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Sector mesh modeling is the dominant computational approach for combustion system design optimization. The aim of this work is to quantify the errors descending from the sector mesh approach through three geometric modeling approaches to an optical diesel engine. A full engine geometry mesh is created, including valves and intake and exhaust ports and runners, and a full-cycle flow simulation is performed until fired TDC. Next, an axisymmetric sector cylinder mesh is initialized with homogeneous bulk in-cylinder initial conditions initialized from the full-cycle simulation. Finally, a 360-degree azimuthal mesh of the cylinder is initialized with flow and thermodynamics fields at IVC mapped from the full engine geometry using a conservative interpolation approach. A study of the in-cylinder flow features until TDC showed that the geometric features on the cylinder head (valve tilt and protrusion into the combustion chamber, valve recesses) have a large impact on flow complexity.

The Composite Lightweight Automotive Suspension System is a composite rear suspension knuckle/tieblade consisting of UD prepreg (epoxy resin), SMC (vinylester resin) carbon fibre and a steel insert to reduce the weight of the component by 35% and reduce Co2. The compression moulding manufacturing process and CAE optimisation are unique and ground-breaking for this product and are designed to allow high volume manufacture of approx. 30,000 vehicles per year. The manufacturing techniques employed allow for multi-material construction within a five minute cycle time to make the process viable for volume manufacture. The complexities of the design lie in the areas of manufacturing, CAE prediction and highly specialised design methods. It is a well-known fact that the performance of a composite part is primarily determined by the way it is manufactured.

In this paper, a soft computing approach to a model-free vehicle stability control (VSC) algorithm is presented. The objective is to create a fuzzy inference system (FIS) that is robust enough to operate in a multitude of vehicle conditions (load, tire wear, alignment), and road conditions while at the same time providing optimal vehicle stability by detecting and minimizing loss of traction. In this approach, an adaptive neuro-fuzzy inference system (ANFIS) is generated using previously collected data to train and optimize the performance of the fuzzy logic VSC algorithm. This paper outlines the FIS detection algorithm and its benefits over a model-based approach. The performance of the FIS-based VSC is evaluated via a co-simulation of MATLAB/Simulink and CarSim model of the vehicle under various road and load conditions. The results showed that the proposed algorithm is capable of accurately indicating unstable vehicle behavior for two different types of vehicles (SUV and Sedan).

A new turbocharged 60° 2.7L 4V-V6 gasoline engine has been developed by Ford Motor Company for both pickup trucks and car applications. This engine was code named “Nano” due to its compact size; it features a 4-valves DOHC valvetrain, a CGI cylinder block, an Aluminum ladder, an integrated exhaust manifold and twin turbochargers. The goal of this engine is to deliver 120HP/L, ULEV70 emission, fuel efficiency improvements and leadership level NVH. This paper describes the upfront design and optimization process used for the NVH development of this engine. It showcases the use of analytical tools used to define the critical design features and discusses the NVH performance relative to competitive benchmarks.

The higher cylinder peak pressure and pressure rise rate of modern diesel and gasoline fueled engines tend to increase combustion noise while customers demand lower noise. The multiple degrees of freedom in engine control and calibration mean there is more scope to influence combustion noise but this must first be measured before it can be balanced with other attributes. An efficient means to realize this is to calculate combustion noise from the in-cylinder pressure measurements that are routinely acquired as part of the engine development process. This publication reviews the techniques required to ensure accurate and precise combustion noise measurements. First, the dynamic range must be maximized by using an analogue to digital converter with sufficient number of bits and selecting an appropriate range in the test equipment.

In the thermal expansion valve (TXV) refrigerant system, transient high-pitched whistle around 6.18 kHz is often perceived following air-conditioning (A/C) compressor engagements when driving at higher vehicle speed or during vehicle acceleration, especially when system equipped with the high-efficiency compressor or variable displacement compressor. The objectives of this paper are to conduct the noise source identification, investigate the key factors affecting the whistle excitation, and understand the mechanism of the whistle generation. The mechanism is hypothesized that the whistle is generated from the flow/acoustic excitation of the turbulent flow past the shallow cavity, reinforced by the acoustic/structural coupling between the tube structural and the transverse acoustic modes, and then transmitted to evaporator. To verify the mechanism, the transverse acoustic mode frequency is calculated and it is coincided to the one from measurement.

The effect of aerodynamically induced pre-swirl on the acoustic and performance characteristics of an automotive centrifugal compressor is studied experimentally on a steady-flow turbocharger facility. Accompanying flow separation, broadband noise is generated as the flow rate of the compressor is reduced and the incidence angle of the flow relative to the leading edge of the inducer blades increases. By incorporating an air jet upstream of the inducer, a tangential (swirl) component of velocity is added to the incoming flow, which improves the incidence angle particularly at low to mid-flow rates. Experimental data for a configuration with a swirl jet is then compared to a baseline with no swirl. The induced jet is shown to improve the surge line over the baseline configuration at all rotational speeds examined, while restricting the maximum flow rate. At high flow rates, the swirl jet increases the compressor inlet noise levels over a wide frequency range.

Refrigerant flow-induced gurgling noise is perceived in automotive refrigerant systems. In this study, the condition of the gurgling generation is investigated at the vehicle level and the fundamental root cause is identified as the two-phase refrigerant flow entering the TXV for system equipped with variable displacement compressors. By conducting literature reviews, the acoustic characteristics of the flow patterns and the parameters affecting the flow regimes in horizontal and vertical tubes are summarized. Then the gurgling mechanism is explained as the intermittent flow is developed at the evaporator inlet. In the end, the improved and feasible design for avoiding the intermittent flow (slug, plug or churn flow) or minimizing its formation is proposed and verified in refrigerant subsystem (RSS) level. Finally, the guidelines for the attenuation and suppression of the gurgle are provided.

This paper presents the methodology of predicting vehicle level automotive air-handling system air-rush noise sound quality (SQ) using the sub-system level measurement. Measurement setup in both vehicle level and sub-system levels are described. To assess the air-rush noise SQ, both 1/3 octave band sound pressure level (SPL) and overall Zwicker's loudness are used. The “Sound Quality Correlation Functions (SQCF)” between sub-system level and vehicle level are developed for the specified climate control modes and vehicle segment defined by J.D. Power & Associates, while the Zwicker's loudness is calculated using the un-weighted predicted 1/3 octave band SPL. The predicting models are demonstrated in very good agreement with the measured data. The methodology is applied to the development of sub-system SQ requirement for upfront delivery of the optimum design to meet global customer satisfaction

OEMs are racing to develop lightweight vehicles as government regulations now mandate automakers to nearly double the average fuel economy of new cars and trucks by 2025. Lightweight materials such as aluminum, magnesium and carbon fiber composites are being used as structural members in vehicle body and suspension components. The reduction in weight in structural panels increases noise transmission into the passenger compartment. This poses a great challenge in vehicle sound package development since simply increasing weight in sound package components to reduce interior noise is no longer an option [1]. This paper discusses weight saving approaches to reduce noise level at the sources, noise transmission paths, and transmitted noise into the passenger compartment. Lightweight sound package materials are introduced to treat and reduce airborne noise transmission into multi-material lightweight body structure.

Hands-free phone use is the most utilized use case for vehicles equipped with infotainment systems with external microphones that support connection to phones and implement speech recognition. Critically then, achieving hands-free phone call quality in a vehicle is problematic due to the extremely noisy nature of the vehicle environment. Noise generated by wind, mechanical and structural, tire to road, passengers, engine/exhaust, HVAC air pressure and flow are all significant contributors and sources of noise. Other factors influencing the quality of the phone call include microphone placement, cabin acoustics, seat position of the talker, noise reduction of the hands-free system, etc. This paper describes the work done to develop procedures and metrics to quantify the effects that influence the hands-free phone call quality.

The performance of an organic Rankine cycle (ORC) that recovers heat from the exhaust of a heavy-duty diesel engine was simulated. The work was an extension of a prior study that simulated the performance of an experimental ORC system developed and tested at Oak Ridge National laboratory (ORNL). The experimental data were used to set model parameters and validate the results of that simulation. For the current study the model was adapted to consider a 15 liter turbocharged engine versus the original 1.9 liter light-duty automotive turbodiesel studied by ORNL. Exhaust flow rate and temperature data for the heavy-duty engine were obtained from Southwest Research Institute (SwRI) for a range of steady-state engine speeds and loads without EGR. Because of the considerably higher exhaust gas flow rates of the heavy-duty engine, relative to the engine tested by ORNL, a different heat exchanger type was considered in order to keep exhaust pressure drop within practical bounds.

As the world's largest auto producer and consumer, China is both the most promising and complex market given the country's rapid economic growth, huge population, and many regional and segment preference differences. This research is aimed at developing data-driven demand models for customer preference analysis and prediction under a competitive market environment. Regional analysis is first used to understand the impact of geographical factors on customer preference. After a comprehensive data exploration, a customer-level mixed logit model is built to shed light on fast-growing vehicle segments in the Chinese auto market. By combining the data of vehicle purchase, consideration, and past choice, cross-shopping behaviors and brand influence are explicitly modeled in addition to the impact of customer demographics, usage behaviors, and attributes of vehicles.

Magnesium die-cast alloys are known to have a layered microstructure composed of: (1) An outer skin layer characterized by a refined microstructure that is relatively defect-free; and (2) A “core” (interior) layer with a coarser microstructure having a higher concentration of features such as porosity and externally solidified grains (ESGs). Because of the difference in microstructural features, it has been long suggested that removal of the surface layer by machining could result in reduced mechanical properties in tested tensile samples. To examine the influence of the skin layer on the mechanical properties, a series of round tensile bars of varying diameters were die-cast in a specially-designed mold using the AM60 Mg alloy. A select number of the samples were machined to different final diameters. Subsequently, all of the samples (as-cast as well as machined) were tested in tension.

Automotive structural parts made out of Advanced High Strength Steel (AHSS) are often produced in a multistage forming process using progressive dies or transfer dies. During each forming stage the steel is subjected to work hardening, which affects the formability of the steel in the subsequent forming operation. Edge flanging and in-plane edge stretching operations are forming modes that are typically employed in the last stage of the multistage forming processes. In this study, the multistage forming process was simulated by pre-straining a DP980 steel in a biaxial strain path with various strain levels followed by edge flanging and in-plane edge stretching. The biaxial prestrains were obtained using the Marciniak stretch test and edge flanging and in-plane edge stretching were accomplished by the hole expansion test using a flat punch and a conical punch, respectively.

Due to magnesium alloy's poor weldability, other joining techniques such as laser assisted self-piercing rivet (LSPR) are used for joining magnesium alloys. This research investigates the fatigue performance of LSPR for magnesium alloys including AZ31 and AM60. Tensile-shear and coach peel specimens for AZ31 and AM60 were fabricated and tested for understanding joint fatigue performance. A structural stress - life (S-N) method was used to develop the fatigue parameters from load-life test results. In order to validate this approach, test results from multijoint specimens were compared with the predicted fatigue results of these specimens using the structural stress method. The fatigue results predicted using the structural stress method correlate well with the test results.

Motivated by a combination of increasing consumer demand for fuel efficient vehicles, more stringent greenhouse gas, and anticipated future Corporate Average Fuel Economy (CAFE) standards, automotive manufacturers are working to innovate in all areas of vehicle design to improve fuel efficiency. In addition to improving aerodynamics, enhancing internal combustion engines and transmission technologies, and developing alternative fuel vehicles, reducing vehicle weight by using lighter materials and/or higher strength materials has been identified as one of the strategies in future vehicle development. Weight reduction in vehicle components, subsystems and systems not only reduces the energy needed to overcome inertia forces but also triggers additional mass reduction elsewhere and enables mass reduction in full vehicle levels.

Exhaust pressures (P3) are hard parameters to measure and can be readily estimated, the cost of the sensors and the temperature in the exhaust system makes the implementation of an exhaust pressure sensor in a vehicle control system a costly endeavor. The contention with measured P3 is the accuracy required for proper engine and vehicle control can sometimes exceed the accuracy specification of market available sensors and existing models. A turbine inlet exhaust pressure observer model based on isentropic expansion and heat transfer across a turbocharger turbine was developed and investigated in this paper. The model uses 4 main components; an open loop P3 orifice flow model, a model of isentropic expansion across the turbine, a turbine and pipe heat transfer models and an integrator with the deviation in the downstream turbine outlet parameter.

This paper presents a numerical study of trace knocking combustion of ethanol/gasoline blends in a modern, single cylinder SI engine. Results are compared to experimental data from a prior, published work [1]. The engine is modeled using GT-Power and a two-zone combustion model containing detailed kinetic models. The two zone model uses a gasoline surrogate model [2] combined with a sub-model for nitric oxide (NO) [3] to simulate end-gas autoignition. Upstream, pre-vaporized fuel injection (UFI) and direct injection (DI) are modeled and compared to characterize ethanol's low autoignition reactivity and high charge cooling effects. Three ethanol/gasoline blends are studied: E0, E20, and E50. The modeled and experimental results demonstrate some systematic differences in the spark timing for trace knock across all three fuels, but the relative trends with engine load and ethanol content are consistent. Possible reasons causing the differences are discussed.

Underhood thermal management is a challenging problem in automotive industry. In order to make sure that vehicle works efficiently, there should be enough airflow through the cooling system so that the consequent heat rejection would be adequate. In idle condition the required air flow is provided by the cooling fan so a better understanding and an accurate predictive CAE tool for fan is very beneficial. Computational Fluid Dynamics (CFD) has been extensively used in predicting aerodynamic performance of automotive components. In the current work, the airflow performance of a fan, shroud and radiator assembly was simulated using Moving Reference Method (MRF) method. Although it is less expensive than Sliding Mesh (SM) method, the CAE results compare well with the test data. The simulation was carried out over 10+ different shrouds and the effect of geometrical parameters on airflow was investigated.