior is re-mapped along with the state flow transition of AUTOSAR NM Algorithm. A re-defined test case design and simulation for vehicle model is created. Especially it focuses on validating the impact of functional CAN signals on DUT’s sleep/wake-up performance.

Abstract The high-frequency noise issue is one of the most significant noise, vibration, and harshness problems, particularly in battery electric vehicles (BEVs). The sound package treatment is one of the most important approaches toward solving this problem. Owing to the limitations imposed by manufacturing error, assembly error, and the operating conditions, there is often a big difference between the actual values and the design values of the sound package components. Therefore, the sound package parameters include greater uncertainties. In this article, an uncertainty analysis method for BEV interior noise was developed based on an interval model to investigate the effect of sound package uncertainty on the interior noise of a BEV. An interval perturbation method was formulated to compute the uncertainty of the BEV’s interior noise.

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 A novel use of state estimation methods as initial input for a landing response analysis is proposed in this work. Six degrees of freedom (DOF) non-linear landing response model is conceived by considering longitudinal dynamics of aircraft as a rigid body with heave-and-pitch motions coupled onto a bicycle landing gear † arrangement. The DOF for each landing gear consist of vertical and longitudinal motions of un-sprung mass, considering strut bending flexibility. The measurement data for state estimation is obtained for three landing cases using non-linear flight mechanics model interfaced with pilot-in-loop simulation. State estimation methods such as Upper Diagonal Adaptive Extended Kalman Filter (UD-AEKF) with fuzzy-based adaptive tuning and Un-scented Kalman Filter (UKF) were adapted for landing maneuver problem. On the basis of estimation error metrics, aircraft state from UKF is considered during onset of touchdown.

Abstract A key problem of the construction of fully electric aircraft is the limited energy density of battery packs. It is generally accepted that this can only be overcome via new, denser battery chemistry together with a further increase in the efficiency of power utilization. One appealing approach for achieving the latter is using laser-assisted filler-based joining technologies, which offers unprecedented flexibility for achieving battery cell connections with the least possible electrical loss. This contribution presents our results on the effect of various experimental and process parameters on the electrical and mechanical properties of the laser-formed bond.

Abstract Improving the energy performance of batteries can increase the reliability of electric aircraft. To achieve this goal, battery management systems (BMS) are required to keep the temperature within the battery pack and cells below the safety limits and make the temperature distribution as even as possible. Batteries have a limited service life as a result of unwanted chemical reactions, physical changes that cause the loss of active materials in the structure, and internal resistance increase during the charging and discharging cycle of the battery. These changes usually affect the electrical performance of batteries. Battery life can be increased only by reducing or preventing unwanted chemical reactions. Lithium-ion (Li-ion) batteries are a suitable option due to their high specific energy and energy density advantages. In this study, the necessity of heat management is emphasized. The discharge tests of the Li-ion battery provided 94.6 Wh under 10C and 90.9 Wh under 1C.

Abstract The range of an aircraft is determined by the amount of energy that its batteries can store. Today, larger batteries are used to increase the range of electric vehicles, although energy efficiency decreases as the weight of the vehicles increases. Among the elements, lithium (Li) is the lightest and has the highest electrochemical potential. Therefore, the use of Li-ion batteries is recommended for hybrid aircraft. In addition, Li-ion batteries are the most common type of battery that is used in portable electronic devices such as smartphones, tablets, and laptops. However, Li-ion batteries may explode due to temperature. Therefore, the thermal analysis of Li-ion batteries was investigated both experimentally and numerically. Li-ion batteries were connected in series (the number is 9). Noboru’s theory of heat generation was discussed in the estimation of energy data.

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 In this article, a unique design for Hydro-Pneumatic Energy Harvesting Suspension HPEHS system is introduced. The design includes a hydraulic rectifier to maintain one-way flow direction in order to obtain maximum power generation from the vertical oscillation of the suspension system and achieve handling and comfort car drive. A mathematical model is presented to study the system dynamics and non-linear effects for HPEHS system. A simulation model is created by using Advanced Modeling Environment Simulations software (AMEsim) to analyze system performance. Furthermore, a co-simulation platform model is developed using Matlab-Simulink and AMEsim to optimize the PID controller parameters of the external variable load resistor applied on the generator by using Particle Swarm Optimization (PSO).

Abstract Recently, electric heavy-duty tractor-trailers (EHDTTs) have assumed significance as they present an immediate solution to decarbonize the transportation sector. Hence, to illustrate the economic viability of electrifying the freight industry, a detailed numerical model to estimate the battery capacity for an EHDTT is proposed for a route between Washington, DC, to Knoxville, TN. This model incorporates the effects of the terrain, climate, vehicular forces, auxiliary loads, and payload in order to select the appropriate motor and optimize the battery capacity. Additionally, current and near-future battery chemistries are simulated in the model. Along with equations describing vehicular forces based on Newton’s second law of motion, the model utilizes the Hausmann and Depcik correlation to estimate the losses caused by the capacity offset of the batteries. Here, a Newton-Raphson iterative scheme determines the minimum battery capacity for the required state of charge.

Abstract A new concept of instantaneous wheel turn center (IWTC) is proposed to evaluate and improve multi-axle vehicle steering coordination performance. The concept of IWTC and its calculation method are studied. The index named dispersion of IWTC is developed to evaluate the vehicle steering coordination performance quantitatively. The simulation tests based on a three-axle off-road vehicle model are conducted under different vehicle velocities and lateral accelerations. The simulation results show that the turn centers of different wheels are disperse, and the dispersion becomes larger with the increase of vehicle velocities and lateral acceleration. Since suspension has important influences on vehicle steering performance, the genetic algorithm is used to optimize the suspension hard points and bushing stiffness, aiming at minimizing the dispersion of wheel turn centers (DWTC) to improve the vehicle steering coordination performance.

Abstract When commercial vehicles drive in a mountainous area, the complex road condition and long slopes cause frequent acceleration and braking, which will use 25% more fuel. And the brake temperature rises rapidly due to continuous braking on the long-distance downslopes, which will make the brake drum fail with the brake temperature exceeding 308°C [1]. Meanwhile, the kinetic energy is wasted during the driving progress on the slopes when the vehicle rolls up and down. Our laboratory built a model that could calculate the distance from the top of the slope, where the driver could release the accelerator pedal. Thus, on the slope, the vehicle uses less fuel when it rolls up and less brakes when down. What we do in this article is use this model in a real vehicle and measure how well it works.

Abstract The supersession of metallic alloys with lightweight, high-strength composites is popular in the aircraft industry. However, aviation electronic enclosures for large format batteries and high power conversion electronics are still primarily made of aluminum alloys. These aluminum enclosures have attractive properties regrading structural integrity for the heavy internal parts, electromagnetic interference (EMI) suppression, electrical bonding for the internal cells, and/or electronics and failure containment. This paper details a lightweight carbon fiber composite chassis developed at Meggitt Sensing Systems (MSS) Securaplane, with a copper metallic mesh co-cured onto the internal surfaces resulting in a 50% reduction in weight when compared to its aluminum counterpart. In addition to significant weight reduction, it provides equal or improved performance with respect to EMI, structural and flammability performance.

Abstract This article investigates the fuel savings potential of a series hybrid military truck using a simultaneous battery pack design and powertrain supervisory control optimization algorithm. The design optimization refers to the sizing of the lithium-ion battery pack in the hybrid configuration. The powertrain supervisory control optimization determines the most efficient way to split the power demand between the battery pack and the engine. Despite the available design and control optimization techniques, a generalized mathematical formulation and solution approach for combined design and control optimization is still missing in the literature. This article intends to fill that void by proposing a unified framework to simultaneously optimize both the battery pack size and power split control sequence. This is achieved through a combination of genetic algorithm (GA) and Pontryagin’s minimum principle (PMP) where the design parameters are integrated into the Hamiltonian function.