Search Results

The transition from combustion engines to electric propulsion is accelerating in every coordinate of the globe. The engineers had strived hard to augment the engine performance for more than eight decades, and a similar challenge had emerged again for electric vehicles. To analyze the performance of the engine, the vector engine operating point (EOP) is defined, which is common industry practice, and the performance vector electric vehicle motor operating point (EVMOP) is not explored in the existing literature. In an analogous sense, electric vehicles are embedded with three primary components, e.g., Battery, Inverter, Motor, and in this article, the EVMOP is defined using the parameters [motor torque, motor speed, motor current]. As a second aspect of this research, deep learning models are developed to predict the EVMOP by mapping the parameters representing the dynamic state of the system in real-time.

Making manned and remotely-controlled wheeled and tracked vehicles easier to drive, especially off-road, is of great interest to the U.S. Army. If vehicles are easier to drive (especially closed hatch) or if they are driven autonomously, then drivers could perform additional tasks (e.g., operating weapons or communication systems), leading to reduced crew sizes. Further, poorly driven vehicles are more likely to get stuck, roll over, or encounter mines or improvised explosive devices, whereby the vehicle can no longer perform its mission and crew member safety is jeopardized. HMI technology and systems to support human drivers (e.g., autonomous driving systems, in-vehicle monitors or head-mounted displays, various control devices (including game controllers), navigation and route-planning systems) need to be evaluated, which traditionally occurs in mission-specific (and incomparable) evaluations.

The automotive industry widely accepted the launch of electric vehicles in the global market, resulting in the emergence of many new areas, including battery health, inverter design, and motor dynamics. Maintaining the desired thermal stress is required to achieve augmented performance along with the optimal design of these components. The HVAC system controls the coolant and refrigerant fluid pressures to maintain the temperatures of [Battery, Inverter, Motor] in a definite range. However, identifying the prominent factors affecting the thermal stress of electric vehicle components and their effect on temperature variation was not investigated in real-time. Therefore, this article defines the vector electric vehicle thermal operating point (EVTHOP) as the first step with three elements [instantaneous battery temperature, instantaneous inverter temperature, instantaneous stator temperature].

Prior work in the literature have shown that pre-chamber spark plug technologies can provide remarkable improvements in engine performance. In this work, three passively fueled pre-chamber spark plugs with different pre-chamber geometries were investigated using in-cylinder high-speed imaging of spectral emission in the visible wavelength region in a single-cylinder direct-injection spark-ignition gasoline engine. The effects of the pre-chamber spark plugs on flame development were analyzed by comparing the flame progress between the pre-chamber spark plugs and with the results from a conventional spark plug. The engine was operated at fixed conditions (relevant to federal test procedures) with a constant speed of 1500 revolutions per minute with a coolant temperature of 90 oC and stoichiometric fuel-to-air ratio. The in-cylinder images were captured with a color high-speed camera through an optical insert in the piston crown.

As new technology is added to vehicles and traffic congestion increases, there is a concern that drivers will be overloaded. As a result, there has been considerable interest in measuring driver workload. This can be achieved using many methods, with subjective assessments such as the NASA Task Loading Index (TLX) being most popular. Unfortunately, the TLX is unanchored, so there is no way to compare TLX values between studies, thus limiting the value of those evaluations. In response, a method was created to anchor overall workload ratings. To develop this method, 24 subjects rated the workload of clips of forward scenes collected while driving on rural, urban, and limited-access roads in relation to 2 looped anchor clips. Those clips corresponded to Level of Service (LOS) A and E (light and heavy traffic) and were assigned values of 2 and 6 respectively.

Tanker trucks are commonly used for transporting liquid material including chemical and petroleum products. On the one hand, tanker trucks are susceptible to rollover accidents due to the high center of gravity when they are loaded and due to the liquid sloshing effects when the tank is partially filled. On the other hand, tanker truck rollover accidents are among the most dangerous vehicle crashes, frequently resulting in serious to fatal driver injuries and significant property damage, because the liquid cargo is often hazardous and flammable. Therefore, effective schemes for tanker truck rollover avoidance are highly desirable and can bring a considerable amount of societal benefit. Yet, the development of such schemes is challenging, as tanker trucks can operate in various environments and be affected by manufacturing variability, aging, degradation, etc. This paper considers the use of Learning Reference Governor (LRG) for tanker truck rollover avoidance.

An experimental investigation of non-intrusive combustion sensing was performed using a tri-axial accelerometer mounted to the engine block of a small-bore high-speed 4-cylinder compression-ignition direct-injection (CIDI) engine. This study investigates potential techniques to extract combustion features from accelerometer signals to be used for cycle-to-cycle engine control. Selection of accelerometer location and vibration axis were performed by analyzing vibration signals for three different locations along the block for all three of the accelerometer axes. A magnitude squared coherence (MSC) statistical analysis was used to select the best location and axis. Based on previous work from the literature, the vibration signal filtering was optimized, and the filtered vibration signals were analyzed. It was found that the vibration signals correlate well with the second derivative of pressure during the initial stages of combustion.

The article solves the problem of reducing electric power losses of the traction induction machine rotor to prevent its overheating in nominal and high-load modes. Electric losses of the rotor power are optimized by the stabilization of the main magnetic flow of the electric machine at a nominal level with the amplitude-frequency control in a wide range of speeds and increased loads. The quasi-independent excitation of the induction machine allows us to increase the rigidity of mechanical characteristics, decrease the rotor slip at nominal loads and overloads and significantly decrease electrical losses in the rotor as compared to other control methods. The article considers the technology of converting the power of individual phases into a single energy flow using a three-phase electric machine equivalent circuit and obtaining an energy model in the form of equations of instantaneous active and reactive power balance.

This paper presents an experimental investigation of the impact of EGR dilution on the tradeoff between flame and end-gas autoignition heat release in a Spark-Assisted Compression Ignition (SACI) combustion engine. The mixture was maintained stoichiometric and fuel-to-charge equivalence ratio (ϕ′) was controlled by varying the EGR dilution level at constant engine speed. Under all conditions investigated, end-gas autoignition timing was maintained constant by modulating the mixture temperature and spark timing. Experiments at constant intake pressure and constant spark timing showed that as ϕ′ is increased, lower mixture temperatures are required to match end-gas autoignition timing. Higher ϕ′ mixtures exhibited faster initial flame burn rates, which were attributed to the higher laminar flame speeds immediately after spark timing and their effect on the overall turbulent burning velocity.

In order to improve the steering stability of the dual-motor drive electric vehicle, Taking the yaw rate and the sideslip angle as the control variables, Using the improved two degree of freedom linear dynamic model and seven degree of freedom nonlinear vehicle dynamics model, The hierarchical structure is used to establish the dual-motor drive electric vehicle steering stability control strategy which consist of the upper direct yaw moment decision-making layer based on the sliding mode controller and the lower additional yaw moment distribution layer based on the optimization theory. The Matlab/Simulink-Carsim joint simulation platform was built. The control strategy proposed in this paper was simulated and verified under the snake test condition and double-line shift test condition.

There is a pressing need to develop accurate and robust approaches for predicting vehicle speed to enhance fuel economy/energy efficiency, drivability and safety of automotive vehicles. This paper details outcomes of research into various methods for the prediction of vehicle velocity. The focus is on short-term predictions over 1 to 10 second prediction horizon. Such short-term predictions can be integrated into a hybrid electric vehicle energy management strategy and have the potential to improve HEV energy efficiency. Several deterministic and stochastic models are considered in this paper for prediction of future vehicle velocity. Deterministic models include an Auto-Regressive Moving Average (ARMA) model, a Nonlinear Auto-Regressive with eXternal input (NARX) shallow neural network and a Long Short-Term Memory (LSTM) deep neural network. Stochastic models include a Markov Chain (MC) model and a Conditional Linear Gaussian (CLG) model.

As European and Chinese tailpipe emission regulations for gasoline light-duty vehicles impose particulate number limits, automotive manufacturers have begun equipping some vehicles with a gasoline particulate filter (GPF). Increased understanding of how soot morphology, reactivity, and GPF loading affect GPF filtration and regeneration characteristics is necessary for advancing GPF performance. This study investigates the impacts of morphology, reactivity, and filter soot loading on GPF filtration and regeneration. Soot morphology and reactivity are varied through changes in fuel injection parameters, known to affect soot formation conditions. Changes in morphology and reactivity are confirmed through analysis using a transmission electron microscope (TEM) and a thermogravimetric analyzer (TGA) respectively.

Combined direct and port fuel injection (i.e., dual injection) in spark ignition engines is of increasing interest due to the advantages for fuel flexibility and the individual merits of each system for improving engine performance and reducing engine-out emissions. Greater understanding of the impact of dual injection will enable deriving the maximum benefit from the two injection systems. This study investigates the effects of dual injection on combustion, especially knock propensity and tolerance to exhaust gas recirculation (EGR) dilution at different levels of EGR. A baseline for comparison with dual injection results was made using direct injection fueling only. A splash blended E20 fuel was used for the direct injection only tests. For the dual injection tests, gasoline, representing 80% by volume of the total fuel, was injected using the direct injector, and ethanol, representing 20% by volume of the total fuel, was injected using the port fuel injector.

Large-eddy simulations (LES) of a motoring single-cylinder engine with transparent combustion chamber (TCC-II) are carried out using a commercially available computer code, CONVERGE. Numerical predictions are compared with high-speed particle image velocimetry (PIV) measurements. Predictions of two spatial discretization schemes, namely, numerically stabilized central difference scheme (CDS) and fully upwind scheme are compared. Four different subgrid scale (SGS) models; a non-eddy viscosity dynamic structure turbulence (DST) model of Pomraning and Rutland, one-equation eddy-viscosity (1-Eqn) model of Menon et al., a zeroequation eddy-viscosity model of Vreman, and the zeroequation standard Smagorinsky model are employed on two different grid configurations. Additionally, simulations are also performed by deactivating the LES SGS models. It is found that the predictions when using the numerically stabilized CDS are significantly better than using the fully upwind scheme.

Non-reacting spray behaviors of the Engine Combustion Network “Spray G” gasoline fuel injector were investigated at flash and non-flash boiling conditions in an optically accessible single cylinder engine and a constant volume spray chamber. High-speed Mie-scattering imaging was used to determine transient liquid-phase spray penetration distances and observe general spray behaviors. The standardized “G2” and “G3” test conditions recommended by the Engine Combustion Network were matched in this work and the fuel was pure iso-octane. Results from the constant volume chamber represented the zero (stationary piston) engine speed condition and single cylinder engine speeds ranged from 300 to 2,000 RPM. As expected, the present results indicated the general spray behaviors differed significantly between the spray chamber and engine. The differences must be thoughtfully considered when applying spray chamber results to guide spray model development for engine applications.

Nozzle length has been proven influencing fuel spray characteristics, and subsequently fuel-air mixing and combustion processes. However, almost all existing related studies are conducted when fuel is subcooled, of which fuel evaporation is extremely weak, especially at the near nozzle region. In addition, injector tip can be heated to very high temperature in SIDI engines, which would trigger flash boiling fuel spray. Therefore, in this study, effect of nozzle length on spray characteristics is investigated under superheated conditions. Three single-hole injectors with different nozzle length were studied. High speed backlit imaging technique was applied to acquire magnified near nozzle spray images based on an optical accessible constant volume chamber. Fuel pressure was maintained at 15 MPa, and n-hexane was chosen as test fuel.

This paper provides insight into the tradeoffs between exhaust energy recovery and increased pumping losses from the flow restriction of the electric turbo-generator (eTG) assessed using thermodynamic principles and with a detailed GT-Power engine model. The GT-Power engine model with a positive displacement expander model was used to predict the influence of back pressure on in-cylinder residuals and combustion. The eTG is assessed for two boosting arrangements: a conventional turbocharger (TC) and an electrically assisted variable speed (EAVS) supercharger (SC). Both a low pressure (post-turbine) and high pressure (pre-turbine) eTG are considered for the turbocharged configuration. The reduction in fuel consumption (FC) possible over various drive cycles is estimated based on the steady-state efficiency of frequently visited operating points assuming all recovered energy can be reused at an engine efficiency of 30% with 10% losses in the electrical path.

Optical imaging diagnostics of combustion are most often performed in the visible spectral band, in part because camera technology is most mature in this region, but operating in the infrared (IR) provides a number of benefits. These benefits include access to emission lines of relevant chemical species (e.g. water, carbon dioxide, and carbon monoxide) and obviation of image intensifiers (avoiding reduced spatial resolution and increased cost). High-speed IR in-cylinder imaging and image processing were used to investigate the relationships between infrared images, quantitative image-derived metrics (e.g. location of the flame centroid), and measurements made with in-cylinder pressure transducers (e.g. coefficient of variation of mean effective pressure). A 9.7-liter, inline-six, natural-gas-fueled engine was modified to enable exhaust-gas recirculation (EGR) and provide borescopic optical access to one cylinder for two high-speed infrared cameras.

The turbulent in-cylinder air flow and the unsteady high-pressure fuel injection lead to a highly transient air fuel mixing process in spark-ignition direct-injection (SIDI) engines, which is the leading cause for combustion cycle-to-cycle variation (CCV) and requires further investigation. In this study, crank-angle resolution particle image velocimetry (PIV) was employed to simultaneously measure the air flow and fuel spray structure at 1300 rpm in an optically accessible single-cylinder SIDI engine. The measurement was conducted at the center tumble plane of the four-valve pent-roof engine, bisecting the spark plug and fuel injector. 84 consecutive cycles were recorded for three engine conditions, i.e. (1) none-fueled motored condition, (2) homogeneous-charge mode with start of injection (SOI) during intake (50 crank-angle degree (CAD) after top dead center exhaust, aTDCexh), and (3) stratified-charge mode with SOI during mid compression (270 aTDCexh).

High-pressure gasoline fuel injection is a means to improve combustion efficiency and lower engine-out emissions. The objective of this study was to quantify the effects of fuel injection pressure on transient gasoline fuel spray development for a wide range of injection pressures, including over 1000 bar, using a constant volume chamber and high-speed imaging. Reference grade gasoline was injected at fuel pressures of 300, 600, 900, 1200, and 1500 bar into the chamber, which was pressurized with nitrogen at 1, 5, 10, and 20 bar at room temperature (298 K). Bulk spray imaging data were used to quantify spray tip penetration distance, rate of spray tip penetration and spray cone angle. Near-nozzle data were used to evaluate the early spray development.