Connected vehicle technologies have the potential to improve safety and energy efficiency. However, an efficient and robust testing framework that bridges simulations and realworld conditions is required to accelerate their validation and deployment. This paper demonstrates a streamlined approach to validating and testing connected vehicles through simulations, MicroAutobox-in-the-loop (MABx-IL) tests, MABx-vehicle-in-the-loop (MABx-VIL), and Human-MABx-VIL tests. The demonstration leverages our anything-in-the-loop (XIL) framework, which interfaces various components (e.g., simulation models, MABx, vehicle, human drivers) to evaluate connected vehicle performance in a simulated Chicago urban corridor. Our automatic model-building process has validated its flexibility, scalability, and consistency, enabling stage-by-stage progressive integration of physical components in XIL testing. Using target electric vehicle (Hyundai Ioniq 5), the Human-MABx-VIL study validated eco-speed advisory driving through a phone-based humanmachine interface (HMI), with drivers successfully performing eco-approaches to virtual signalized intersections along the road. This effort was preceded by extensive simulations, MABx-IL, and MABx-VIL, progressively swapping virtual components within the XIL framework. It underscores the necessity of streamlined validation and testing and highlights the potential of connected eco-speed advisory driving using real-time vehicle-to-everything (V2X) information.

Gasoline compression ignition (GCI) is a promising strategy to achieve high thermal efficiency and low emissions with limited modifications to the conventional diesel engine hardware. It is a partially premixed concept, which derives its superiority from higher volatility and longer ignition delay of gasoline-like fuels combined with higher compression ratio typical of diesel engines. The present study investigates the combustion process in a GCI engine operating with different injection strategies using computational fluid dynamics (CFD). Simulations are carried out on a single cylinder of a multi cylinder heavy-duty compression ignition engine, which operates at a compression ratio of 17:1 and an engine speed of 1038 rev/min. Two different injection strategies viz., late injection (LI), and early pilot injection (EP) are investigated to understand their impact on combustion and performance of the engine. Renormalized group (RNG) k-ε model is used to describe in-cylinder turbulence and KH RT model is used to simulate the fuel spray breakup. The developed CFD methodology is validated against relevant experimental data under a wide range of operating conditions for each injection strategy. The developed CFD methodology was found to capture the engine combustion behavior quite well. Based on the validated CFD model, the differences in the progress of combustion event for the two injection strategies is highlighted. It was found that a larger pilot fuel mass fraction results in a steeper rise in the initial heat release rate which in turn influences the transition to mixing controlled combustion. In line with the experimental data, the study showed that the late pilot injection strategy with three injection pulses, results in higher performance compared to the other conditions.

Using gasoline or other low reactivity fuels with a pilot injection or port fuel injection in a compression ignition engine has shown great potential in reducing NOx emissions while keeping high thermal efficiency compared to diesel. However, excessive combustion noise is caused by a high maximum pressure rise rate in the cylinder due to the higher fractions of premixed charge of the low-reactivity fuel. This noise can result in structural damage to engine components and as such, combustion noise limits the range of the operating parameters and makes the control of such engines challenging. In this study, a simulation environment was built up in MATLAB/Simulink leveraging a physics-based zero-dimension combustion model to capture the in-cylinder pressure time traces as well as metrics relevant to thermal efficiency and combustion noise. In order to also facilitate the control of emissions, machine learning models were investigated to capture NOx emissions. A kernel-based extreme learning machine (K-ELM) performed best and had a coefficient of correlation (R-squared) of 0.998. The combustion and NOx emission models are valid for not only conventional gasoline fuel but also oxygenated alternative fuel blends at three different pilot injection strategies. In order to track key combustion metrics while keeping noise and emissions within constraints, a model predictive control (MPC) was applied for a compression ignition engine operating with a range of potential fuels and fuel injection strategies. The MPC is validated under different scenarios, including a load step change, fuel type change, and injection strategy change, with proportional–integral (PI) control as the baseline. The simulation results show that MPC reduces about 26% of ringing intensity in the transient process and 17% at the steady state for E30. Generally, MPC can optimize the overall performance through modifying the main injection timing, pilot fuel mass, and exhaust gas recirculation (EGR) fraction.

Over the past couple of years, Argonne National Laboratory has tested, analyzed, and validated automobile models for the light duty vehicle class, including several types of powertrains including conventional, hybrid electric, plug-in hybrid electric and battery electric vehicles. Argonne’s previous works focused on the light duty vehicle models, but no work has been done on medium and heavy-duty vehicles. This study focuses on the validation of shifting control in advanced automatic transmission technologies for medium duty vehicles by using Argonne’s model-based high-fidelity, forward-looking, vehicle simulation tool, Autonomie. Different medium duty vehicles, from Argonne’s own fleet, including the Ram 2500, Ford F-250 and Ford F-350, were tested with the equipment for OBD (on-board diagnostics) signal data record. For the medium duty vehicles, a workflow process was used to import test data. In addition to importing measured test signals into the Autonomie environment, the process also calculated some of the critical missing signals, such as each component effort or flow signal. Numerous analysis functions have been developed to quickly analyze the shifting map, using the integrated test data in Autonomie to generate model parameters. In addition, a set of calibrations for the generic shifting algorithm was developed to match the test data. Finally, we demonstrated the validation of Autonomie transmission component models and shifting control strategy by using medium duty vehicle test data over different driving records.

Gasoline compression ignition shows great potential in reducing NOx and soot emissions with competitive thermal efficiency by leveraging the properties of gasoline fuels and the high compression ratio of compression ignition engines operating air-dilute. Meanwhile, its control becomes challenging due to not only the properties of different gasoline-type fuels but also the impacts of injection strategies on the in-cylinder reactivity. As such, a computationally efficient zero-dimension combustion model can significantly reduce the cost of control development. In this study, a previously developed zero-dimension combustion model for gasoline compression ignition was extended to multiple gasoline-type fuel blends and a port fuel injection/direct fuel injection strategy. Tests were conducted on a 12.4-liter heavy-duty engine with five fuel blends. A modification was made to the functional ignition delay model to cover the significantly different ignition delay behavior between conventional and oxygenated fuel blends. The parameters in the model were calibrated with only gasoline data at a load of 14 bar brake mean effective pressure. The results showed that this physics-based model can be applied to the other four fuel blends at three different pilot injection strategies without recalibration. For all tests, the error of the maximum pressure is within 14 bar, and that of combustion phasing and indicated mean effective pressure is within 2 CAD and 1.1 bar, respectively. In addition, the model was validated with 7 bar BMEP data and had the same level of accuracy as the 14 bar cases.

This study provides an energy consumption analysis of two prevalent micromobility vehicles: an e-scooter and an e-bike. Utilizing a custom data acquisition system, the vehicles were tested under various conditions at Argonne National Laboratory. Initial tests focused on steady-state energy consumption, while subsequent evaluations considered real-world riding conditions. Both vehicles were tested in throttle mode, eliminating human propulsion. The e-bike was also tested across three pedal-assistance levels. Results show the e-bike is roughly twice as energy-efficient as the e-scooter in most scenarios. Additionally, peak power outputs for both vehicles significantly exceeded nominal values. The study also examined the charging characteristics of each vehicle, such as efficiency and duration.

Gasoline Compression Ignition is a novel combustion concept that derives is superiority from the high compression ratio of a compression ignition engine as well as the properties of gasoline fuel, such as longer ignition delay and higher volatility compared to diesel. This combustion concept was experimentally tested on a 12.4L Class 8 truck engine which is equipped with unique features that include variable geometry turbine and variable valve actuation. Based on these experimental data, prior efforts by the authors focused on the development of an engine model for a heavy-duty engine operating on a low-reactivity fuel. This engine model was leveraged within this study to investigate a combustion control strategy at different engine conditions and injection methods and was augmented to incorporate cycle-to-cycle combustion variations. State estimation is performed by means of a Kalman filter which feeds into a model predictive controller. The model predictive controller chooses control actions based on a predefined cost function under consideration of bounds reflecting physical constraints. The engine model was utilized to establish a state–space model that serves the Kalman filter and model predictive controller for estimation and prediction. A comparative study investigating control actions and engine behavior was performed with and without limiting in-cylinder peak pressure as well as combustion noise, which is of particular interest for early pilot injection strategies. In addition, the proposed control architecture was investigated at two different levels of cycle-to-cycle variations and compared to the performance of a control structure with input disturbance rejection For increased cycle-to-cycle variations, disturbance estimation reduces state fluctuations and control effort. In general, this investigation highlights control aspects specific to a compression-ignited combustion regime with low-reactivity fuel, which heavily relies on the impact of the variable geometry turbine and variable valve actuation on states and constraints. The control algorithm is able to maintain the desired references for brake mean effective pressure and combustion phasing while controlling peak in-cylinder pressure and combustion noise.

This work focuses on zero-dimensional modeling of the heat release rate in a compression ignition engine operating on gasoline-like fuels. Due to the properties of gasoline, such as high volatility and longer ignition delay than diesel, the injection strategies can vary significantly from the operation with conventional diesel fuel. Different injection strategies are commonly used to achieve varying degrees of in-cylinder stratification in order to shape the combustion event and maximize efficiency. The proposed zero-dimensional combustion model was developed to account for the different stages in combustion caused by the fuel stratification. As the ignition delay model is an integral part of the entire combustion process and significantly affects the prediction accuracy, special attention has been paid to local phenomena influencing ignition delay. A one-dimensional spray model by Musculus and Kattke was employed in conjunction with a Lagrangian tracking approach in order to estimate the local air–fuel ratio within the spray tip, as a proxy for reactivity. The local air–fuel ratio, in-cylinder temperature and pressure were used in an integral fashion to estimate the ignition delay. Heat release rates were modeled using first-order non-linear differential equations. The proposed combustion model was validated against experimental data of a heavy-duty compression ignition engine with up to three injection events at mostly 1038 r/min and 14 bar brake mean effective pressure. Further validation of the model was carried out at other engine loads and speeds. Model prediction errors in CA50 of less than 1 °CA across all conditions were found. Modeling results of other combustion metrics such as combustion duration and indicated mean effective pressure are also highly satisfactory. In addition, the model has been shown to be capable of estimating the ringing intensity for most conditions.

Gasoline compression ignition (GCI) is a promising way to achieve high thermal efficiency and low emissions while leveraging conventional diesel engine hardware. GCI is a partially premixed combustion concept, which derives its superiority from good volatility and long ignition delay of gasoline-like fuels. The present study investigates the interaction between the piston bowl and the spray plume of a compression ignition engine that operates with a late fuel injection strategy using computational fluid dynamics (CFD) analysis. Simulations were carried out on a single cylinder of a multi-cylinder heavy-duty compression ignition engine. The engine operates at a speed of 1038 rev/min., and a compression ratio of 17. Incylinder turbulence was modelled using RNG k-ε model and the fuel spray break up was modelled using KH-RT model. A reduced chemical kinetic mechanism was used to model combustion chemistry. After validating the combustion and performance characteristics of the baseline piston against experimental results, several new piston bowl designs were generated using CAESES. Full cycle engine simulations for four selected bowl profiles were carried out. The results compare the spray-bowl interaction of the new piston bowl designs with the baseline design. It was found that the lip location and center depth of the bowl profile are the critical design parameters that influence the air utilization and heat transfer losses. The impact of spray-bowl interaction on thermal efficiency of the engine is investigated.

Gasoline compression ignition (GCI) is an emerging technology that can achieve high fuel efficiency and low criteria emissions in diesel engine platforms using gasoline and gasoline-like fuels. While low- and mid-range loads are enabled with low temperature combustion (LTC) approaches, high-loads are more efficient with high temperature combustion (HTC) requiring mixing-controlled combustion (MCC). Lower soot emissions are achieved with gasoline even in high-load MCC than with diesel, but detailed soot properties from gasoline and diesel have been rarely discussed. In order to better understand how high-load operations affect soot properties, gasoline and diesel were tested in a six-cylinder heavy duty engine at 14 bar brake mean effective pressure (BMEP) at similar combustion phasing. Effects of pilot mass ratio and EGR on heat release rates, cylinder temperatures, ignition delay (ID) and combustion duration (CD) were examined, relating with emissions variations with applications of the two fuels. Soot mass and particle number emissions were slightly lower with gasoline than with diesel, resulting in a more favorable NOx-soot trade-off with gasoline like other reports. Contrary to other findings in the literature, gasoline and diesel soot samples presented similar particle distribution shapes, carbon crystalline structures and primary particle sizes, regardless of fuel type and EGR rate. Consequently, the current result proposes that soot particles have undergone similar soot formation and oxidation processes despite reactivity difference and oxygen availability under the examined high-load MCC with similar combustion phases.

Gasoline compression ignition using a single gasoline-type fuel for direct/port injection has been shown as a method to achieve low-temperature combustion with low engine-out NO x and soot emissions and high indicated thermal efficiency. However, key technical barriers to achieving low-temperature combustion on multi-cylinder engines include the air handling system (limited amount of exhaust gas recirculation) as well as mechanical engine limitations (e.g. peak pressure rise rate). In light of these limitations, high-temperature combustion with reduced amounts of exhaust gas recirculation appears more practical. Furthermore, for high-temperature gasoline compression ignition, an effective aftertreatment system allows high thermal efficiency with low tailpipe-out emissions. In this work, experimental testing was conducted on a 12.4 L multi-cylinder heavy-duty diesel engine operating with high-temperature gasoline compression ignition combustion with port and direct injection. Engine testing was conducted at an engine speed of 1038 r/min and brake mean effective pressure of 1.4 MPa for three injection strategies, late pilot injection, early pilot injection, and port/direct fuel injection. The impact on engine performance and emissions with respect to varying the combustion phasing were quantified within this study. At the same combustion phasing, early pilot injection and port/direct fuel injection had an earlier start of combustion and higher maximum pressure rise rates than late pilot injection attributable to more premixed fuel from pilot or port injection; however, brake thermal efficiencies were higher with late pilot injection due to reduced heat transfer. Early pilot injection also exhibited the highest cylinder-to-cylinder variations due to differences in injector behavior as well as the spray/wall interactions affecting mixing and evaporation process. Overall, peak brake thermal efficiency of 46.1% and 46% for late pilot injection and port/direct fuel injection was achieved comparable to diesel baseline (45.9%), while early pilot injection showed the lowest brake thermal efficiency (45.3%).

Steady-state experiments were conducted on a 12.4L, six-cylinder heavy-duty engine to investigate the influence of port-injected water and dilution via exhaust gas recirculation (EGR) on combustion and emissions for diesel and gasoline operation. Adding a diluent to the combustion process reduces peak combustion temperatures and can reduce the reactivity of the charge, thereby increasing the ignition-delay and, allowing for more time to premix air and fuel. Experiments spanned water/fuel mass ratios up to 140mass% and exhaust gas recirculation ratios up to 20vol% for gasoline and diesel operation with different injection strategies. Diluting the combustion process with either water or EGR resulted in a significant reduction in nitrogen oxide emissions along with a reduction in brake thermal efficiency. The sensitivity of brake thermal efficiency to water and EGR varied among the fuels and injection strategies investigated. An efficiency breakdown revealed that water injection considerably reduced the wall heat transfer; however, a substantial increase in exhaust enthalpy offset the reduction in wall heat transfer and led to a reduction in brake thermal efficiency. Regular diesel operation with main and post injection exhibited a brake thermal efficiency of 45.8% and a 0.3% reduction at a water/fuel ratio of 120%. The engine operation with gasoline, early pilot, and main injection strategy showed a brake thermal efficiency of 45.0% at 0% water/fuel ratio, and a 1.2% decrease in brake thermal efficiency for a water/fuel ratio of 140%. Using EGR as a diluent reduced the brake thermal efficiency by 0.3% for diesel operation, comparing ratios of 0% and 20% EGR. However, a higher impact on brake thermal efficiency was seen for gasoline operation with early pilot and main injection strategy, with a reduction of about 0.8% comparing 0% and 20% EGR. Dilution by means of EGR exhibited a reduction in nitrogen oxide emissions up to 15 g/kWh; water injection showed only up to 10 g/kWh reduction for the EGR rates and water/fuel ratio investigated.

Gasoline compression ignition using a single gasoline-type fuel for direct/port injection has been shown as a method to achieve low temperature combustion with low engine-out NOx and soot emissions and high indicated thermal efficiency. However, key technical barriers to achieving low temperature combustion on multi-cylinder engines include the air handling system (limited amount of exhaust gas recirculation) as well as mechanical engine limitations (e.g. peak pressure rise rate). In light of these limitations, high temperature combustion with reduced amounts of exhaust gas recirculation appears more practical. Previous studies by the authors demonstrated that utilizing port and direct injection of E85 gasoline simultaneously resulted in the best performance and the highest brake thermal efficiency of 47.1%, which was 1.2% higher compared to diesel baseline. For further efficiency improvement, a better understanding of energy and exergy loss mechanisms is required. In this work, first and second law thermodynamics analysis were applied to experiments with gasoline compression ignition at an engine speed of 1038 rpm and brake mean effective pressure of 1.4 MPa on a 12.4 L multi-cylinder heavy-duty diesel engine. The impact on the efficiency, losses, and irreversibility with respect to various parameters such as fuel, injection strategy, intake condition, and port injected water mass was quantified. The peak efficiency of ideal cycles and the combined efficiency with a waste heat recovery system were also estimated in this study to assess opportunities for further efficiency gains. It was found that the combustion irreversibility was dominated by the combustion temperature rather than the fuel structure. Despite its highest brake thermal efficiency, E85 gasoline generated the highest exergy destruction due to its lowest combustion temperature. For the same reason, retarding the combustion phasing or adopting a port and direct injection strategy increased the exergy destruction. The combustion duration loss was more notable than the phasing loss and was affected by both the combustion duration and shape of heat release profile. Water port injection increased the exhaust energy, but the available energy dropped significantly attributed to the decrease in the exhaust temperature, rendering waste heat recovery ineffective. The second law analysis serves as a helpful tool in conjunction with the first law analysis to explore pathways to maximize engine efficiency.

Recent increases in natural gas supply have led to a desire to leverage this fuel in the transportation sector. Dual fuel engines provide a platform on which to use natural gas efficiently; these engines, however, require new hardware and new control strategies to properly utilize two fuels simultaneously. This paper explores the impact of implementing dual fuel capabilities on a sedan and demonstrates that a dual fuel E10 and compressed natural gas engine is able to improve the average engine efficiency by up to 6.5% compared to a single fuel engine on standard drive cycles. An optimal control technique is also developed, and the proposed approach allows factors including fuel cost and fuel availability to be taken into account. Optimization at each time instant is investigated and contrasted with optimization over the entire cycle. Cycle optimization is shown to have particular value for cases in which the level in one fuel tank is low.

One of the main factors limiting the efficiency of spark-ignited engines is the occurrence of engine knock. In high temperature and high pressure in-cylinder conditions, the fuel-air mixture auto-ignites creating pressure shock waves in the cylinder. Knock can significantly damage the engine and hinder its performance; as such, conservative knock control strategies are generally implemented that avoid such operating conditions at the cost of lower thermal efficiencies. Significant improvements in the performance of conventional knock controllers are possible if the properties of the knock process are better characterized and exploited in knock controller designs. One of the methods undertaken to better characterize knocking instances is to employ a probabilistic approach, in which the likelihood of knock is derived from the statistical distribution of knock intensity. In this paper, it is shown that knock intensity values at a fixed operating point for single fuel and dual fuel engines are accurately described using a mixed lognormal distribution. The fitting accuracy is compared against those for a randomly generated mixed-lognormally distributed data set, and shown to exceed a 95% accuracy threshold for almost all of the operating points tested. Additionally, this paper discusses a stochastic knock control approach that leverages the mixed lognormal distribution to adjust spark timing based on knock intensity measurements. This more informed knock control strategy would allow for improvements in engine performance and fuel efficiency by minimizing knock occurrences.