Search Results

The benefits of adding variable compression ratio (VCR) capability to a Gasoline Turbocharged Direct Injection (GTDI) has been experimentally explored by AVL to quantify the potential efficiency improvements along with other combustion benefits and challenges. The development process is discussed along with key results showing how the combination of VCR, GDI, external cooled EGR and variable cam phasing was optimized to achieve maximum benefit. The concept demonstrates aggressive downsizing capability with BMEP levels above 40 bar BMEP with a two-stage turbocharging system on 95 RON gasoline. The iso-BSFC sweet spot was also improved with reduced BSFC over a broader operating range. The issues of knock, low speed pre-ignition, particulates and sensitivity to octane level and ambient temperature conditions were also investigated and are discussed. Engine level results are shown translated into predicted NEDU vehicle fuel economy improvements.

Lithium-ion (Li-ion) batteries are becoming widely used high-energy sources and a replacement of the Nickel Metal Hydride batteries in electric vehicles (EV), hybrid electric vehicles (HEV) and plug-in hybrid electric vehicles (PHEV). Because of their light weight and high energy density, Li-ion cells can significantly reduce the weight and volume of the battery packs for EVs, HEVs and PHEVs. Some materials in the Li-ion cells have low thermal stabilities and they may become thermally unstable when their working temperature becomes higher than the upper limit of allowed operating temperature range. Thus, the cell working temperature has a significant impact on the life of Li-ion batteries. A proper control of the cell working temperature is crucial to the safety of the battery system and improving the battery life. This paper outlines an approach for the thermal analysis of Li-ion battery cells and modules.

Modern heavy duty Commercial Off The Shelf (COTS) diesel engines represent the state of the art in engine performance and design features, control architecture, and the use of light weight high strength materials. These engines, with appropriate adaptation for operation on military fuels, make excellent choices for defense applications. This paper reviews the selection and modification of a COTS engine suitable for potential defense applications. Considerations for robust operation of the engine on JP8, engine system modifications appropriate for military vehicle emission requirements, reduction of engine system heat rejection, and optimization of engine efficiency will be discussed using example data from converting a 2011 model year COTS engine for defense applications. This work was funded by the Tank Automotive Research, Development and Engineering Center (TARDEC) from Broad Agency Announcement (BAA) Topic 15, awarded in 2009.

In recent years, computer simulations gained an increased role in the design, development, optimization, and calibration of the valve train systems. With the development of non-conventional systems and actuation mechanisms, computer modeling became even more important. Part I of this article presents an overview of the current modeling and simulation methods of conventional valve trains at component and system level. First, the modeling of the valve train kinematics, including cam shape design and optimization, is summarized. Mathematical modeling of the valve spring, hydraulic lash adjuster, oil aeration, bulk modulus, contact stiffness and contact damping in multibody systems are discussed. The benefits and limitations of the different modeling approaches of the valve train dynamics are pointed out. Another important aspect is the valve train tribology.

Gasoline turbocharged direct injection (GTDI) engines, such as EcoBoost™ from Ford, are becoming established as a high value technology solution to improve passenger car and light truck fuel economy. Due to their high specific performance and excellent low-speed torque, improved fuel economy can be realized due to downsizing and downspeeding without sacrificing performance and driveability while meeting the most stringent future emissions standards with an inexpensive three-way catalyst. A logical and synergistic extension of the EcoBoost™ strategy is the use of E85 (approximately 85% ethanol and 15% gasoline) for knock mitigation. Direct injection of E85 is very effective in suppressing knock due to ethanol's high heat of vaporization - which increases the charge cooling benefit of direct injection - and inherently high octane rating. As a result, higher boost levels can be achieved while maintaining optimal combustion phasing giving high thermal efficiency.

The performance of an EGR cooler is influenced significantly by particulate fouling in the cooler. As a result of fouling, a highly porous soot deposit layer is formed in the EGR cooler. This deposit layer not only causes a decrease in the cooler effectiveness but also an increase in the EGR pressure drop over the cooler. Increasing the EGR cooler pressure drop reduces the driving force for the EGR flow under a given differential pressure across the engine. Thus, the EGR cooler fouling has a big impact on the control of the engine-out NO emissions. In this paper, a semi-empirical model is developed for predicting pressure drops of fouled EGR coolers. Based on this model and the particulate fouling model developed previously by the author, the process is analyzed for the pressure drop increase with building up of the soot deposit in an EGR cooler.

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.

Superior NVH performance is a key focus in the development of new powertrains. In recent years, computer simulations have gained an increasing role in the design, development, and optimization of powertrain NVH at component and system levels. This paper presents the results of a study carried out on a 4-cylinder in-line spark-ignition engine with focus on growl noise. Growl is a low frequency noise (300-700 Hz) which is primarily perceived at moderate engine speeds (2000-3000 rpm) and light to moderate throttle tip-ins. For this purpose, a coupled and fully flexible multi-body dynamics model of the powertrain was developed. Structural components were reduced using component mode synthesis and used to determine dynamics loads at various engine speeds and loading conditions. A comparative NVH assessment of various crankshaft designs, engine configurations, and in- cylinder gas pressures was carried out.

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.

Modern diesel systems have come to rely on fuel systems with the capacity for high injection pressures. The benefits of such high pressures include improved tolerance for EGR, reduced emissions and improved performance. Current production fuel systems have typical capacities to 2500 bar, when a decade ago 1800 bar was a typical limit. Following the trend, this paper investigates the effect of rail pressures up to 3000 bar on a 1.5L single cylinder research engine. The injector nozzles tested include two variations in flow rate, the number of holes, and spray cone angle. In addition to fuel rail pressure, the effects of intake swirl, excess-air ratio, EGR, and injection timing are evaluated at speed and load points representative of A100, B100, and C100 test conditions of the U.S. EPA on-highway 13 Mode test cycle.

This study demonstrates the use of pressure sensing technology to predict the crash severity of frontal impacts. It presents an investigation of the pressure change in the front structural elements (bumper, crush cans, rails) during crash events. A series of subsystem tests were conducted in the laboratory that represent a typical frontal crash development series and provided empirical data to support the analysis of the concept. The pressure signal energy at different sensor mounting locations was studied and design concepts were developed for amplifying the pressure signal. In addition, a pressure signal processing methodology was developed that relies on the analysis of the air flow behavior by normalizing and integrating the pressure changes. The processed signal from the pressure sensor is combined with the restraint control module (RCM) signals to define the crash severity, discriminate between the frontal crash modes and deploy the required restraint devices.

Gas Metal Arc Welding (GMAW) is widely employed for joining relatively thick sheet steels in automotive body-in-white structures and frames. The GMAW process is very flexible for various joint geometries and has relatively high welding speed. However, fatigue failures can occur at welded joints subjected to various types of loads. Thus, vehicle design engineers need to understand the fatigue characteristics of welded joints produced by GMAW. Currently, automotive structures employ various advanced high strength steels (AHSS) such as dual-phase (DP) and transformation-induced plasticity (TRIP) steels to produce lighter vehicle structures with improved safety performance and fuel economy, and reduced harmful emissions. Relatively thick gages of AHSS are commonly joined to conventional high strength steels and/or mild steels using GMAW in current body-in-white structures and frames.

The r-value is a very important parameter in the forming simulations of high strength steels, especially for steels with prominent anisotropy. R-values for sheet steels conventionally measured by extensometers were found neither consistent nor accurate due to difficulties in measuring the width strain. In this study, the Digital Image Correlation (DIC) technique was applied to determine r-values in Longitudinal (L), Transverse (T) and Diagonal (D) directions for cold rolled DP980 GI, DP780 GI, DP600 GI and BH250 GI sheet steels. The r-values measured from DIC were validated by finite element analysis (FEA) of a uniaxial tensile test for BH250. The simulation results of the load-displacement for two plasticity models were compared to experimental data, with one being the isotropic yield (von-Mises) and the other being an anisotropic model (Hill-48) using the r-value measured from DIC.

The temperature distribution is studied theoretically in a battery module stacked with 12 high-power Li-ion pouch cells. The module is cooled indirectly with ambient air through aluminum heat-sink plates or cooling plates sandwiched between each pair of cells in the module. Each of the cooling plates has an extended cooling fin exposed in the cooling air channel. The cell temperatures can be controlled by changing the air temperature and/or the heat transfer coefficient on the cooling fin surfaces by regulating the air flow rate. It is found that due to the high thermal conductivity and thermal diffusivity of the cooling plates, heat transfer of the cooling plate governs the cell temperature distribution by spreading the cell heat over the entire cell surface. Influence of thermal from the cooling fins is also simulated.