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A series of scaled wind tunnel tests are conducted to investigate the aerodynamic benefits of heavy vehicle platooning and the availability of cooling air for trailing vehicles on two- and four-vehicle platoons. To measure the aerodynamic drag, scale models are mounted onto a splitter plate by means of a low-friction linear bearing and a load cell located within each model trailer. In addition to drag, pressure measurements are made with a pitot probe positioned at the center of each model radiator grill. Four homogeneous, two-vehicle platoons are tested for spacings up to 300′ and six heterogeneous, four-vehicle platoons are tested with spacings ranging from 30′ to 50′. For the heterogeneous platoons, configurations are tested with one distinct heavy vehicle or medium duty vehicle, as well as with four distinct heavy vehicles. Over spacings of 15′ to 80′, the best performing homogeneous, two-vehicle platoons are comprised of a Supertruck tractor and straight frame trailer.

Lawrence Livermore National Laboratory (LLNL) has conducted a series of scaled wind tunnel tests to investigate the aerodynamic benefits of heavy vehicle platooning and the availability of cooling air for trailing vehicles on two- and three-vehicle platoons. To measure the aerodynamic drag, scale models are mounted onto a LLNL designed splitter plate by means of a low-friction linear bearing and a load cell located within each model trailer. In addition to drag, pressure measurements are made with a pitot probe positioned at the center of each model radiator grill. Particle Image Velocimetry (PIV) and Infrared Thermography (IRT) measurements are used to map the three-dimensional velocity field and flow structures around the vehicles.

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.

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.

This paper proposes an approach that characterizes a driver's driving behavior and style in real-time during car-following drives. It uses an online learning of the evolving Takagi-Sugeno fuzzy model combined with the Markov model. The inputs fed into the proposed algorithm are from the measured signals of on-board sensors equipped with current vehicles, including the relative distance sensors for Adaptive Cruise Control feature and the accelerometer for Electronic Stability Control feature. The approach is verified using data collected using a test vehicle from several car-following test trips. The effectiveness of the proposed approach has been shown in the paper.

Injection spray dynamics is known to be of great importance when modeling turbulent multi-phase flows in diesel engines. Two key aspects of spray dynamics are liquid breakup and penetration, both of which are affected by the initial sizes of the injected droplets. In the current study, injection of liquid n-heptane is characterized with initial droplet sizes with diameters on the order of 0.10 - 0.25 nozzle diameters. This is done for a Reynolds Averaged Navier-Stokes (RANS) RNG k-ε turbulence model with a minimum grid size of 125 μm and for a Large Eddy Simulations (LES) viscosity turbulence model with a minimum grid size of 62.5 μm. The results of both turbulence models are validated against non-reacting experimental data from the Engine Combustion Network (ECN). The results show that the injected droplet sizes have a significant impact on both liquid and vapor penetration lengths.

The aluminum alloy 7075-T6 has the potential to be used for structural automotive body components as an alternative to boron steel. Although this alloy shows poor formability at room temperature, it has been demonstrated that hot stamping is a feasible sheet metal process that can be used to overcome the forming issues. Hot stamping is an elevated temperature forming operation in which a hot blank is formed and quenched within a stamping die. Attaining a high quench rate is a critical step of the hot stamping process and corresponds to maximum strength and corrosion resistance. This work looks at measuring the quench rate of AA7075-T6 by way of three different approaches: water, a water-cooled plate, and a bead die. The water-cooled plate and the bead die are laboratory-scale experimental setups designed to replicate the hot stamping/die quenching process.

New vehicle control algorithms are needed to meet future emissions and fuel economy mandates that are quite likely to require a measurement of ambient specific humidity (SH). Current practice is to obtain the SH by measurement of relative humidity (RH), temperature and barometric pressure with physical sensors, and then to estimate the SH using a fit equation. In this paper a novel approach is described: a system of neural networks trained to estimate the SH using data that already exists on the vehicle bus. The neural network system, which is referred to as a virtual SH sensor, incorporates information from the global navigation satellite system such as longitude, latitude, time and date, and from the vehicle climate control system such as temperature and barometric pressure, and outputs an estimate of SH. The conclusion of this preliminary study is that neural networks have the potential of being used as a virtual sensor for estimating ambient and intake manifold's SH.

No two battery cells can be identical. Charging/discharging a battery pack without monitoring cell voltages or SoC (State-of-Charge) will cause cell voltages to deviate over time and the packs useable capacity to decrease quickly. To redistribute charge uniformly among cells, various cell balancing methods have been proposed in the literature. In this paper, a cell balancing method based on a single switched-capacitor is presented from a brand new perspective. Unlike the traditional balancing methods that rely on the voltage divergence criterion, this paper uses the SoC divergence criterion to shuttle charge from a highly charged cell to a poorly charged cell. Moreover, an equivalent resistance of the single-switched capacitor topology is derived in steady state. For fast cell balancing, design guidelines are provided for selecting a proper switching-time period and the capacitor parameters. Ultracapacitors are recommended to achieve this goal.

With a goal to help develop pressure sensor calibration and deployment algorithms using computer simulations, an Arbitrary Lagrangian Eulerian (ALE) approach was adopted in this research to predict the responses of side crash pressure sensors for unitized vehicles. For occupant protection, acceleration-based crash sensors have been used in the automotive industry to deploy restraint devices when vehicle crashes occur. With improvements in the crash sensor technology, pressure sensors that detect pressure changes in door cavities have been developed recently for vehicle crash safety applications. Instead of using acceleration (or deceleration) in the acceleration-based crash sensors, the pressure sensors utilize pressure change in a door structure to determine the deployment of restraint devices. The crash pulses recorded by the acceleration-based crash sensors usually exhibit high frequency and noisy responses.

High-resolution planar laser-induced fluorescence (PLIF) measurements were performed on the scalar field in an optical engine. The measurements were of sufficient resolution to fully resolve all of the length scales of the flow field through the full cycle. The scalar dissipation spectrum was calculated, and by fitting the results to a model turbulent spectrum the Batchelor scale of the turbulent flow was estimated. The scalar inhomogeneity was introduced by a low-momentum gas jet injection. A consistent trend was observed in all data; the Batchelor scale showed a minimum value at top dead center (TDC) and was nearly symmetric about TDC. Increasing the engine speed resulted in a decrease of the Batchelor scale, and the presence of a shroud on the intake valve, which increased the turbulence intensity, also reduced the Batchelor scale. The effect of the shrouded valve was less significant compared to the effect of engine speed.

In an attempt to predict the responses of side crash pressure sensors, the Corpuscular Particle Method (CPM) was adopted and enhanced in this research. Acceleration-based crash sensors have traditionally been used extensively in automotive industry to determine the air bag firing time in the event of a vehicle accident. The prediction of crash pulses obtained from the acceleration-based crash sensors by using computer simulations has been very challenging due to the high frequency and noisy responses obtained from the sensors, especially those installed in crash zones. As a result, the sensor algorithm developments for acceleration-based sensors are largely based on prototype testing. With the latest advancement in the crash sensor technology, side crash pressure sensors have emerged recently and are gradually replacing acceleration-based sensor for side impact applications.

An Arbitrary Lagrangian Eulerian (ALE) approach was adopted in this study to predict the responses of side crash pressure sensors in an attempt to assist pressure sensor algorithm development by using computer simulations. Acceleration-based crash sensors have traditionally been used to deploy restraint devises (e.g., airbags, air curtains, and seat belts) in vehicle crashes. The crash pulses recorded by acceleration-based crash sensors usually exhibit high frequency and noisy responses depending on the vehicle's structural design. As a result, it is very challenging to predict the responses of acceleration-based crash sensors by using computer simulations, especially those installed in crush zones. Therefore, the sensor algorithm developments for acceleration-based sensors are mostly based on physical testing.

This paper presents advanced and cost-reducing technologies of a motor drive system with reduced permanent magnets but without a position sensor. The key enabler is the integration of novel designs of flux-intensifying interior permanent magnet synchronous machines (FI-IPMSMs) and position self-sensing control technologies. In this paper, we focus on two advantages of FI-IPMSM over conventional flux-weakening interior permanent magnet synchronous machines (FW-IPMSMs). The first benefit is that thinner magnets are possible and there is less concern for demagnetization because of its significantly smaller flux-weakening current. This paper presents two design examples of FI-IPMSMs, one of which has not only smaller magnets but also similar power conversion capability. The second advantage is reduced saturation and cross-saturation effect, which leads to improved position self-sensing capability.

The ISO TC22/SWG2 - Brake Lining Committee established a task force to determine and analyze root causes for variability during dynamometer brake performance testing. SAE paper 2010-01-1697 “Brake Dynamometer Test Variability - Analysis of Root Causes” [1] presents the findings from the phases 1 and 2 of the “Test Variability Project.” The task force was created to address the issue of test variability and to establish possible ways to improve test-to-test and lab-to-lab correlation. This paper presents the findings from phase 3 of this effort-description of factors influencing test variability based on DOE study. This phase concentrated on both qualitative and quantitative description of the factors influencing friction coefficient measurements during dynamometer testing.

This paper proposes an approach to use ABS wheel speed sensor signals together with other vehicle state information from a brake control module to detect an unbalanced tire or tires in real-time. The proposed approach consists of two-stage algorithms that mix a qualitative method using band-pass filtering with a quantitative parameter identification using conditional least squares. This two-stage approach can improve the robustness of tire imbalance or imbalances. The proposed approach is verified through vehicle testing and the test results show the effectiveness of the approach.

Recent advances in morphing, simulation, and optimization technologies have enabled analytically driven aerodynamic shape optimization to become a reality. This paper will discuss the integration of these technologies into a single process which enables the aerodynamicist to optimize vehicle shape as well as gain a much deeper understanding of the design space around a given exterior theme.

Increasing electronics content, growing computing power, and proliferation of opportunities for information connectivity (through improved sensors, GPS, road and traffic information systems, wireless internet access, vehicle-to-vehicle communication, etc.) are technology trends which can significantly transform and impact future automotive vehicle's control and diagnostic strategies. One aspect of the increasing vehicle connectivity is access to ambient and road condition information, such as ambient temperature, ambient pressure, humidity, % cloudiness, visibility, cloud ceiling, precipitation, rain droplet size, wind speed, and wind direction based on wireless internet access. The paper discusses the potential opportunities made available through wireless communication between the vehicle and the internet.

Nowadays is a common sense the importance of the CAE usage in the modern automotive industry. The ability to predict the design behavior of a project represents a competitive advantage. However, some CAE models have become so complex and detailed that, in some cases, one just can not build up the model without a considerable amount of information. In that case simplified models play an important role in the design phase, especially in pre-program stages. This work intends to build an archetypal vehicle dynamics model able to predict the rollover resistance of a vehicle design. Through the study of a more complex model, carried out in Adams environment, it was possible to identify the key degrees of freedom to be considered in the simplified model along with important elements of the suspension which are also important design factors.

Exhaust gas temperature is often measured with a device such as thermocouple or RTD (Resistance Temperature Detector). An alternative method to determine the gas temperature would be to use an existing gas sensor heating mechanism to perform as a temperature sensor. A planar type FLOH (Fast Light Off HEGO-Heated Exhausted Gas Oxygen) sensor under transient vehicle speed/load conditions is suited to this function and was modeled to predict the exhaust gas temperature. The numerical input to the model includes exhaust flow rate, heater voltage, and heater current. Laboratory experiments have been performed to produce an equation relating the resistance of the heater and the temperature of the sensor (heater), which provides a method to indirectly determine HEGO sensor temperature.