Search Results

Opposed piston two-stroke (OP2S) diesel engines have demonstrated a reduction in engine-out emissions and increased efficiency compared to conventional four-stroke diesel engines. Due to the higher stroke-to-bore ratio and the absence of a cylinder head, the heat transfer loss to the coolant is lower near ‘Top Dead Center.’ The selection and design of the air path is critical to realizing the benefits of the OP2S engine architecture. Like any two-stroke diesel engine, the scavenging process and the composition of the internal residuals are predominantly governed by the pressure differential between the intake and the exhaust ports. Without dedicated pumping strokes, the two-stroke engine architecture requires external devices to breathe.

Improving passenger safety inside vehicle cabins requires continuously monitoring vehicle seat occupancy statuses. Monitoring a vehicle seat’s occupancy status includes detecting if the seat is occupied and classifying the seat’s occupancy type. This paper introduces an innovative non-intrusive technique that employs capacitive sensing and an occupancy classifier to monitor a vehicle seat’s occupancy status. Capacitive sensing is facilitated by a meticulously constructed capacitance-sensing mat that easily integrates with any vehicle seat. When a passenger or an inanimate object occupies a vehicle seat equipped with the mat, they will induce variations in the mat’s internal capacitances. The variations are, in turn, represented pictorially as grayscale capacitance-sensing images (CSI), which yield the feature vectors the classifier requires to classify the seat’s occupancy type.

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.

Semiconductor devices in electric vehicle (EV) motor drive systems are considered the most fragile components with a high occurrence rate for open circuit fault (OCF). Various signal-based and model-based methods with explicit mathematical models have been previously published for OCF diagnosis. However, this proposed work presents a model-free machine learning (ML) approach for a single-switch OCF detection and localization (DaL) for a two-level, three-phase inverter. Compared to already available ML models with complex feature extraction methods in the literature, a new and simple way to extract OCF feature data with sufficient classification accuracy is proposed. In this regard, the inherent property of active thermal management (ATM) based model predictive control (MPC) to quantify the conduction losses for each semiconductor device in a power converter is integrated with an ML network.

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.

1Increasing adoption of downsized, boosted, spark-ignition engines has improved vehicle fuel economy, and continued improvement is desirable to reduce carbon emissions in the near-term. However, this strategy is limited by damaging preignition events which can cause hardware failure. Research to date has shed light on various contributing factors related to fuel and lubricant properties as well as calibration strategies, but the causal factors behind an individual preignition cycle remain elusive. If actionable precursors could be identified, mitigation through active control strategies would be possible. This paper uses artificial neural networks to search for identifiable precursors in the cylinder pressure data from a large real-world data set containing many preignition cycles. It is found that while follow-up preignition cycles in clusters can be readily predicted, the initial preignition cycle is not predictable based on features of the cylinder pressure.

This work for the Coordinating Research Council (CRC) explores dependencies on the opportunity for fuel to impinge on internal engine surfaces (i.e., fuel–wall impingement) as a function of fuel properties and engine operating conditions and correlates these data with measurements of stochastic preignition (SPI) propensity. SPI rates are directly coupled with laser–induced florescence measurements of dye-doped fuel dilution measurements of the engine lubricant, which provides a surrogate for fuel–wall impingement. Literature suggests that SPI may have several dependencies, one being fuel–wall impingement. However, it remains unknown if fuel-wall impingement is a fundamental predictor and source of SPI or is simply a causational factor of SPI. In this study, these relationships on SPI and fuel-wall impingement are explored using 4 fuels at 8 operating conditions per fuel, for 32 total test points.

Catalytic converters, which are commonly used for after-treatment in SI engines, exhibit poor performance at lower temperatures. This is one of the main reasons that tailpipe emissions drastically increase during cold-start periods. Thermal inertia of turbocharger casing prolongs the catalyst warm-up time. Exhaust enthalpy management becomes crucial for a turbocharged direct injection spark ignition (DISI) engine during cold-start periods to quickly heat the catalyst and minimize cold-start emissions. Thermal barrier coatings (TBCs), because of their low thermal inertia, reach higher surface temperatures faster than metal walls, thereby blocking heat transfer and saving enthalpy for the catalyst. The TBCs applied on surfaces that exchange heat with exhaust gases can increase the enthalpy available for the catalyst warm-up.

The application of power electronic converters (PEC) in electric vehicles (EVs) has increased immensely as they provide enhanced controllability and flexibility to these vehicles. Accordingly, the interest in developing innovative and sustainable technologies to ensure safe and reliable operation of PECs has also risen. One of the most difficult challenges experienced during the development of reliable PECs is the design of proper thermal management systems for controlling the junction temperature and reducing the thermal cycling of power semiconductors. The addition of Active Thermal Control (ATC) can mitigate these concerns. Moreover, the performance of the thermal management system can be enhanced further by the integration of active cooling methods. An active cooling system consumes external energy for circulating cooling air or liquid within the PECs.

High compression ratios are critical to increasing the efficiency of spark ignition engines, but the trend in downsized and down sped configurations has brought attention to the nominally low compression ratios used to avoid knock. Knock is an abnormal combustion event defined by the acoustic sound caused by end-gas auto-ignition ahead of the flame front. In order to avoid engine-damaging levels of knock, low compression ratios and retarded combustion phasing at high loads are used, both of which lower efficiency. Low carbon alternative fuels such as ethanol or water-based alcohol fuels combine strong chemical auto-ignition resistance with large charge cooling characteristics that can suppress knock and enable optimal combustion phasing, thus allowing an increase in the compression ratio.

Spark ignition engines have low tailpipe criteria pollutants due to their stoichiometric operation and three-way catalysis and are highly controllable. However, one of their main drawbacks is that the compression ratio is low due to knock, which incurs an efficiency penalty. With a global push towards low-lifecycle-carbon renewable fuels, high-octane alternatives to gasoline such as ethanol are attractive options as fuels for spark ignition engines. Under premixed spark ignition operating conditions, ethanol can enable higher compression ratios than regular-grade gasoline due to its high octane number. The high cooling potential of high-ethanol content gasolines, like E85, or of ethanol-water blends, like hydrous ethanol, can be leveraged to further reduce knock and enable higher compression ratios as well as further downsizing and boosting to reduce frictional and throttling losses.

With increasingly stringent regulations mandating the improvement of vehicle fuel economy, automotive manufacturers face growing pressure to develop and implement technologies that improve overall system efficiency. One such technology is an automatic (auto) stop-start feature. Auto stop-start reduces idle time and reduces fuel use by temporarily shutting the engine off when the vehicle comes to a stop and automatically re-starting it when the brake is released, or the accelerator is pressed. As mandated by the U.S. Congress, the U.S. Environmental Protection Agency (EPA) is required to keep the public informed about fuel saving practices. This is done, in partnership with the U.S. Department of Energy (DOE), through the fueleconomy.gov website. The “Fuel-Saving Technologies” and “Gas Mileage Tips” sections of the website are focused on helping the public make informed purchasing decisions and encouraging fuel-saving driving habits.

Renewable fuels, such as the alcohols, ammonia, and hydrogen, have a high autoignition resistance. Therefore, to enable these fuels in compression ignition, some modifications to existing engine architectures is required, including increasing compression ratio, adding insulation, and/or using hot internal residuals. The opposed-piston two-stroke (OP2S) engine architecture is unique in that, unlike conventional four-stroke engines, the OP2S can control the amount of trapped residuals over a wide range through its scavenging process. As such, the OP2S engine architecture is well suited to achieve compression ignition of high autoignition resistance fuels. In this work, compression ignition with wet ethanol 80 (80% ethanol, 20% water by mass) on a 3-cylinder OP2S engine is experimentally demonstrated. A load sweep is performed from idle to nearly full load of the engine, with comparisons made to diesel at each operating condition.

The development of a future hydrogen energy economy will require the development of several hydrogen market and industry segments including a hydrogen based commercial freight transportation ecosystem. For a sustainable freight transportation ecosystem, the supporting fueling infrastructure and the associated vehicle powertrains making use of hydrogen fuel will need to be co-established. This paper develops a long-term plan for refueling infrastructure deployment using the OR-AGENT (Optimal Regional Architecture Generation for Electrified National Transportation) tool developed at the Oak Ridge National Laboratory, which has been used to optimize the hydrogen refueling infrastructure requirements on the I-75 corridor for heavy duty (HD) fuel cell electric commercial vehicles (FCEV).

To achieve carbon neutrality by 2060, the Chinese government has put effort into decarbonizing the transportation sector. Consequently, China elaborated a new energy vehicle strategy promoting the production of electric vehicles and expanding into hydrogen (H2) vehicle technologies including fuel cell electric vehicles and H2 internal combustion engine vehicles. The Transportation Energy Analysis Model (TEAM) projects the market penetration as well as energy demand and greenhouse gas emissions in China up to 2050. By integrating the Monte Carlo simulation, this study tests the robustness of TEAM and investigates the key parameters that will shape passenger vehicle sales and emissions in the future. The results show that fuel cell cost, H2 price, and battery cost are the most sensitive parameters for H2 vehicle technologies.

China's plug-in electric vehicle (PEV) market with stocks at 7.8 million is the world's largest in 2021, and it accounts for half of the global PEV growth in 2021. The PEV market in China has dramatically evolved since the pandemic in 2020: over 20% of all new PEV sales are from China by mid-2022. Recent features of PEV market dynamics, consumer acceptance, policies, and infrastructure have important implications for both the global energy market and manufacturing stakeholders. From the perspective of demand pull-supply push, this study analyzes China's PEV industry with a market dynamics framework by reviewing sales, product and brand, infrastructure, and government policies from the last few years and outlooking the development of the new government’s 14th Five-Year Plan (2021-2025).

Spark ignition knock is highly sensitive to changes in intake air temperature. Hot surface temperatures due to ceramic thermal barrier coatings increase knock propensity by elevating the incoming air temperature, thus mitigating the positive impacts of low heat transfer losses by requiring spark retard to avoid knock. Low thermal inertia coatings (i.e. Temperature swing coatings) have been proposed as a means of reducing or eliminating the open cycle charge heating penalty of traditional TBCs through a combination of low thermal conductivity and low volumetric heat capacity materials. However, in order to achieve a meaningful gain in efficiency, a significant fraction of the combustion chamber must be coated. In this study, a coated piston and intake and exhaust valves with coated combustion faces, backsides, and stems are installed in a single-cylinder research engine to evaluate the effect of high coated fractions of the combustion chamber in a knock-sensitive architecture.

Gasoline knock resistance is characterized by the Research and Motor Octane Number (RON and MON), which are rated on the CFR octane rating engine at naturally aspirated conditions. However, modern automotive downsized boosted spark ignition (SI) engines generally operate at higher cylinder pressures and lower temperatures relative to the RON and MON tests. Using the naturally aspirated RON and MON ratings, the octane index (OI) characterizes the knock resistance of gasolines under boosted operation by linearly extrapolating into boosted “beyond RON” conditions via RON, MON, and a linear regression K factor. Using OI solely based on naturally aspirated RON and MON tests to extrapolate into boosted conditions can lead to significant errors in predicting boosted knock resistance between gasolines due to non-linear changes in autoignition and knocking characteristics with increasing pressure conditions.

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.

The US Department of Energy’s Co-Optimization of Engine and Fuels Initiative (Co-Optima) investigated how unique properties of bio-blendstocks considered within Co-Optima help address emissions challenges with mixing controlled compression ignition (i.e., conventional diesel combustion) and enable advanced compression ignition modes suitable for implementation in a diesel engine. Additionally, the potential synergies of these Co-Optima technologies in hybrid vehicle applications in the medium- and heavy-duty sector was also investigated. In this work, vehicles system were simulated using the Autonomie software tool for quantifying the benefits of Co-Optima engine technologies for medium-duty trucks. A Class 6 delivery truck with a 6.7 L diesel engine was used for simulations over representative real-world and certification drive cycles with four different powertrains to investigate fuel economy, criteria emissions, and performance.