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In electrified vehicles, auxiliary units can be a dominant source of noise, one of which is the refrigerant scroll compressor. Compared to vehicles with combustion engines, e-vehicles require larger refrigerant compressors, as in addition to the interior, also the battery and the electric motors have to be cooled. Currently, scroll compressors are widely used in the automotive industry, which generate one pressure pulse per revolution due to their discontinuous compression principle. This results in speed-dependent pressure fluctuations as well as higher-harmonic pulsations that arise from reflections. These fluctuations spread through the refrigeration cycle and cause the vibration excitation of refrigerant lines and heat exchangers. The sound transmission path in the air conditioning heat exchanger integrated in the dashboard is particularly critical. Various silencer configurations can be used to dampen these pulsations.

By building on mature internal combustion engine (ICE) hardware combined with dedicated hydrogen (H2) technology, the H2-ICE has excellent potential to accelerate CO2 reduction. H2-ICE concepts can therefore contribute to realizing the climate targets in an acceptable timeframe. In the landscape of H2-ICE combustion concepts, High Pressure Direct Injection (HPDI™) is an attractive option considering its high thermal efficiency, wide load range and its applicability to on-road as well as off-road heavy-duty equipment. Still, H2-HPDI is characterized by diffusion combustion, giving rise to significant NOx emissions. In this paper, the potential of H2-HPDI toward compliance with future emissions legislation is explored on a 1.8L single-cylinder research engine. With tests on multiple load-speed points, Exhaust Gas Recirculation (EGR) was shown to be an effective measure for reducing engine-out NOx, although at the cost of a few efficiency points.

In the effort to achieve the goal of a climate-neutral transportation system, the use of hydrogen and other synthetic fuels plays a key role. As battery electric vehicles become more widespread, e-fuels could be used to defossilize the hard-to-electrify transportation sectors and to store energy produced from renewable and non-continuous energy sources. Among e-fuels, hydrogen and ammonia are very attractive because they are carbon-neutral and their oxidation does not lead to any CO2 emissions. Furthermore, hydrogen/ammonia mixtures overcome the issues that arise as each of the two fuels is separately used. In the automotive sector, the use of either hydrogen, ammonia or their blends require a characterization of such mixtures under engine-like conditions, that is, at high pressures and temperatures. The aim of this work is to evaluate the Laminar Flame Speed (LFS) of hydrogen/ammonia mixtures by varying the thermodynamic conditions and the molar composition of the reactants.

Though modal analysis is a common tool to evaluate the dynamic properties of a structure, there are still many individual decisions to be made during the process which are often based on experience and make it difficult for occasional users to gain reliable and correct results. One of those experience-based choices is the correct number and placement of reference points. This decision is especially important, because it must be made right in the beginning of the process and a wrong choice is only noticeable in the very end of the process. Picking the wrong reference points could result in incomplete modal analysis outcomes, as it might make certain modes undetectable, compounded by the user's lack of awareness about these missing modes. In the paper an innovative approach will be presented to choose the minimal number of mandatory reference points and their placement.

Electrified vehicles are particularly quiet, especially at low speeds due to the absence of combustion noises. This is why there are laws worldwide for artificial driving sounds to warn pedestrians. These sounds are generated using a so-called Acoustic Vehicle Alerting System (AVAS) which must maintain certain minimum sound pressure levels in specific frequency ranges at low speeds. The creation of the sound currently involves an iterative and sometimes time-consuming process that combines composing the sound on a computer with measuring the levels with a car on an outside noise test track. This continues until both the legal requirements and the subjective demands of vehicle manufacturers are met. To optimize this process and reduce the measurement effort on the outside noise test track, the goal is to replace the measurement with a simulation for a significant portion of the development.

This specification covers a titanium alloy in the form of bars, forgings, and flash-welded rings up through 12.000 inches (304.80 mm), inclusive, in diameter or least distance between parallel sides, and stock of any size for forging or flash-welded rings. Bars, forgings, and flash-welded rings with a nominal thickness of 3.000 inches (79.20 mm) or greater shall have a maximum cross-sectional area of 113 square inches (729 cm2) (see 8.5).

Verification and validation (V&V) of autonomous vehicles (AVs) is a challenging task. AVs must be thoroughly tested, to ensure their safe functionality in complex traffic situations including rare but safety-relevant events. Furthermore, AVs must mitigate risks and hazards that result from functional insufficiencies, as described in the Safety of the Intended Functionality (SOTIF) standard. SOTIF analysis includes iterative identification of driving scenarios that are not only unsafe, but also unknown. However, identifying SOTIF’s unknown-unsafe scenarios is an open challenge. In this paper we proposed a systematic optimization-based approach for identification of unknown-unsafe scenarios. The proposed approach consists of three main steps including data collection, feature extraction and optimization towards unknown unsafe scenarios.

As a key technology of intelligent transportation system, vehicle type recognition plays an important role in ensuring traffic safety,optimizing traffic management and improving traffic efficiency, which provides strong support for the development of modern society and the intelligent construction of traffic system. Aiming at the problems of large number of parameters, low detection efficiency and poor real-time performance in existing vehicle type recognition algorithms, this paper proposes an improved vehicle type recognition algorithm based on YOLOv5. Firstly, the lightweight network model MobileNet-V3 is used to replace the backbone feature extraction network CSPDarknet53 of the YOLOv5 model. The parameter quantity and computational complexity of the model are greatly reduced by replacing the standard convolution with the depthwise separable convolution, and enabled the model to maintain higher accuracy while having faster reasoning speed.

The global energy crisis and drastic climate change are continuously promoting the implementation of sustainable energy sources. To meet the emission standards and carbon-neutrality targets in vehicle industry, ammonia is considered to be one of the promising carbon-neutral fuels. However, running the engines on high amounts of ammonia may lead to significantly high ammonia slip. This originates huge safety concerns. Therefore, hydrogen is added in certain ratio with ammonia to promote combustion and reduce ammonia slip. Furthermore, adding diesel as a pilot fuel further facilitates the combustion reactions. This experimental study investigated the effect of different ammonia-hydrogen blend ratios on in-cylinder pressure, heat release rate, cumulative heat release, indicated mean effective pressure (IMEP), indicated thermal efficiency (ITE), CA5 and CA50. This effect of blend ratios was tested for varied diesel pilot amounts and timings.

Water content estimation is a key problem for studying the PEM fuel cell. When several hundred fuel cells are connected in serial and their active surface area is enlarged for sufficient power, the difference between cells becomes significant with respect to voltage and water content. The voltage of each cell is measurable by the cell voltage monitor (CVM) while it is difficult to estimate water content of the individual. Resistance of the polymer electrolyte membrane is monotonically related to its water content, so that the new online high frequency resistance (HFR) measurement technique is investigated to identify the uniformity of water content between cells and analyze its sensitivity to operating conditions in this paper. Firstly, the accuracy of the proposed technique is experimentally validated to be comparable to that of a commercialized electrochemical impedance spectroscopy (EIS) measurement equipment.

As a key tool to maintain urban cleanliness and improve the road environment, road cleaning vehicles play an important role in improving the quality of life of residents. However, the traditional road cleaning vehicle requires the driver to monitor the situation of road garbage at all times and manually operate the cleaning process, resulting in an increase in the driver 's work intensity. To solve this problem, this paper proposes a road garbage recognition algorithm based on improved YOLOv5, which aims to reduce labor consumption and improve the efficiency of road cleaning. Firstly, the lightweight network MobileNet-V3 is used to replace the backbone feature extraction network of the YOLOv5 model. The number of parameters and computational complexity of the model are greatly reduced by replacing the standard convolution with the deep separable convolution, which enabled the model to have faster reasoning speed while maintaining higher accuracy.

A multi-dimensional cathode spot generation model is proposed to study the interaction between the plasma arc and cathode surface of a spark plug during the ignition process. The model is focused on the instationary (high current) arc phase immediately following breakdown, and includes detailed physics for the phenomena during spot formation such as ion collision, thermal-field emission, and metal vaporization, to simulate the surface heat source, current density and surface pressure. The spot formation for a platinum cathode is simulated using the VOF (volume of fluid) model within FLUENT, where the local metal is melted and deformed by pressure differences on the surface. A random walk model has been integrated to consider the movement of the arc center, resulting in the formation of different types of spots.

In the field of autonomous driving trajectory planning, it’s virtual to ensure real-time planning while guaranteeing feasibility and robustness. Current widely adopted approaches include decoupling path planning and velocity planning based on optimization method, which can’t always yield optimal solutions, especially in complex dynamic scenarios. Furthermore, search-based and sampling-based solutions encounter limitations due to their low resolution and high computational costs. This paper presents a novel spatio-temporal trajectory planning approach that integrates both search-based planning and optimization-based planning method. This approach retains the advantages of search-based method, allowing for the identification of a global optimal solution through search. To address the challenge posed by the non-convex nature of the original solution space, we introduce a spatio-temporal semantic corridor structure, which constructs a convex feasible set for the problem.

The bi-stable phenomena of the Ahmed model were experimentally studied at different rear slant angles (31.8 °, 42 °, 50 °, 60 °, 75 °, 90°) and different Reynolds numbers (9.2 × 104, 1.84 × 105, 2.76 × 105). The analysis of pressure gradients both on the base and slant indicate that no bi-stable phenomena were observed at different Reynolds numbers when the slant angle was less than or equal to 50°. However, for the rear slant angles greater than or equal to 60°, the pressure gradients consistently shift between two preferred values at various Reynolds numbers, indicating the presence of bi-stable behavior in the spanwise direction. Therefore, the critical angle for the appearance of bi-stability in the Ahmed model lies within the range of 50° to 60°, and the existence of bistable behavior remains unaffected by the Reynolds number. As the slant angle increases, the switching rate decreases significantly until the angle is greater than 60°.

Using the recycled waste oils are to be focused for the protection of environment by reducing the land pollution and disposal costs. This study is to use the recycled waste engine oil, waste cooking oil and waste plastic oil along with Bio-butanol from the waste cut vegetables and fruits. Initially, properties and solubility were tested for choosing a suitable blend for fueling into diesel engine from various proportions. These three blends from the base of three waste oils are then tested by modifying and standard engine operating parameters for performance. The properties tests results as 18% of waste engine oil (by volume) with bio-butanol, 16% of waste cooking oil (by volume) with bio- butanol and 24% of waste plastic oil (by volume) with bio-butanol are found competent for fueling engine. These blends produces low efficiency in lower brake powers and the emissions of smoke, hydrocarbons and carbon monoxide are also higher during the operation under standard parameters.

This paper delves into the investigation of flatness-based active damping control for hybrid vehicle transmissions. The main objective is to improve the current in-production controller performances without the need for additional sensors or observers. The primary goals include improving torque setpoint tracking, enhancing robustness margins, and ensuring zero steady-state torque correction. The investigation proceeds in several steps: Initially, both the general differential flatness property and the identification of flat outputs in linear dynamical systems are revisited. Subsequently, the bond graph formalism is employed to deduce straightforwardly the dynamical equations of the system. Next, a new flat output of the vehicle transmission is identified and utilized to formulate the trajectory tracking controller to align with the required control objectives and to fulfill the system constraints.

Recent automobile engines are equipped with many devices that are driven by oil pressure. Generally, engine oil is used for oil pressure, and in addition to its conventional functions of lubrication and cooling, etc., it also plays an important role in accurately driving such devices. One of the factors that can interfere with the characteristics of engine oil is air contamination. Excessive air contamination can cause issues with driving devices. Although there are various factors that contribute to air contamination, this paper focuses on, and attempts to help predict, the air generated by engine oil falling and colliding with the surface of the oil in the oil pan as it returns from the top to the bottom of the engine. Using the particle method as the prediction method, the coupled Moving Particle Simulation (MPS) and Discrete Element Method (DEM) calculations were used to represent the generation of air.

This paper details testing for torque converter clutch (TCC) characterization during steady state and dynamic operation under controlled slip conditions on a dynamometer setup. The subject torque converter under test is a twin plate clutch with a dual stage turbine damper without a centrifugal pendulum absorber. An overview is provided of the dynamometer setup, hydraulic system and control techniques for regulating the apply pressure to the torque converter and clutch. To quantify the performance of the clutch in terms of control stability, pressure to torque relationship and the dynamic behavior during apply and release, a matrix of oil temperatures, output speeds, input torques, and clutch apply pressures were imposed upon the torque converter.

Ammonia has received attention as an alternative hydrogen carrier and a potential fuel for thermal propulsion systems with a lower carbon footprint. One strategy for high power density in ammonia applications will be direct injection of liquid ammonia. Understanding the evaporation and mixing processes associated with this is important for model development. Additionally, as a prior step for developing new injectors, it is of interest to understand how a conventional gasoline direct injection (GDI) injector would behave when used for liquid ammonia without any modifications. Pure anhydrous ammonia, in its liquid form, was injected from a single hole GDI injector at a fuel pressure of 150 bar into an optically accessible constant volume chamber filled with nitrogen gas for ammonia spray measurements. The chamber conditions spanned a wide range of pressures from 3 − 15 bar at an increment of 1 bar or 2 bar between the test points.