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Computational Fluid Dynamics (CFD) modeling was used to investigate the effects of the direct injection of wet ethanol at various injection timings during the intake stroke in a diesel engine with a shallow bowl piston. Thermally Stratified Compression Ignition (TSCI) has been proposed to expand the operating range of Low Temperature Combustion (LTC) by broadening the temperature distribution in the cylinder prior to ignition. TSCI is accomplished by injecting either water or a water-fuel mixture with a high latent heat of vaporization like wet ethanol. This current study focuses on isolating the effects that injecting such a high heat of vaporization mixture during the intake stroke has on the distribution of temperature and equivalence ratio in the cylinder before the onset of combustion. A CONVERGE 3-D CFD model of a single cylinder diesel research engine using Reynolds Averaged Naiver Stokes (RANS) turbulence modeling was developed and validated against experimental data.

In military applications, diesel engines are required to achieve high power outputs and therefore must operate at high loads. This high load operation leads to high piston component temperatures and heat rejection rates limiting the packaged power density of the powertrain. To help predict and understand these constraints, as well as their effects on performance, a thermodynamic engine model coupled to a finite element heat conduction solver is proposed and validated in this work. The finite element solver is used to calculate crank angle resolved, spatially averaged piston temperatures from in-cylinder heat transfer calculations. The calculated piston temperatures refine the heat transfer predictions as well requiring iteration between the thermodynamic model and finite element solver.

Electrification of off-road vehicle powertrains can increase mobility, improve energy efficiency, and enable new utility by providing high amounts of electrical power for auxiliary devices. These vehicles often operate in extreme temperature conditions at low ground speeds and high power levels while also having significant cooling airpath restrictions. The restrictions are a consequence of having grilles and/or louvers in the airpath to prevent damage from the operating environment. Moreover, the maximum operating temperatures for high voltage electrical components, like batteries, motors, and power-electronics, can be significantly lower than those of the internal combustion engine. Rejecting heat at a lower temperature gradient requires higher flow rates of air for effective heat exchange to the operating environment at extreme temperature conditions.

Vehicle dynamics simulation is one of the newest and most valuable technologies being applied in the racing world today. Professional designers and race teams are investing heavily to test and improve the dynamics of their suspension systems through this new technology. This paper discusses the testing of one of Clemson University's most recent Formula SAE racecars on a seven-poster vehicle dynamics simulator; commonly known as a “shaker rig.” Testing of the current dampers using a shock dynamometer was conducted prior to testing and results are included for further support of conclusions. The body of the paper is a discussion of the setup and testing procedures involved with the dynamic simulator. The results obtained from the dynamic simulator tests are then analyzed in conjunction with the shock dynamometer results. Conclusions are formed from test results and methods for future improvements to be applied in Formula SAE racing are suggested.

A hot and cold water mixing process with a steam condenser and a chilled water heat exchanger is set up for an engine EGR fouling test. The test rig has water recycled in the loop of a pump, heat exchangers, a three-way mixing valve, and a test EGR unit. The target unit temperature is controlled by a heating, cooling and mixing process with individual valves regulating the flow-rate of saturated steam, chilled water and mixing ratio. The challenges in control design are the dead-time, interaction, nonlinearity and multivariable characteristics of heat exchangers, plus the flow recycle in the system. A systems method is applied to extract a simple linear model for control design. The method avoids the nonlinearity and interaction among different temperatures at inlet, outlet and flow-rate. The test data proves the effectiveness of systems analysis and modeling methodology. As a result, the first-order linear model facilitates the controller design.

Drive cycles are a core piece of vehicle development testing methodology. The control and calibration of the vehicle is often tuned over drive cycles as they are the best representation of the real-world driving the vehicle will see during deployment. To obtain general performance numerous drive cycles must be generated to ensure final control and calibration avoids overfitting to the specifics of a single drive cycle. When real-world driving cycles are difficult to acquire methods can be used to create statistically similar synthetic drive cycles to avoid the overfitting problem. This subject has been well addressed within the passenger vehicle domain but must be expanded upon for utilization with tracked off-road vehicles. Development of hybrid tracked vehicles has increased this need further. This study shows that turning dynamics have significant influence on the vehicle power demand and on the power demand on each individual track.

The development of a repeatable dynamic rollover test methodology with meaningful occupant protection performance objectives has been a longstanding and unmet challenge. Numerous studies have identified the random and chaotic nature of rollover crashes, and the difficulty associated with simulating these events in a laboratory setting. Previous work addressed vehicle level testing attempting to simulate an entire rollover event but it was determined that this test methodology could not be used for development of occupant protection restraint performance objectives due to the unpredictable behavior of the vehicle during the entire rollover event. More recent efforts have focused on subsystem tests that simulate distinct phases of a rollover event, up to and including the first roof-to-ground impact.

Adiabatic heating during plastic straining can slow the diffusionless shear transformation of austenite to martensite in steels that exhibit transformation induced plasticity (TRIP). However, the extent to which the transformation is affected over a strain rate range of relevance to automotive stamping and vehicle impact events is unclear for most third-generation advanced high strength TRIP steels. In this study, an 1180MPa minimum tensile strength TRIP steel with carbide-free bainite is evaluated by measuring the variation of retained austenite volume fraction (RAVF) in fractured tensile specimens with position and strain. This requires a combination of servo-hydraulic load frame instrumented with high speed stereo digital image correlation for measurement of strains and ex-situ synchrotron x-ray diffraction for determination of RAVF in fractured tensile specimens.

Under the initiative of The United States Council for Automotive Research LLC (USCAR) [1], we have developed and run comprehensive friction tests of dual clutch transmission fluids (DCTFs). The focus of this study is to quantify the anti-shudder durability over a simulated oil life of 75,000 shifts. We have evaluated six DCT fluids, including 2 fluids with known field shudder performance. Six different tests were conducted using a DC motor-driven friction test machine (GK test bench): 1. Force Controlled Continuous Slip, 2. Dynamic Friction, 3. Speed controlled Acceleration-Deceleration, 4. Motor-torque controlled Acceleration-Deceleration, 5. Static Friction, and 6. Static Break-Away. The test fluids were aged (with the clutch system) on the test bench to create a realistic aging of the entire friction system simultaneously.

Magnesium alloys are not corrosion resistant in many applications and they require coating protection. In this study, we developed an electroless E-coating technique for magnesium alloys and discussed a cathodic E-coating deposition mechanism for the electroless E-coating process. This coating can be formed within a few seconds by dipping a magnesium alloy (i.e., AZ91D) in an E-coat bath without applying a current or voltage. The deposited electroless coat can offer good protection to the AZ91D magnesium alloy in 5 wt% NaCl corrosive solution as well as in a phosphating bath. The most interesting finding is that the electroless coating is not sensitive to local damage. No preferential corrosion attack occurred along the scratches made on the coating.

A new apparatus for testing modern safety belt systems was developed. The apparatus design, dynamic behavior and test procedure are described. A number of tests have been conducted using this apparatus. These tests allowed identification of key performance parameters of pretensioners and load limiting retractors which are relevant to occupant protection in a crash environment. Good test repeatability was observed, which allowed comparison of different safety belt designs. The apparatus may be used for better specification and verification of safety belt properties on a subsystem level as well as for the validation of CAE models of safety belts used in simulations of occupant response to crash events.

Biodiesel is a domestic, renewable fuel for diesel engines and is made from agricultural co-products such as soybean oil, rapeseed oil, palm oil and other natural oils. Biodiesel is a cleaner burning fuel that is biodegradable and non-toxic compared to petroleum diesel. Biodiesel has become a major alternative fuel for automotive applications and is critical for lowering US dependence on foreign oil and attain energy security. Vehicle manufacturers have developed new vehicle and diesel engine technologies compatible with B6-B20 biodiesel blends meeting ASTM D7467 specifications. Field warranty and validation tests have shown significant concerns with use of poor quality biodiesel fuels including fuel system deposits, engine oil deterioration, and efficiency loss of the after treatment system. Maintaining good quality of biodiesel is critical for success as a commercial fuel.

Heat treated cast aluminum components like engine blocks and cylinder heads can develop significant amount of residual stress and distortion particularly with water quench. To incorporate the influence of residual stress and distortion in cast aluminum product design, a rapid simulation approach has been developed based on artificial neural network and component geometry characteristics. Multilayer feed-forward artificial neural network (ANN) models were trained and verified using FEA residual stress and distortion predictions together with part geometry information such as curvature, maximum dihedral angle, topologic features including node's neighbors, as well as quench parameters like quench temperature and quench media.

This article presents a pointing gesture-based point of interest computation method via pointing rays’ intersections for situated awareness interactions in vehicles. The proposed approach is compared with two alternative methods: (a) a point of interest identification method based on the intersection of the pointing ray with the point cloud (PoC) resulting from the vehicle sensors, and (b) the traditional ray-casting approach, where the point of interest is computed based on the first intersection of the pointing rays with locations stored in a 2D annotated map. Simulation results show that the presented method outperforms by 36.25% the traditional ray casting one. However, as it was expected, the sensor-based computation method is more accurate. The validation of our approach was conducted by experiments performed in a test track facility.

Heat rejection in ground vehicle propulsion systems remains a challenge given variations in powertrain configurations, driving cycles, and ambient conditions as well as space constraints and available power budgets. An optimization strategy is proposed for engine radiator geometry size scaling to minimize the cooling system power consumption while satisfying both the heat removal rate requirement and the radiator dimension size limitation. A finite difference method (FDM) based on a heat exchanger model is introduced and utilized in the optimization design. The optimization technique searches for the best radiator core dimension solution over the design space, subject to different constraints. To validate the proposed heat exchanger model and optimization algorithm, a heavy duty military truck engine cooling system is investigated.

It has been extensively evidenced that modern diesel engines generate a considerable amount of soot nanoparticles. Existing soot sensors are not suitable for such nanoparticles. Current standard gravimetric techniques are extremely insensitive to fine soot particles. Soot diagnostics developed for research purposes, e.g., laser induced-incandescence, do not provide quantitative characterization, and expanded practical applications of these techniques are hardly conceivable. This paper addresses this emerging need for monitoring nano-sized soot emissions. Here, we investigated the use of polarization modulated scattering (PMS) for soot sensing in engine environments. The technique involves 1) measuring laser scattering by soot particles at multiple angles while varying the polarization states of the incident laser beam, 2) determining multiple elements of the Mueller matrix from the measured signals, and 3) inferring properties of the soot particles from these elements.

A major concern for a high-power density, heavy-duty engine is the durability of its components, which are subjected to high thermal loads from combustion. The thermal loads from combustion are unsteady and exhibit strong spatial gradients. Experimental techniques to characterize these thermal loads at high load conditions on a moving component such as the piston are challenging and expensive due to mechanical limitations. High performance computing has improved the capability of numerical techniques to predict these thermal loads with considerable accuracy. High-fidelity simulation techniques such as three-dimensional computational fluid dynamics and finite element thermal analysis were coupled offline and iterated by exchanging boundary conditions to predict the crank angle-resolved convective heat flux and surface temperature distribution on the piston of a heavy-duty diesel engine.

Substantial fuel economy improvements for light-duty automotive engines demand novel combustion strategies. Low temperature combustion (LTC) demonstrates potential for significant fuel efficiency improvement; however, control complexity is an impediment for real-world transient operation. Spark-assisted compression ignition (SACI) is an LTC strategy that applies a deflagration flame to generate sufficient energy to trigger autoignition in the remaining charge. Operating a practical engine with SACI combustion is a key modeling and control challenge. Current models are not sufficient for control-oriented work such as calibration optimization, transient control strategy development, and real-time control. This work describes the process and results of developing a fast-running control-oriented model for the autoignition phase of SACI combustion. A data-driven model is selected, specifically artificial neural networks (ANNs).

A single radiator cooling system architecture has been widely applied in ground vehicles for safe equipment (e.g., engine block, electronics, and motors) temperature control. The introduction of multiple smaller heat exchangers provides additional energy management features and alternate pathways for continued operation in case of critical subsystem failure. Although cooling performance is often designed for maximum thermal loads, systems typically operate at a fraction of the peak values for most of their life cycle. In this project, a two-radiator configuration with variable flow rates and valve positions has been mathematically modelled and experimentally validated to study its performance feasibility. A multi-node resistance-capacitance thermal model was derived using the ε−NTU approach with accompanying convective and conductive heat transfer pathways within the system.

The integration of electric motors into ground vehicle propulsion systems requires the effective removal of heat from the motor shell. As the torque demand varies based on operating cycles, the generated heat from the motor windings and stator slots must be rejected to the surroundings to ensure electric machine reliability. In this paper, an electric motor cooling system design will be optimized for a light duty autonomous vehicle. The design variables include the motor cradle volume, the number of heat pipes, the coolant reservoir dimensions, and the heat exchanger size while the cost function represents the system weight, overall size, and performance. The imposed requirements include the required heat transfer per operating cycle (6, 9, 12kW) and vehicle size, component durability requirement, and material selection. The application of a nonlinear optimization package enabled the cooling system design to be optimized.