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Abstract Lane changes are stressful maneuvers for drivers, particularly during high-speed traffic flows. However, modeling driver’s lane-changing decision and implementation process is challenging due to the complexity and uncertainty of driving behaviors. To address this issue, this article presents a personalized Lane-Changing Model (LCM) for Advanced Driver Assistance System (ADAS) based on deep learning method. The LCM contains three major computational components. Firstly, with abundant inputs of Root Residual Network (Root-ResNet), LCM is able to exploit more local information from the front view video data. Secondly, the LCM has an ability of learning the global spatial-temporal information via Temporal Modeling Blocks (TMBs). Finally, a two-layer Long Short-Term Memory (LSTM) network is used to learn video contextual features combined with lane boundary based distance features in lane change events.

Abstract Carbon fiber reinforced plastic (CFRP) has been used in automobiles as well as airplanes. Because of its light weight and high strength, CFRP is a good choice for making vehicle bodies lighter, which would improve fuel economy. Conventional metal bodies provide a convenient body return for electric wiring and offer good shielding against electromagnetic fields. Although CFRP is a conductor, its conductivity is much lower than that of metals. Therefore, CFRP bodies are usually not useful for electric wiring. In thunderstorms, an automotive body is considered to be a Faraday cage that protects the vehicle’s occupants from the potential harms of lightning. Before CFRP becomes widely applied to automotive bodies, its electric and electromagnetic properties need to be investigated in order to determine whether it also works as a Faraday cage against lightning. In this article, CFRP and metal body vehicles were tested under artificial lightning.

Abstract In this paper, an efficient lane detection using deep feature extraction method is proposed to achieve real-time lane detection in diverse road environment. The method contains three main stages: 1) pre-processing, 2) deep lane feature extraction and 3) lane fitting. In pre-processing stage, the inverse perspective mapping (IPM) is used to obtain a bird's eye view of the road image, and then an edge image is generated using the canny operator. In deep lane feature extraction stage, an advanced lane extraction method is proposed. Firstly, line segment detector (LSD) is applied to achieve the fast line segment detection in the IPM image. After that, a proposed adaptive lane clustering algorithm is employed to gather the adjacent line segments generated by the LSD method. Finally, a proposed local gray value maximum cascaded spatial correlation filter (GMSF) algorithm is used to extract the target lane lines among the multiple lines.

Abstract Potential collisions with oncoming traffic while turning left belong to the most safety-critical situations accounting for ~25% of all intersection crossing path crashes. A Left Turn Assist (LTA) was developed to reduce the number of crashes. Crucial for the effectiveness of the system is the design of the human-machine interface (HMI), i.e. defining how the system uses the calculated crash probability in the communication with the driver. A driving simulator study was conducted evaluating a warning strategy for two use cases: firstly, the driver comes to a stop before turning (STOP), and secondly, the driver moves on without stopping (MOVE). Forty drivers drove through three STOP and two MOVE scenarios. For the STOP scenarios, the study compared the effectiveness of an audio-visual warning with an additional brake intervention and a baseline. For the MOVE scenarios, the study analyzed the effectiveness of the audio-visual warning against a baseline.

Abstract This article presents a fault diagnosis approach for roller bearing by applying the autocorrelation approach to filtered vibration measured signal. An optimal Morlet wavelet filter is applied to eliminate the frequency associated with interferential vibrations; the raw measured signal is filtered with a band-pass filter based on a Morlet wavelet function whose parameters are optimized based on maximum Kurtosis. Autocorrelation enhancement is applied to the filtered signal to further reduce the residual in-band noise and highlight the periodic impulsive feature. The proposed technique is used to analyze the experimental measured signal of investigated vehicle gearbox. An artificial fault is introduced in vehicle gearbox bearing an orthogonal placed groove on the inner race with the initial width of 0.6 mm approximately. The faulted bearing is a roller bearing located on the gearbox input shaft - on the clutch side.

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 ISO 26262 needs to be considered when developing safety-relevant E/E systems within the automotive industry. One part of the development process according to ISO 26262 is the derivation of the safety requirements for component functions. Here, one attribute of the safety requirements is the Automotive Safety Integrity Level (ASIL). The ASIL at a component level can be determined using ASIL allocation and decomposition. Considering complex systems such as vehicle electrical systems, countless possibilities can be identified for how the ASILs at a component level can be assigned in line with safety goals. In terms of efficiency, manual assignment is not expedient. Therefore, an algorithm for automated assignment of the ASILs will be introduced which considers constraints based on a fault tree analysis. The function of the approach will be demonstrated using the example of a vehicle electrical system from an automated vehicle.

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 In motorcycles, when they are traveling at medium to high speed, the roll stability is usually maintained by the restoration force generated by self-steering effect. However, when the vehicle is stationary or traveling in low speed, sufficient restoring force does not occur because some of the forces, such as centrifugal force, become small. In our study, we aimed at prototyping a motorcycle having a roll stability realized by a steering control when the vehicle is stationary or traveling in low speed. When we considered a mathematical control model to be applied, general models of four-degree-of-freedom had a critical inconvenience that the formulae include nonlinear second derivatives making them excessively complicated for deriving a practically applicable control method. Accordingly, we originally constructed a new control model which has equivalent two point masses (upper and lower from the vehicle’s center of gravity).

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 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 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 Since the tire inflation pressure has a significant influence on safety, comfort and environmental behavior of a vehicle, the choice of the optimal inflation pressure is always a conflict of aims. The development of a highly dynamic Tire Pressure Control System (TPCS) can reduce the conflict of minimal rolling resistance and maximal traction. To study the influence of the tire inflation pressure on longitudinal tire characteristics under laboratory conditions, an experimental sensitivity analysis is performed using a multivalent usable Corner Module Test Rig (CMTR) developed by the Automotive Engineering Group at Technische Universität Ilmenau. The test rig is designed to analyze suspension system and tire characteristics on a roller of the recently installed 4 chassis roller dynamometer. Camber angle, toe angle and wheel load can be adjusted continuously. In addition, it is possible to control the temperature of the test environment between −20 °C and +45 °C.

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.

Abstract Catalytic converters, a primary component in most automotive emissions control systems, do not function well until they are heated substantially above ambient temperature. As the primary energy for catalyst heating comes from engine exhaust gases, plug-in hybrid electric vehicles (PHEVs) that have the potential for short and infrequent use of their onboard engine may have limited energy available for catalytic converter heating. This article presents a comparison of multiple hybrid supervisory control strategies to determine the ability to avoid engine cold starts during a blended charge-depleting propulsion mode. Full vehicle and catalytic converter simulations are performed in parallel with engine dynamometer testing in order to examine catalyst temperature variations during the course of the US06 City drive cycle. Emissions and energy consumption (E&EC) calculations are also performed to determine the effective number of engine starts during the drive cycle.

Abstract The advancement towards development of autonomy follows either the bottom-up approach of gradually improving and expanding existing Advanced Driver Assist Systems (ADAS) technology where the driver is present in the control loop or the top-down approach of directly developing autonomous vehicle hardware and software using alternative approaches without the driver present in the control loop. Most ADAS systems today fall under the classification of SAE Level 1 which is also referred to as the driver assistance level. The progression from SAE Level 1 to SAE Level 2 or partial automation involves the critical task of merging automated lateral control and automated longitudinal control such that the tasks of steering and acceleration/deceleration are not required to be handled by the driver under certain conditions [1].