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Consumers design different PHEVs than expert analysts assume. Experts almost uniformly assume PHEVs that offer true all-electric driving for 10 to 60 miles; consumers are more likely to design PHEVs that do not offer true all-electric driving and have short ranges over which they use grid-electricity. Thus consumers? PHEV designs are less expensive. These consumer PHEV designs do, or don?t, produce lower GHG emissions than experts? PHEVs over the next ten years. The devil is in the details, i.e., which powerplant emissions to assign to new electricity demand: marginal or average. If (based on marginal powerplant emissions) it makes almost no difference whether we sell consumer-designed or expert-assumed PHEVs over the next ten years, yet as the grid continues to de-carbonize all-electric PHEV designs emerge as clearly the better option, there is a trajectory we could be on from blended, ?short range? PHEVs to all-electric ?long range? PHEVs.

This study evaluates utilizing an accelerated test method that correlates customer interaction with a vehicle seat where bagginess and wrinkling is produced. The evaluation includes correlation from warranty returns as well as test vehicle results for test verification. Consumer metrics will be discussed within this paper with respect to potential application of this test method, including but not limited to JD Power ratings. The intent of the test method is to aid in establishing appropriate design parameters of the seat trim covers and to incorporate appropriate design measures such as tie downs and lamination. This test procedure was utilized in a Design for Six Sigma (DFSS) project as an aid in optimizing seat parameters influencing trim cover performance using a Design of Experiment approach. Presenter Lisa Fallon, General Motors LLC

The original Table 2 includes incorrect data under the "Primary Energy" column for "multi-strike", "continuous" and "plasma" system types.

The present production General Motors 2-Mode Hybrid system for full-size SUVs and pickup trucks integrates truck utility functions with a full hybrid system. The 2-mode hybrid system incorporates two electro-mechanical power-split operating modes with four fixed-gear ratios. The combination provides fuel savings from electric assist, regenerative braking and low-speed electric vehicle operation. The combination of two power-split modes reduces the amount of mechanical power that is converted to electric power for continuously variable transmission operation, meeting the utility required for SUVs and trucks. This paper describes how fuel economy functionality was blended with full-size truck utility functions. Truck functions described include: Manual Range Select, Cruise Control, 4WD-Low and continuous high load operation.

In the analysis for durability or R&H performance with the full vehicle multibody models, the need for component flexibility is increasing along with demand for more precise full vehicle system. The component elastic deformations are usually expressed by modal superposition from component normal mode analysis with finite element model for reducing model size and simulation time. Although the simulation results of MBD analysis are more accurate according to increasing the number of flexible body and modes, the increasing of flexible components makes worse simulation time and convergence in MBD analysis. Especially, in the MBD analysis including a flexible upper body, in substitution for large number degree of freedom FE model such as trimmed body, it should take a few times longer than the case of rigid upper body This paper proposes the methods of reducing computational cost with adequate mode selections without the loss of simulation accuracy in the flexible MBD.

The NVH study of trimmed vehicle body is essential in improving the passenger comfort and optimizing the vehicle weight. Efficient modal finite-element approaches are widely used in the automotive industry for investigating the frequency response of large vibro-acoustic systems involving a body structure coupled to an acoustic cavity. In order to accurately account for the localized and frequency-dependant damping mechanism of the trim components, a direct physical approach is however preferred. Thus, a hybrid modal-physical approach combines both efficiency and accuracy for large trimmed body analysis. Dynamic loads and exterior acoustic loads can then be applied on the trimmed body model in order to evaluate the transfer functions between these loads and the acoustic response in the car compartment.

The assessment of the Transmission Loss (TL) of vehicle components at Low-Mid Frequencies generally raises difficulties associated to the physical mechanisms of the noise transmission through the automotive panel. As far as testing is concerned, it is common in the automotive industry to perform double room TL measurements of component baffled cut-outs, while numerical methods are rather applied when prototype or hardware variants are not available. Indeed, in the context of recent efforts for reduction of vehicle prototypes, the use of simulation is constantly challenged to deliver reliable means of decision during virtual design phase. While the Transfer matrix method is commonly and conveniently used at Mid-High frequencies for the calculation of a trimmed panel, the simulation of energy transfer at low frequencies must take into account modal interactions between the vehicle component and the acoustic environment.

For (benchmark) tests it is not only useful to study the acoustic performance of the whole vehicle, but also to assess separate components such as the engine. Reflections inside the engine bay bias the acoustic radiation estimated with sound pressure based solutions. Consequently, most current methods require dismounting the engine from the car and installing it in an anechoic room to measure the sound emitted. However, this process is laborious and hard to perform. In this paper, two particle velocity based methods are proposed to characterize the sound radiated from an engine while it is still installed in the car. Particle velocity sensors are much less affected by reflections than sound pressure microphones when the measurements are performed near a radiating surface due to the particle velocity's vector nature, intrinsic dependency upon surface displacement and directivity of the sensor. Therefore, the engine does not have to be disassembled, which saves time and money.

Driving on the race track is an especially grueling situation for the automotive brake system. Temperatures can exceed the phase transition temperature of the disc material, wear rates of friction material can be orders of magnitude higher than during street use, and hydraulic pressures and mechanical stresses on components can approach their design limits. It is a given that friction material under these conditions will wear unevenly - causing taper and cupping wear - and an associated set of performance degradations will occur, including an increase in fluid consumption (pedal travel increase) and loss of mechanical efficiency (pedal force increase).

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.

A turbocharger is currently widely used to boost performance of an internal combustion engine. Generally, a turbocharger consists of a compressor which typically is driven by an exhaust turbine. The compressor will influence how the low frequency engine pulsation propagates in the intake system. The compressor will also produce broad-band flow induced sound due to the turbulence flow and high frequency narrowband tonal sound which is associated with rotating blade pressures. In this paper, a practical simulation procedure based on a computational fluid dynamics (CFD) approach is developed to predict the flow induced sound of a turbocharger compressor. In the CFD model of turbocharger compressor, the unsteady, moving wheel, detached eddy simulation (DES) approach are utilized. In this manner, both the broad-band and narrow-band flow induced sound are directly resolved in the CFD computation.

The highly transient operational nature of passenger car engines makes cylinder pressure based feedback control of combustion phasing difficult. The problem is further complicated by cycle-to-cycle combustion variation. A method for fast and accurate differentiation of normal combustion variations and true changes in combustion phasing is addressed in this research. The proposed method combines the results of a feed forward combustion phasing prediction model and “noisy” measurements from cylinder pressure using an iterative estimation technique. A modified version of an Extended Kalman Filter (EKF) is applied to calculate optimal estimation gain according to the stochastic properties of the combustion phasing measurement at the corresponding engine operating condition. Methods to improve steady state CA50 estimation performance and adaptation to errors are further discussed in this research.

As the automotive industry prepares to roll out an unprecedented range of fully electric propulsion vehicle models over the next few years - it really brings to a head for folks responsible for brakes what used to be the subject of hypothetical musings and are now pivotal questions for system design. How do we really go about designing brakes for electric vehicles, in particular, for the well-known limit condition of descending a steep grade? What is really an “optimal’ design for brakes considering the imperatives for the entire vehicle? What are the real “limit conditions” for usage that drive the fundamental design? Are there really electric charging stations planned for or even already existing in high elevations that can affect regenerative brake capacity on the way down? What should be communicated to drivers (if anything) about driving habits for electric vehicles in routes with significant elevation change?

Autoignition delay times of two full blend gasoline fuels (high and low RON) were explored in a rapid compression machine. CO2 dilution by mass was introduced at 0%, 15%, and 30% levels with the O2:N2 mole ratio fixed at 1:3.76. This dilution strategy is used to represent exhaust gas recirculation (EGR) substitution in spark ignition (SI) engines by using CO2 as a surrogate for major EGR constituents(N2, CO2, H2O). Experiments were conducted over the temperature range of 650K-900K and at 10 bar and 20 bar compressed pressure conditions for equivalence ratios of (Φ =) 0.6-1.3. The full blend fuels were admitted directly into the combustion chamber for mixture preparation using the direct test chamber (DTC) approach. CO2 addition retarded the autoignition times for the fuels studied here. The retarding effect of the CO2 dilution was more pronounced in the NTC region when compared to the lower and higher temperature range.

Accurate prediction of in-vehicle powertrain bounce mode is necessary to ensure optimum responses are achieved at driver’s touch points during 4post shake or rough road shake events. But, during the early stages of vehicle development, building a detailed vehicle finite element (FE) model is not possible and often powertrain bounce modes are computed assuming the powertrain to be a stand-alone unit. Studies conducted on FE models of a large SUV with body on frame architecture showed that the stand-alone approach overestimates the powertrain bounce mode. Consequently, there is a need for a simplified version of vehicle model which can be built early on to compute powertrain modes. Previously, representing all the major components as rigid entities, simplified unibody vehicle models have been built to compute powertrain modes. But such an approach would be inaccurate here, for a vehicle with body on frame architecture due to the flexible nature of the frame (even at low frequencies).

The Particulate Matter Index (PMI) is a tool that provides an indication of a fuel’s tendency to produce Particulate Matter (PM) emissions. Currently, the index is being used by various fuel laboratories and the Automotive OEMs as a tool to understand the gasoline fuel’s impact on both PM from engine hardware and vehicle-out emissions. In addition, a newer index that could be used to give an indication of the PM tendency of the gasoline range fuels, called the Particulate Evaluation Index (PEI), is shown to have a good correlation to PMI. The data used in those indices are collected from chemical analytical methods. This paper will compare gas chromatography (GC) methods used by three laboratories and discuss how the different techniques may affect the PMI and PEI calculation.

Internal combustion engine gets heated up due to continuous combustion of fuel. To keep engine working efficiently and prevent components damage due to very high temperature, the engine needs to be cooled down. Based on power output requirement and provision for cooling system, every engine has it’s unique cooling system. Liquid based cooling systems are majorly implemented in automobile. It’s important to keep in mind that during design phase that, cooling the engine will lower the power to fuel consumption ratio. Therefore, during lower ambient conditions, the cooling system should be able to uniformly increase the temperature of the engine components, engine oil and transmission oil. This is achieved by circulating the coolant through cooling jacket, engine oil heater and transmission oil heater, which will be heated by the combustion heat.

During a vehicle drive cycle, the oil in the engine oil pan sloshes very vigorously due to the acceleration of the vehicle. This can cause the pickup tube in the engine oil pan to become uncovered from oil and exposed to air, which affects the lubrication pump performance. Engine oil pan sloshing is inherently a 3D problem as the free oil surface is constantly changing. Multi-dimensional Computational Fluid Dynamics (CFD) methods are very useful to simulate such problems with high detail and accuracy but are computationally very expensive. Part of the engine lubrication system, such as the pump, can be modelled in 1D which can predict accurate results at relatively high computational speeds. By utilizing the advantages of both 1D and 3D CFD models, a coupled 1D-3D simulation approach has been developed to capture the detailed oil sloshing phenomenon in SimericsMP+ and the system level simulation is conducted in GT-SUITE where 3D spatial data is not required.

It is known that SEA is a rapid and simple methodology for analyzing complex vibroacoustic systems. However, the SEA principle is not always valid and one has to be careful about the physical conditions at which the SEA principle is acceptable. In this study, the appropriate damping loss factor of the vehicle interior cavity is studied in the viewpoint of the modal overlap factor of the cavity and the decay per mean free path (DMFP) of the cavity. Virtual SEA tests are performed with an FE model combination, which is suggested by a previous study of Stelzer et al. for the simulation of the sound transmission loss (STL) of vehicle panel structure. The FE model combination is consisting of the body in white (BIW), an acoustical-excited hemisphere-shaped exterior cavity, and the interior cavity. It is found that the DMFP of the interior cavity is appropriate between 0.5 ~ 1 dB for applying SEA principle.

In general, when a problem occurs in a component of powertrains, various phenomena appear, and abnormal noise is one of them. The service mechanics diagnose the noise through analysis by using their ears and equipment. However, depending on their experiences, analysis time and diagnostic accuracy vary greatly. To shorten the analysis time and improve the diagnostic accuracy, we have developed a technology to diagnose powertrain parts that cause abnormal noises. To create the best deep learning model for our diagnosis, we tried to collect many abnormal noises from various parts. The collected noise data was measured under idle and various operating conditions from our vehicles and test cells. This noise data is abnormal noises generated from engines, transmissions, drive system and PE (Power Electric) parts of eco-friendly vehicles. From the collected data, we distinguished good and bad data through detailed analysis in time and frequency domain.