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With the rapid development of artificial intelligence, the autonomous vehicles (AV) have attracted considerable attention in the automotive industry. However, different factors negatively impact the adoption of the AVs, delaying their successful commercialization. Accretion of atmospheric icing, especially wet snow, on AV sensors causes blockage on their lenses, making them prone to lose their sight, in turn, increasing potential chances of accidents. In this study, two different designs are proposed in order to prevent snow accretion on the lenses of AVs via air flow across the lens surface. In both designs, lenses made of plain glass and superhydrophobic coated glass surfaces are tested. While some researchers have shown promise of water repellency on superhydrophobic surfaces, more snow accretion is observed on the superhydrophobic surfaces, when compared to the plain glass lenses.

Lean operating natural gas heavy duty applications have advantages in terms of lower CO2 and PM compared to Diesel applications. This makes operating heavy duty applications on natural gas attractive and currently, they do not have to implement an exhaust particulate filter. However, the challenge is controlling methane emissions over a range of vehicle operating conditions. Methane is extremely stable and light off occurs at temperatures above 400 °C, with high efficiency occurring >500 °C and requires high precious metal loaded catalysts in the range of 150 - 200 g/ft3. Under stoichiometric conditions, 500 °C can be met in many engine operating points however, for lean operating applications, the exhaust temperature can be significantly lower than 500 °C posing a significant challenge for exhaust catalytic CH4 control. This paper will discuss synthetic gas reactor study results using ozone in the feed gas to perform low temperature methane control.

This article presents an approach for comparing alternative repairable systems and calculating the value of information obtained by testing a specified number of such systems. More specifically, an approach is presented to determine the value of information that comes from field testing a specified number of systems in order to appropriately estimate the reliability metric associated with each of the respective repairable systems. Here the reliability of a repairable system will be measured by its failure rate. In support of the decision-making effort, the failure rate is translated into an expected utility based on a utility curve that represents the risk tolerance of the decision-maker. The algorithm calculates the change of the expected value of the decision with the sample size. The change in the value of the decision represents the value of information obtained from testing.

The Magma engine concept is characterised by a high compression ratio, central injector combustion system employed in a downsized direct-injection gasoline engine. An advanced boosting system and Miller cycle intake-valve closing strategies are used to control combustion knock while maintaining specific performance. A key feature of the Magma concept is the use of high CR without compromise to mainstream full-load performance levels. This paper focuses on development of the Magma combustion system using a single-cylinder engine, including valve event, air motion and injection strategies. Key findings are that Early Intake Valve Closing (EIVC) is effective both in mitigating knock and improving fuel consumption. A Net Indicated Mean Effective Pressure (NIMEP) equivalent to 23.6 bar Brake Mean Effective Pressure (BMEP) on a multi-cylinder engine has been achieved with a geometric compression ratio of 13:1.

Design optimization occurs through a series of decisions that are a standard part of the product development process. Decisions are made anywhere from concept selection to the design of the assembly and manufacturing processes. The effectiveness of these decisions is based on the information available to the decision maker. Decision analysis provides a structured approach for quantifying the value of information that may be provided to the decision maker. This paper presents a process for determining the value of information that can be gained by evaluating linearly correlated design alternatives. A unique approach to the application of Bayesian Inference is used to provide simulated estimates in the expected utility with increasing observations sizes. The results provide insight into the optimum observation size that maximizes the expected utility when assessing correlated decision alternatives.

An experimental study was conducted to evaluate the variable amplitude fatigue behavior of a neat polymer (polypropylene impact co-polymer) and a polymer composite made of polybutylene terephthalate (PBT) with 30 wt% short glass fibers. Fatigue tests were conducted on un-notched and notched specimens at room temperatures. Plate-type specimens were prepared in the transverse direction with respect to the injection mold flow direction and a circular hole was drilled in the center of notched specimens. Two-step loadings (high-low and low-high) tests at two damage ratio of 0.2 and 0.5 at stress ratios of R = 0.1 and -1 were conducted to investigate load sequence effects and prediction accuracy of the linear damage rule. Different behaviors were observed for unreinforced and short glass fiber reinforced polymers under the two-step loading tests.

Conventional car manufacturing is extremely capital and energy-intensive. Due to these limitations, major auto manufacturers produce very similar, if not virtually identical, vehicles at very large volumes. This limits potential customization for different users and acts as a barrier to entry for new companies or production techniques. Better understanding of the barriers for low volume production and possible solutions with innovative production techniques is crucial for making low volume vehicles viable and accelerating the adoption of new production techniques and lightweight materials into the competitive marketplace. Additive manufacturing can enable innovative design with minimal capital investment in tooling and hence should be ideal for low and perhaps high volume parts. For this reason, it was desired to evaluate potential opportunities in manufacturing automotive parts with additive techniques.

OEMs are investigating opportunities to reduce vehicle mass, driven by a need to meet upcoming CAFE targets, increase the range and reduce battery size of EVs. A number of lightweight materials including high strength steels, aluminum alloys, plastics and composites are now in production. To facilitate development of corporate R&D and commercialization plans for new materials, it is beneficial to understand the current manufacturing costs for production components, and their impact on piece price at different volumes. This paper investigates design and cost impact of light-weighting with respect to front door and floor assembly of Toyota Corolla and BMW i3. Toyota Corolla has a traditional steel body and is sold in high volumes while BMW i3 has relatively low annual sales and is primarily made of composite, aluminum and plastic parts.

An experimental study was conducted to evaluate the effect of water absorption on tensile and fatigue behaviors of an impact-modified short glass fiber polyamide-6 and a short glass fiber polybutylene terephthalate. Specimens were prepared in the longitudinal and transverse directions with respect to the injection mold flow direction and immersed in water. Kinetics of water absorption was studied and found to follow the Fick's law. Tensile tests were performed at room temperature with specimens in the longitudinal and transverse directions and with various degrees of water absorption. Mathematical relations were developed to represent tensile properties as a function of water content. Load-controlled tension-tension fatigue tests were conducted in both longitudinal and transverse directions and correlations between tensile and fatigue strengths were obtained. Specimen fracture surfaces were also microscopically studied and mechanisms of tensile and fatigue failures were identified.

With improvements in casting technology, cast iron can be an alternative to steel in some applications due to its similar strength. One objective of this study was to analyze cast iron data obtained from the literature and evaluate predictive correlations between its tensile, microstructural, and fatigue properties. Reasonably good correlation of tensile strength and yield strength were found with hardness. However, fatigue strength could not be correlated with hardness or tensile properties. Another objective of this study was to evaluate tensile and compressive means stress effects on fatigue behavior of 120-90-02 ductile cast iron experimentally, as well as analytically by using predictive models. Mean stress levels were chosen such that R ratios in load-controlled tests were −7, −3, −1, 0, 1/3, 0.5, and 0.75. Modified Goodman, Smith-Watson-Topper, FKM and the Fatemi-Socie mean stress parameters were used to account for the mean stress effect on fatigue life.

Intake and exhaust system development is an important step in automotive design. The intake system must allow sufficient air to flow into the engine, and the exhaust system must allow exhaust gases to depart at the rear of the vehicle, without excessive pressure loss. These systems must also attenuate the acoustic pressure pulsations generated by the engine, such that the noise emitted from the intake and exhaust orifices is constrained within reasonable limits, and exhibits a sound quality in keeping with the brand and vehicle image. Pressure loss and orifice noise tend to be in conflict, so an appropriate trade-off must be sought. Simulation of both parameters allows intake and exhaust systems to be designed effectively, quickly, cheaply and promptly. Linear simulation approaches have been widely used for intake and exhaust acoustic prediction for many decades.

Inflatable space structures can have lower launching cost and larger habitat volume than their conventional rigid counterparts. These structures are made of composite laminates, and they are flexible when folded and partially inflated. They contain light-activated resins, and can be cured with the sun light after being inflated in space. A spacecraft can burst due to cracks caused by meteor showers or debris. Therefore, it is critical to identify the important fracture failure modes, and assess their probability. This information will help a designer minimize the risk of failure and keep the mass and cost low. This paper presents a probabilistic approach for finding the required thickness of an inflatable habitat shell for a prescribed reliability level, and demonstrates the superiority of probabilistic design to its deterministic counterpart.

An investigation has been carried out to examine the influence of up to 300 MPa injection pressure on engine performance and emissions. Experiments were performed on a 4 cylinder, 4 valve / cylinder, 4.5 liter John Deere diesel engine using the Ricardo Twin Vortex Combustion System (TVCS). The study was conducted by varying the injection pressure, Start of Injection (SOI), Variable Geometry Turbine (VGT) vane position and a wide range of EGR rates covering engine out NOx levels between 0.3 g/kWh to 2.5 g/kWh. A structured Design of Experiment approach was used to set up the experiments, develop empirical models and predict the optimum results for a range of different scenarios. Substantial fuel consumption benefits were found at the lowest NOx levels using 300 MPa injection pressure. At higher NOx levels the impact was nonexistent. In a separate investigation a Cambustion DMS-500 fast particle spectrometer, was used to sample and analyze the exhaust gas.

Importance Sampling is a popular method for reliability assessment. Although it is significantly more efficient than standard Monte Carlo simulation if a suitable sampling distribution is used, in many design problems it is too expensive. The authors have previously proposed a method to manage the computational cost in standard Monte Carlo simulation that views design as a choice among alternatives with uncertain reliabilities. Information from simulation has value only if it helps the designer make a better choice among the alternatives. This paper extends their method to Importance Sampling. First, the designer estimates the prior probability density functions of the reliabilities of the alternative designs and calculates the expected utility of the choice of the best design. Subsequently, the designer estimates the likelihood function of the probability of failure by performing an initial simulation with Importance Sampling.

Future fuel economy targets represent a significant challenge to the automotive industry. While a range of technologies are in research and development to address this challenge, they all bring additional cost and complexity to future products. The most cost effective solutions are likely to be combinations of technologies that in isolation might have limited advantages but in a systems approach can offer complementary benefits. This presentation describes work carried out at Ricardo to explore Intelligent Electrification and the use of Stratified Charge Lean Combustion in a spark ignition engine. This includes a next generation Spray Guided Direct Injection SI engine combustion system operating robustly with highly stratified dilute mixtures and capable of close to 40% thermal efficiency with very low engine-out NOx emissions.

The U.S. Environmental Protection Agency, U.S. Department of Transportation's National Highway and Traffic Safety Administration, and the California Air Resources Board have recently released proposed new regulations for greenhouse gas emissions and fuel economy for light-duty vehicles and trucks in model years 2017-2025. These proposed regulations intend to significantly reduce greenhouse gas emissions and increase fleet fuel economy from current levels. At the fleet level, these rules the proposed regulations represent a 50% reduction in greenhouse gas emissions by new vehicles in 2025 compared to current fleet levels. At the same time, global growth, especially in developing economies, should continue to drive demand for crude oil and may lead to further fuel price increases. Both of these trends will therefore require light duty vehicles (LDV) to significantly improve their greenhouse gas emissions over the next 5-15 years to meet regulatory requirements and customer demand.

Due to the recent drive to reduce CO₂ emissions, the turbocharged direct injection spark ignition (turbo DISI) gasoline engine has become increasingly popular. In addition, future turbo DISI engines could incorporate a form of charge dilution (e.g., lean operation or external EGR) to further increase fuel efficiency. Thus, the conditions experienced by the fuel before and during combustion are and will continue to be different from those experienced in naturally aspirated SI engines. This work investigates the effects of fuel properties on a modern and prototype turbo DISI engine, with particular focus on the octane appetite: How relevant are RON and MON in predicting a fuel's anti-knock performance in these modern/future engines? It is found that fuels with high RON and low MON values perform the best, suggesting the current MON requirements in fuel specifications could actually be detrimental.

Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) networks within the Intelligent Transportation System (ITS) lead to safety and mobility improvements in vehicle road traffic. This paper presents case studies that support the realization of the ITS architecture as an evolutionary process, beginning with driver information systems for enhancing feedback to the users, semi-autonomous control systems for improved vehicle system management, and fully autonomous control for improving vehicle cooperation and management. The paper will also demonstrate how the automotive, telecom, and data and service providers are working together to develop new ITS technologies.

A complete probabilistic model of uncertainty in probabilistic analysis and design problems is the joint probability distribution of the random variables. Often, it is impractical to estimate this joint probability distribution because the mechanism of the dependence of the variables is not completely understood. This paper proposes modeling dependence by using copulas and demonstrates their representational power. It also compares this representation with a Monte-Carlo simulation using dispersive sampling.

The Ethanol-Boosted Direct Injection (EBDI) demonstrator engine is a collaborative project led by Ricardo targeted at reducing the fuel consumption of a spark-ignited engine. This paper describes the design challenges to upgrade an existing engine architecture and the synergistic use of a combination of technologies that allows a significant reduction in fuel consumption and CO₂ emissions. Features include an extremely reduced displacement for the target vehicle, 180 bar cylinder pressure capability, cooled exhaust gas recirculation, advanced boosting concepts and direct injection. Precise harmonization of these individual technologies and control algorithms provide optimized operation on gasoline of varying octane and ethanol content.