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Abstract Windshield glare at night is a safety concern for all drivers. Public transit bus drivers also face another concern about glare caused by interior lighting sources originally designed for passenger safety. The extent to which interior light reflections contribute to glare is unknown. Unique methods for measuring discomfort and disability glare during bus driving were developed. An initial simulation study measured windshield luminance inside of a New Flyer D40LF diesel bus parked in a controlled, artificial, totally darkened test environment. Findings indicated significant disability glare (from elevated luminance) in the drivers’ primary field of view due to interior reflections. Any reduction in contrast would result in less prominent glare if actual driving conditions differ. To assess this, levels of windshield glare were also measured with the bus parked on the roadside under the “background glow” of the urban environment.

Abstract The water droplet erosion (WDE) on high-speed rotating wheels appears in several engineering fields such as wind turbines, stationary steam turbines, fuel cell turbines, and turbochargers. The main reasons for this phenomenon are the high relative velocity difference between the colliding particles and the rotor, as well as the presence of inadequate material structure and surface parameters. One of the latest challenges in this area is the compressor wheels used in turbochargers, which has a speed up to 300,000 rpm and have typically been made of aluminum alloy for decades, to achieve the lowest possible rotor inertia. However, while in the past this component was only encountered with filtered air, nowadays, due to developments in compliance with tightening emission standards, various fluids also collide with the spinning blades, which can cause mechanical damage.

Abstract Automated driving as one of the most anticipated technologies is approaching its market release in the near future. Since several years, the research in the automotive industry is largely focused on its development and presents well-engineered prototypes. The many aspects of this development do not only concern the function and its components itself, but also the proof of safety and assessment for its market release. It is clear that previous methods used for the release of Advanced Driver Assistance Systems are not applicable. In contrast to already released systems, automated driving is not restricted to a certain field of application in terms of driving scenarios it has to take action in. This results in an infeasible amount of required testing and unforeseeable scenarios the function can face throughout its lifetime. In this article, we show a scenario-based approach that promises to overcome those challenges.

Abstract As automated driving technology is evolving quickly and becomes more widely deployed, it is essential to validate the Safety of the Intended Functionality (SOTIF) of Automated Vehicles (AVs) prior to mass production. In general, an exhaustive real-world scenario validation of AVs is considered infeasible due to excessive time consumption. Additionally, simulation tests alone are often regarded as inadequate since it is difficult to model the system and physical properties of vehicles with full fidelity. Therefore, a SOTIF validation method for AVs is proposed in this article, which consists of structure design and scenario determination. A mature, systematic, and complete set of testing and evaluation procedures is presented in structure design, and a scenario generation method is introduced in scenario determination. The SOTIF validation method takes advantage of both simulation tests and on-road tests.

Abstract The crush energy is a key parameter to determine the delta-V in accident reconstructions. Since an accurate car crush profile can be obtained from 3D scanners, this research aims at validating the methods currently used in calculating crush energy from a crush profile. For this validation, a finite element (FE) car model was analyzed using various types of impact conditions to investigate the theory of energy-based accident reconstruction. Two methods exist to calculate the crush energy: the work based on the barrier force and the work based on force calculated by the vehicle acceleration times the vehicle mass. We show that the crush energy calculated from the barrier force was substantially larger than the internal energy calculated from the FE model. Whereas the crush energy calculated from the vehicle acceleration was comparable to the internal energy of the FE model.

Abstract One of the key problems of battery electric vehicles is the risk of severe range reduction in winter conditions. Technologies such as heat pump systems can help to mitigate such effects, but finding adequate heat sources for the heat pump sometimes can be a problem, too. In cold ambient conditions below −10°C and for a cold-soaked vehicle this can become a limiting factor. Storing waste heat or excess cold when it is generated and releasing it to the vehicle thermal management system later can reduce peak thermal requirements to more manageable average levels. In related architectures it is not always necessary to replace existing electric heaters or conventional air-conditioning systems. Sometimes it is more efficient to keep them and support them, instead. Accordingly, we show, how latent heat storage can be used to increase the efficiency of existing, well-established heating and cooling technologies without replacing them.

Abstract This article presents surrogate mixtures that simulate the physical and chemical properties in the auto-ignition of hydrotreated vegetable oil (HVO). Experimental investigation was conducted in the Ignition Quality Tester (IQT) to validate the auto-ignition properties with respect to those of the target fuel. The surrogate development approach is assisted by artificial neural network (ANN) embedded in MATLAB optimization function. Aspen HYSYS is used to calculate the key physical and chemical properties of hundreds of mixtures of representative components, mainly alkanes—the dominant components of HVO, to train the learning algorithm. Binary and ternary mixtures are developed and validated in the IQT. The target properties include the derived cetane number (DCN), density, viscosity, surface tension, molecular weight, and volatility represented by the distillation curve. The developed surrogates match the target fuel in terms of ignition delay and DCN within 6% error range.

Abstract The first objective of this study, addressed in Part 1, is to use finite element (FE) human body modeling (HBM) to evaluate the tangent of the Belt-to-Pelvis angle (tanθBTP) as a submarining predictor in frontal crashes for occupants in reclined seats. The second objective, addressed in Part 2, is to use this predictor to assess two technical solutions for reducing submarining risks for two different occupant anthropometries. In Part 1, tanθBTP (the lap belt penetration from the anterior superior iliac spine [ASIS] in the abdominal direction) was evaluated in impact simulations with varying seat belt anchor positions. Sled simulations with a 56 km/h full-frontal crash pulse were performed with the SAFER HBM morphed to the anthropometry of a small female and average male. A correlation was found between the submarining predictor and submarining.

Abstract To reduce fuel consumption and carbon dioxide (CO2) emissions from mobile air conditioning (A/C) systems, “U.S. Light-Duty Vehicle Greenhouse Gas Emissions and Corporate Average Fuel Economy Standards” identified solar/thermal technologies such as solar control glazings, solar reflective paint, and active and passive cabin ventilation in an off-cycle credit menu. National Renewable Energy Laboratory (NREL) researchers developed a sophisticated analysis process to calculate U.S. light-duty A/C fuel use that was used to assess the impact of these technologies, leveraging thermal and vehicle simulation analysis tools developed under previous U.S. Department of Energy projects. Representative U.S. light-duty driving behaviors and weighting factors including time-of-day of travel, trip duration, and time between trips were characterized and integrated into the analysis.

Abstract This article focuses on the development of a two-way coupled methodology to predict gear temperature of oil jet lubricated transmissions using commercial software for computational fluid dynamics simulation. The proposed methodology applies an overset mesh technique to model the gear interlocking motion, multiphase of air-oil mixture, and heat transfer. Two gear pairs were used to develop and validate the methodology, an overdrive helical gear pair of a commercial vehicle transmission and a standard spur gear pair. Different oil jet lubrication methods were investigated using the proposed methodology, such as oil jet directed at the into-mesh position and at the out-of-mesh position. This investigation showed that out of mesh lubrication direction shows better cooling performance which is in well agreement with previous studies of literature.

Abstract In urban roads the engine speed and the load vary suddenly and frequently, resulting in increased exhaust emissions. In such operations, the effect of air injection technique to access the transient response of the engine is of great interest. The effectiveness of air injection technique in improving the transient response under speed transient is investigated in detail [1]; however, it is not evaluated for the load transients. Load step demand of the engine is another important event that limits the transient response of the turbocharger. In the present study, response of a heavy-duty turbocharged diesel engine is investigated for different load conditions. Three cases of load transients are considered: constant load, load magnitude variation, and load scheduling. Air injection technique is simulated and after optimization of injection pressure based on orifice diameter, its effect on the transient response is presented.

Abstract Emerging technologies for connected and automated vehicles (CAVs) are rapidly advancing, and there is an incremental adoption of partial automation systems in existing vehicles. Nevertheless, there are still significant barriers before fully or highly automated vehicles can enter mass production and appear on public roads. These are not only associated with the need to ensure their safe and efficient operation but also with cost and delivery time constraints. A key challenge lies in the testing and validation (T&V) requirements of CAVs, which are expected to be significantly higher than those of traditional and partially automated vehicles. Promising methodologies that can be used toward this goal are scenario-based (SBT) and X-in-the-Loop (XiL) testing. At the same time, complex techniques such as co-simulation and mixed-reality simulation could also provide significant benefits.

Abstract Scenario-based testing is a promising approach to solving the challenge of proving the safe behavior of vehicles equipped with automated driving systems (ADS). Since an infinite number of concrete scenarios can theoretically occur in real-world road traffic, the extraction of scenarios relevant in terms of the safety-related behavior of these systems is a key aspect for their successful verification and validation. Therefore, a method for extracting multimodal urban traffic scenarios from naturalistic road traffic data in an unsupervised manner, minimizing the amount of (potentially biased) prior expert knowledge, is proposed. Rather than an (elaborate) rule-based assignment by extracting concrete scenarios into predefined functional scenarios, the presented method deploys an unsupervised machine learning pipeline. The approach allows for exploring the unknown nature of the data and their interpretation as test scenarios that experts could not have anticipated.

Abstract Accurate exhaust gas temperature (EGT) measurements are vital in the design and development process of internal combustion engines (ICEs). The unsteady ICE exhaust flow and thermal inertia of commonly used sheathed thermocouples and resistance thermometers require high bandwidth EGT pulse measurements for accurate cycle-resolved and mean EGTs. The EGT pulse measurement challenge is typically addressed using exposed thin-wire resistance thermometers or thermocouples. The sensor robustness to response tradeoff limits ICE tests to short durations over a few exhaust conditions. Larger diameter multiwire thermocouples using response compensation potentially overcomes the tradeoff. However, the literature commonly adopts weaker slack wire designs despite indications of coated weld taut wires being robust.

Abstract Diesel engines include systems for cooling, lubrication, and fuel injection and contain a variety of components. A malfunction in any of the engine systems or the presence of any faulty element influences engine performance and deteriorates its components. This research is concerned with the untimely appearance of vital cracks in the liners of a turbocharged heavy-duty Diesel engine. To find the root causes for premature failure, rigorous examinations through visual observations, material characterization, and metallographic investigations are performed. These include Scanning Electron Microscope (SEM) and Energy-Dispersive Spectroscopy (EDS), fracture mechanics analysis, and performance examination, which are also followed by Finite Element Moldings. To find the proper remedy to resolve the problem, drawing a precise and reliable picture of the engine’s operating conditions is required.

Abstract This work develops a comprehensive thermohydrodynamic (THD) model for high-speed squeeze film dampers (SFDs) in the presence of lubricant inertia effects. Firstly, the generalized expression for Reynolds equation is developed. Additionally, in order to reduce the complexity of the hydrodynamic equations, an average radial viscosity is defined and integrated into the equations. Subsequently, an inertial correction to the pressure is incorporated by using a first-order perturbation technique to represent the effect of lubricant inertia on the hydrodynamic pressure distribution. Furthermore, a thermal model, including the energy equation, the Laplace heat conduction equations in the surrounding solids (i.e. the journal and the bush), and the thermal boundary conditions at the interfaces is constructed. Moreover, the system of partial differential hydrodynamic and thermal equations is simultaneously solved by using an iterative numerical algorithm.

Abstract Increasing thermal and fuel efficiency in Internal Combustion Engines (ICEs) requires thorough investigations on the combustion process and its thermodynamics. The first law of thermodynamics expresses the balance of the energy, while the second law specifies the maximum achievable work. In this article, Low-Temperature Combustion (LTC) strategies, including Homogeneous Charge Compression Ignition (HCCI), Reactivity Controlled Compression Ignition (RCCI), Partially Premixed Combustion (PPC), and Direct Dual-Fuel Stratification (DDFS) were analyzed by the first and second law approaches, and they were compared with ideal-diesel cycle and Conventional Diesel Combustion (CDC). HCCI and RCCI had the highest exergy efficiency of 50.8% and 49.2%, respectively, compared to other cases, and exergy destruction in these cases was the lowest (25.3% and 27.5%, respectively).

Abstract High technology expertise and strong advancement in electric vehicles and Lithium (Li)-ion battery devices and systems have increased the speed of development and application of new equipment. It is reported that Li-ion battery life reduces almost by 60 days per degree temperature rise in an operational temperature of 30°C to 40°C, which makes cooling a high priority. The current study focuses on cooling the battery system using Phase Change Material (PCM) placed as bands of different dimensions around the prismatic battery. Eight novel designs of varying dimensions were constructed for three-volume scenarios. The heat generations considered in this study are 6,855 W/m3, 12,978 W/m3, 19,100 W/m3, and 63,970 W/m3. The data obtained was trained using an artificial neural network (ANN), and an equation was attained to fit the data. The optimum placement of PCM with respect to the number of bands and dimensions was achieved through a Genetic Algorithm.

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 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.