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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.

Effective control of exhaust emissions from modern diesel engines requires the use of aftertreatment systems. Elevated aftertreatment component temperatures are required for engine-out emissions reductions to acceptable tailpipe limits. Maintaining elevated aftertreatment components temperatures is particularly problematic during prolonged low speed, low load operation of the engine (i.e. idle, creep, stop and go traffic), on account of low engine-outlet temperatures during these operating conditions. Conventional techniques to achieve elevated aftertreatment component temperatures include delayed fuel injections and over-squeezing the turbocharger, both of which result in a significant fuel consumption penalty. Cylinder deactivation (CDA) has been studied as a candidate strategy to maintain favorable aftertreatment temperatures, in a fuel efficient manner, via reduced airflow through the engine.

There is an increased use of elastomers in the automotive industry for sealing, noise isolation, load dampening, insulation, etc., because of their key properties of elasticity and resilience. Elastomers are used in supercharger application for dampening the torsional fluctuation from the engine, to reduce noise issues. Finite element modeling of elastomers is challenging because of its non-linear behavior in different loading directions. It also undergoes very large elemental deformation (~up to 200%), which results in additional complexities in getting numerical convergence. Finally, it also exhibits viscous and elastic behavior simultaneously (viscoelastic effect) and it undergoes softening with progressive cyclic loading (Mullins effect). The present study deals with the characterization of elastomers for its modeling in commercial finite element software packages and verification of some predicted design parameters with physical testing.

The demand for injection molded reinforced plastic products used in the automotive industry is growing due to the capability of the material for volume production, high strength to weight ratio, and its flexibility of geometry design. On the other hand, the application of fiber filled plastic composites has been challenging and subject of research during past decades due to the inability to accurately predict the mechanical strength and stiffness behavior owing to its anisotropic characteristics. This paper discusses a numerical simulation based technique using multiscale (2 scale Micro-Macro) modeling approach for short fiber reinforced plastic composites. Fiber orientation tensors and knit lines are predicted in microscale analysis using Autodesk Inc.’s Moldflow® software, and structural analysis is performed considering the homogenized structure in macroscale analysis using ANSYS® software tool.

In this paper, an optimization method is proposed to improve the efficiency of a transmission equipped electric vehicle (EV) by optimizing gear shift strategy. The idea behind using a transmission for EV is to downsize the motor size and decrease overall energy consumption. The efficiency of an electric motor varies with its operating region (speed/torque) and this plays a crucial role in deciding overall energy consumption of EVs. A lot of work has been done to optimize gear shift strategy of internal combustion engines (ICE) based automatic transmission (AT), and automatic-manual transmissions (AMT), but for EVs this is still a new area. In case of EVs, we have an advantage of regeneration which makes it different from the ICE based vehicles. In order to maximize the efficiency, a heuristic search based algorithm - Genetic Algorithm (GA) is used.

This paper presents the application of a proposed fuzzy inference system as part of a stability control design scheme implemented with active steering actuator sets. The fuzzy inference system is used to detect the level of overseer/understeer at the high level and a speed-adaptive activation module determines whether an active front steering, active rear steering, or active 4 wheel steering is suited to improve vehicle handling stability. The resulting model-free system is capable of minimizing the amount of model calibration during the vehicle stability control development process as well as improving vehicle performance and stability over a wide range of vehicle and road conditions. A simulation study will be presented that evaluates the proposed scheme and compares the effectiveness of active front steer (AFS) and active rear steer (ARS) in enhancing the vehicle performance. Both time and frequency domain results are presented.

Fuel economy of both highway and off-highway vehicles is a major driver for new technology development. One of the technologies to meet this driver is a digital valve based hydraulic system. Digital Hydraulics technology employs high speed on/off valves to achieve the same functionality with no throttling loss. Furthermore, by forming various architecture by using digital valves, it provides the system level capability and flexibility for energy saving and productivity improvement. There are many challenges in fully realizing the full efficiency benefits of the system in an actual application. These challenges include packaging, durability, a change in the operator's perception of the vehicle as well as hydraulic system performances during operation. One significant issue is the noise, vibration and harshness (NVH) of the system. Due to the nature of the digital valve operation, there are severe transient dynamics in the fluid system.

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.

Driveline plunge mechanism dynamics has a significant contribution to the driver's perceivable transient NVH error states and to the transmission shift quality. As it accounts for the pitch or roll movements of the front powerplant and rear drive unit, the plunging joints exhibit resisting force in the fore-aft direction under various driveline torque levels. This paper tackles the difficult task of quantifying the coefficient of static friction and the coefficient of dynamic friction in a simple to use metric as it performs in the vehicle. The comparison of the dynamic friction to the static friction allows for the detection of the occurrence of stick-slip in the slip mechanism; which enables for immediate determination of the performance of the design parameters such as spline geometry, mating parts fit and finish, and lubrication. It also provides a simple format to compare a variety of designs available to the automotive design engineer.

Drivelines used in modern pickup trucks commonly employ universal joints. This type of joint is responsible for second driveshaft order vibrations in the vehicle. Large displacements of the joint connecting the driveline and the rear axle have a detrimental effect on vehicle NVH. As leaf springs are critical energy absorbing elements that connect to the powertrain, they are used to restrain large axle windup angles. One of the most common types of leaf springs in use today is the multi-stage parabolic leaf spring. A simple SAE 3-link approximation is adequate for preliminary studies but it has been found to be inadequate to study axle windup. A vast body of literature exists on modeling leaf springs using nonlinear FEA and multibody simulations. However, these methods require significant amount of component level detail and measured data. As such, these techniques are not applicable for quick sensitivity studies at design conception stage.

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.

Electric vehicles are receiving considerable attention because they offer a more efficient and sustainable transportation alternative compared to conventional fossil-fuel powered vehicles. Since the battery pack represents the primary energy storage component in an electric vehicle powertrain, it requires accurate monitoring and control. In order to effectively estimate the battery pack critical parameters such as the battery state of charge (SOC), state of health (SOH), and remaining capacity, a high-fidelity battery model is needed as part of a robust SOC estimation strategy. As the battery degrades, model parameters significantly change, and this model needs to account for all operating conditions throughout the battery's lifespan. For effective battery management system design, it is critical that the physical model adapts to parameter changes due to aging.

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.

Designing a vehicle body involves meeting numerous performance requirements related to different attributes such as NVH, Durability, Safety, and others. Multi-Disciplinary Optimization (MDO) is an efficient way to develop a design that optimizes vehicle performance while minimizing the weight. Since a body design evolves in course of the product development cycle, it is essential to repeat the MDO process several times as a design matures and more accurate data become available. This paper presents a real life application of the MDO process to reduce weight while optimizing performance over the design cycle of the 2015 Mustang. The paper discusses the timing and results of the applied Multi-Disciplinary Optimization process. The attributes considered during optimization include Safety, Durability and Body NVH. Several iterations of MDO have been performed at different milestones in the design cycle leading to a significant weight reduction of the already optimized design by over 16kg.

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.