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Automotive engines are regularly utilized in the material handling market where LPG is often the primary fuel used. When compared to gasoline, the use of gaseous fuels (LPG and CNG) as well as alcohol based fuels, often result in significant increases in valve seat insert (VSI) and valve face wear. This phenomenon is widely recognized and the engine manufacturer is tasked to identify and incorporate appropriate valvetrain material and design features that can meet the ever increasing life expectations of the end-user. Alternate materials are often developed based on laboratory testing – testing that may not represent real world usage. The ultimate goal of the product engineer is to utilize accelerated lab test procedures that can be correlated to field life and field failure mechanisms, and then select appropriate materials/design features that meet the targeted life requirements.

An operational scheme with fuel-lean and exhaust gas dilution in spark-ignited engines increases thermal efficiency and decreases NOx emission, while these operations inherently induce combustion instability and thus large cycle-to-cycle variation in engine. In order to stabilize combustion variations, the development of an advanced ignition system is becoming critical. To quantify the impact of spark-ignition discharge, ignitability tests were conducted in an optically accessible combustion vessel to characterize the flame kernel development of lean methane-air mixture with CO₂ simulating exhaust diluent. A shrouded fan was used to generate turbulence in the vicinity of J-gap spark plug and a Variable Output Ignition System (VOIS) capable of producing a varied set of spark discharge patterns was developed and used as an ignition source. The main feature of the VOIS is to vary the secondary current during glow discharge including naturally decaying and truncated with multiple strikes.

The human thermal comfort, which has been a subject of extensive research, is a principal objective of the automotive climate control system. Applying the results of research studies to the practical problems require quantitative information of the thermal environment in the passenger compartment of a vehicle. The exposure to solar radiation is known to alter the thermal environment in the passenger compartment. A photovoltaic-cell based sensor is commonly used in the automotive climate control system to measure the solar radiation exposure of the passenger compartment of a vehicle. The erroneous information from a sensor however can cause thermal discomfort to the occupants. The erroneous measurement can be due to physical or environmental parameters. Shading of a solar sensor due to the opaque vehicle body elements is one such environmental parameter that is known to give incorrect measurement.

Computer programs and models are playing an increasing role in simulating vehicle crashworthiness, dynamic, and fuel efficiency. To maximize the effectiveness of these models, the validity and predictive capabilities of these models need to be assessed quantitatively. For a successful implementation of Computer Aided Engineering (CAE) models as an integrated part of the current vehicle development process, it is necessary to develop objective validation metric that has the desirable metric properties to quantify the discrepancy between multiple tests and simulation results. However, most of the outputs of dynamic systems are multiple functional responses, such as time history series. This calls for the development of an objective metric that can evaluate the differences of the multiple time histories as well as the key features under uncertainty.

A copula-based approach for model bias characterization was previously proposed [18] aiming at improving prediction accuracy compared to other model characterization approaches such as regression and Gaussian Process. This paper proposes an adaptive copula-based approach for model bias identification to enhance the available methodology. The main idea is to use cluster analysis to preprocess data, then apply the copula-based approach using information from each cluster. The final prediction accumulates predictions obtained from each cluster. Two case studies will be used to demonstrate the superiority of the adaptive copula-based approach over its predecessor.

To date, model validation metric is prominently designed for non-dynamic model responses. Though metrics for dynamic responses are also available, they are specifically designed for the vehicle impact application and uncertainties are not considered in the metric. This paper proposes the validation metric for general dynamic system responses under uncertainty. The metric makes use of the popular U-pooling approach and extends it for dynamic responses. Furthermore, shape deviation metric was proposed to be included in the validation metric with the capability of considering multiple dynamic test data. One vehicle impact model is presented to demonstrate the proposed validation metric.

Simulation based design optimization has become the common practice in automotive product development. Increasing computer models are developed to simulate various dynamic systems. Before applying these models for product development, model validation needs to be conducted to assess their validity. In model validation, for the purpose of obtaining results successfully, it is vital to select or develop appropriate metrics for specific applications. For dynamic systems, one of the key obstacles of model validation is that most of the responses are functional, such as time history curves. This calls for the development of a metric that can evaluate the differences in terms of phase shift, magnitude and shape, which requires information from both time and frequency domain. And by representing time histories in frequency domain, more intuitive information can be obtained, such as magnitude-frequency and phase-frequency characteristics.

Design optimization methods are commonly used for weight reduction subjecting to multiple constraints in automotive industry. One of the major challenges remained is to deal with a large number of design variables for large-scale design optimization problems effectively. In this paper, a new approach based on fuzzy rough set is proposed to address this issue. The concept of rough set theory is to deal with redundant information and seek for a reduced design variable set. The proposed method first exploits fuzzy rough set to screen out the insignificant or redundant design variables with regard to the output functions, then uses the reduced design variable set for design optimization. A vehicle body structure is used to demonstrate the effectiveness of the proposed method and compare with a traditional weighted sensitivity based main effect approach.

One of the major challenges in multiobjective, multidisciplinary design optimization (MDO) is the long computational time required in evaluating the new designs' performances. To shorten the cycle time of product design, a data mining-based strategy is developed to improve the efficiency of heuristic optimization algorithms. Based on the historical information of the optimization process, clustering and classification techniques are employed to identify and eliminate the low quality and repetitive designs before operating the time-consuming design evaluations. The proposed method improves design performances within the same computation budget. Two case studies, one mathematical benchmark problem and one vehicle side impact design problem, are conducted as demonstration.

Ultrasonic fatigue tests (testing frequency around 20 kHz) have been conducted on four different cast aluminum alloys each with a distinct composition, heat treatment, and microstructure. Tests were performed in dry air, laboratory air and submerged in water. For some alloys, the ultrasonic fatigue lives were dramatically affected by the environment humidity. The effects of different factors like material composition, yield strength, secondary dendrite arm spacing and porosity were investigated; it was concluded that the material strength may be the key factor influencing the environmental humidity effect in ultrasonic fatigue testing. Further investigation on the effect of chemical composition, especially copper content, is needed.

The Chevrolet Volt is an electric vehicle with extended-range that is capable of operation on battery power alone, and on engine power after depletion of the battery charge. First generation Chevrolet Volts were driven over half a billion miles in North America from October 2013 through September 2014, 74% of which were all-electric [1, 12]. For 2016, GM has developed the second-generation of the Volt vehicle and “Voltec” propulsion system. By significantly re-engineering the traction power inverter module (TPIM) for the second-generation Chevrolet Volt extended-range electric vehicle (EREV), we were able to meet all performance targets while maintaining extremely high reliability and environmental robustness. The power switch was re-designed to achieve efficiency targets and meet thermal challenges. A novel cooling approach enables high power density while maintaining a very high overall conversion efficiency.

Connectivity has become an essential need for daily device users. With the car projected to be the “ultimate mobile device”, connectivity modules will eventually be mainstream in every car. Network providers are expanding their infrastructure and technology to accommodate the connected cars. Besides making voice and emergency calls the connected car will be sharing data with telematics service providers, back end systems and other vehicles. This trend will increase vehicle modules, complexity, entry points and vulnerabilities. This paper will present the current connected car architectures. The paper will present current architectural issues of the connected car and its vulnerabilities. The paper will present a new proposed architecture for the future connected car that enhances efficiency and security.

Recently, a new technology, termed 2-way SCR/DPF by the authors, has been developed by several catalyst suppliers for diesel exhaust emission control. Unlike a conventional emission control system consisting of an SCR catalyst followed by a catalyzed DPF, a wall-flow filter is coated with SCR catalysts for controlling both NOx and PM emissions in a single catalytic converter, thus reducing the overall system volume and cost. In this work, the potential and limitations of the Cu/Zeolite-based SCR/DPF technology for meeting future emission standards were evaluated on a pick-up truck equipped with a prototype light-duty diesel engine.

Sequel is the third vehicle in GM's Reinvention of the Automobile and is the first zero emissions passenger vehicle to drive more than 300 miles on public roads without refueling or recharging. It is purpose-built around the hydrogen storage and fuel cell systems and uses the skateboard principle introduced in the Autonomy vision concept and the Hy-wire proof-of-concept vehicles. Sequel's aluminum structure, Flexray controlled chassis-by-wire systems and AWD system comprising a single front electric motor and two rear wheel motors make it, perhaps, the most technically advanced automobile ever built. The paper describes the vehicle's design and performance characteristics.

A fully flexible valve actuation (FFVA) system was developed for a single cylinder research engine to investigate high efficiency clean combustion (HECC) in a diesel engine. The main objectives of the study were to examine the emissions, performance, and combustion characteristics of the engine using late intake valve closing (LIVC) to determine the benefits and limitations of this strategy to meet Tier 2 Bin 5 NOx requirements without after-treatment. The most significant benefit of LIVC is a reduction in particulates due to the longer ignition delay time and a subsequent reduction in local fuel rich combustion zones. More than a 95% reduction in particulates was observed at some operating conditions. Combustion noise was also reduced at low and medium loads due to slower heat release. Although it is difficult to assess the fuel economy benefits of LIVC using a single cylinder engine, LIVC shows the potential to improve the fuel economy through several approaches.

This paper suggests a scientific approach to designing conservative tests based on computer simulation of the influence of the sources of variations. The idea is to design the conservative test so that, even in the presence of variation, there is a high probability that a random test will have a better result than the conservative test. Therefore, if the conservative test meets the requirement, one has a scientific reason to believe that any random test would have a high probability of meeting it. This new approach is illustrated for FMVSS301 80 kph 70% rear offset deformable barrier impact.

Over the past decade, the automotive industry has seen a rapid decrease in product development cycle time and an ever increasing need by original equipment manufacturers and their suppliers to differentiate themselves in the marketplace. This differentiation is increasingly accomplished by introducing new technology while continually improving the performance of existing automotive systems. In the area of automotive brake system design, and, in particular, the brake apply subsystem, an increased focus has been placed on the development of electrohydraulic apply systems and brake-by-wire systems to replace traditional pneumatic and hydraulic systems. Nevertheless, the traditional brake apply systems, especially vacuum-based or pneumatic systems, will continue to represent the majority of brake apply system production volume into the foreseeable future, which underscores the need to improve the performance and application of these traditional systems in passenger cars and light-trucks.

With increasingly stringent emissions regulations and concurrent requirements for enhanced engine thermal efficiency, a comprehensive characterization of the automotive gasoline fuel spray has become essential. The acquisition of accurate and repeatable spray data is even more critical when a combustion strategy such as gasoline direct injection is to be utilized. Without industry-wide standardization of testing procedures, large variablilities have been experienced in attempts to verify the claimed spray performance values for the Sauter mean diameter, Dv90, tip penetration and cone angle of many types of fuel sprays. A new SAE Recommended Practice document, J2715, has been developed by the SAE Gasoline Fuel Injection Standards Committee (GFISC) and is now available for the measurement and characterization of the fuel sprays from both gasoline direct injection and port fuel injection injectors.

A key element of General Motors' Advanced Propulsion Technology Strategy is the electrification of the automobile. The objectives of this strategy are reduced fuel consumption, reduced emissions and increased energy security/diversification. The introduction of hybrid vehicles was one of the first steps as a result of this strategy. To determine future opportunities and direction, an extensive study was completed to better understand the ability of Plug-in Hybrid Electric Vehicles (PHEV) and Extended-Range Electric Vehicles (E-REV) to address societal challenges. The study evaluated real world representative driving datasets to understand actual vehicle usage. Vehicle simulations were conducted to evaluate the merits of PHEV and E-REV configurations. As derivatives of conventional full hybrids, PHEVs have the potential to deliver a significant reduction in petroleum usage.

The auto industry has had decades of experience with designing safe vehicles. The introduction of highly integrated features brings new challenges that require innovative adaptations of existing safety methodologies and perhaps even some completely new concepts. In this paper, we describe some of the new challenges that will be faced by all OEMs and suppliers. We also describe a set of generic top-level potential hazards that can be used as a starting point for the Preliminary Hazard Analysis (PHA) of a vehicle software-intensive motion control system. Based on our experience with the safety analysis of a system of this kind, we describe some general categories of hazard causes that are considered for software-intensive systems and can be used systematically in developing the PHA.