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The use of virtual prototyping early in the design stage of a product has gained popularity due to reduced cost and time to market. The state of the art in vehicle simulation has reached a level where full vehicles are analyzed through simulation but major difficulties continue to be present in interfacing the vehicle model with accurate powertrain models and in developing adequate formulations for the contact between tire and terrain (specifically, scenarios such as tire sliding on ice and rolling on sand or other very deformable surfaces). The proposed work focuses on developing a ground vehicle simulation capability by combining several third party packages for vehicle simulation, tire simulation, and powertrain simulation. The long-term goal of this project consists in promoting the Digital Car idea through the development of a reliable and robust simulation capability that will enhance the understanding and control of off-road vehicle performance.

In order to reduce fuel consumption, companies have been looking at hybridizing vehicles. So far, two main hybridization options have been considered: electric and hydraulic hybrids. Because of light duty vehicle operating conditions and the high energy density of batteries, electric hybrids are being widely used for cars. However, companies are still evaluating both hybridization options for medium and heavy duty vehicles. Trucks generally demand very large regenerative power and frequent stop-and-go. In that situation, hydraulic systems could offer an advantage over electric drive systems because the hydraulic motor and accumulator can handle high power with small volume capacity. This study compares the fuel displacement of class 6 trucks using a hydraulic system compared to conventional and hybrid electric vehicles. The paper will describe the component technology and sizes of each powertrain as well as their overall vehicle level control strategies.

A Vehicle-Engine-Cooling (VEC) system computer simulation model was used to study the transient performance of control devices and their temperature settings on oil, coolant and cab temperatures. The truck used in the study was an International Harvester COF-9670 cab over chassis heavy-duty vehicle equipped with a standard cab heater, a Cummins NTC-350 diesel engine with a McCord radiator and standard cooling system components and aftercooler. Input data from several portions of a Columbus to Bloomington, Indiana route were used from the Vehicle Mission Simulation (VMS) program to determine engine and vehicle operating conditions for the VEC system computer simulation model. The control devices investigated were the standard thermostat, the Kysor fan-clutch and shutter system. The effect of shutterstat location on shutter performance along with thermostat, shutter and fan activation temperature settings were investigated for ambient temperatures of 32, 85 and 100°F.

A computational fluid dynamics (CFD) guided combustion system optimization was conducted for a heavy-duty diesel engine running with a gasoline fuel that has a research octane number (RON) of 80. The goal was to optimize the gasoline compression ignition (GCI) combustion recipe (piston bowl geometry, injector spray pattern, in-cylinder swirl motion, and thermal boundary conditions) for improved fuel efficiency while maintaining engine-out NOx within a 1-1.5 g/kW-hr window. The numerical model was developed using the multi-dimensional CFD software CONVERGE. A two-stage design of experiments (DoE) approach was employed with the first stage focusing on the piston bowl shape optimization and the second addressing refinement of the combustion recipe. For optimizing the piston bowl geometry, a software tool, CAESES, was utilized to automatically perturb key bowl design parameters. This led to the generation of 256 combustion chamber designs evaluated at several engine operating conditions.

A computational fluid dynamics (CFD) guided combustion system optimization was conducted for a heavy-duty compression-ignition engine with a gasoline-like fuel that has an anti-knock index (AKI) of 58. The primary goal was to design an optimized combustion system utilizing the high volatility and low sooting tendency of the fuel for improved fuel efficiency with minimal hardware modifications to the engine. The CFD model predictions were first validated against experimental results generated using the stock engine hardware. A comprehensive design of experiments (DoE) study was performed at different operating conditions on a world-leading supercomputer, MIRA at Argonne National Laboratory, to accelerate the development of an optimized fuel-efficiency focused design while maintaining the engine-out NOx and soot emissions levels of the baseline production engine.

To properly compare and contrast the environmental performance of one vehicle technology against another, it is necessary to consider their production, operation, and end-of-life fates. Since 1995, Argonne’s GREET® life cycle analysis model (Greenhouse gases, Regulated Emissions, and Energy use in Technologies) has been annually updated to model and refine the latest developments in fuels and materials production, as well as vehicle operational and composition characteristics. Updated cradle-to-grave life cycle analysis results from the model’s latest release are described for a wide variety of fuel and powertrain options for U.S. light-duty and medium/heavy-duty vehicles. Light-duty vehicles include a passenger car, sports utility vehicle (SUV), and pick-up truck, while medium/heavy-duty vehicles include a Class 6 pickup-and-delivery truck, Class 8 day-cab (regional) truck, and Class 8 sleeper-cab (long-haul) truck.

This paper describes a configuration and controller, designed using Autonomie,1 for dual-motor battery electric vehicle (BEV) heavy-duty trucks. Based on the literature and current market research, this model was designed with two electric motors, one on the front axle and the other on the rear axle. A rule-based control algorithm was designed for the new dual-motor BEV, based on the model, and the control parameters were optimized by using a genetic algorithm (GA). The model was simulated in diverse driving cycles and gradeability tests. The results show both a good following of the desired cycle and achievement of truck gradeability performance requirements. The simulation results were compared with those of a single-motor BEV and showed reduced energy consumption with the high-efficiency operation of the two motors.

A computer simulation program was developed to simulate the thermal responses of an on-highway, heavy duty diesel powered truck in transient operation for evaluation of cooling system performance. Mathematical models of the engine, heat exchangers, lubricating oil system, thermal control sensors (thermostat and shutterstat), auxiliary components, and the cab were formulated and calibrated to laboratory experimental data. The component models were assembled into the vehicle engine cooling system model and used to predict air-to-boil temperatures. The model has the capability to predict real time coolant, oil and cab temperatures using vehicle simulation input data over various routes.

Low temperature combustion through in-cylinder blending of fuels with different reactivity offers the potential to improve engine efficiency while yielding low engine-out NOx and soot emissions. A Navistar MaxxForce 13 heavy-duty compression ignition engine was modified to run with two separate fuel systems, aiming to utilize fuel reactivity to demonstrate a technical path towards high engine efficiency. The dual-fuel engine has a geometric compression ratio of 14 and uses sequential, multi-port-injection of a low reactivity fuel in combination with in-cylinder direct injection of diesel. Through control of in-cylinder charge reactivity and reactivity stratification, the engine combustion process can be tailored towards high efficiency and low engine-out emissions. Engine testing was conducted at 1200 rpm over a load sweep.

In this last decade, non-destructive X-ray measurement techniques have provided unique insights into the internal surface and flow characteristics of automotive injectors. This has in turn contributed to enhancing the accuracy of Computational Fluid Dynamics (CFD) models of these critical injection system components. By employing realistic injector geometries in CFD simulations, designers and modelers have identified ways to modify the injectors’ design to improve their performance. In recent work, the authors investigated the occurrence of cavitation in a heavy-duty multi-hole diesel injector operating with a high-volatility gasoline-like fuel for gasoline compression ignition applications. They proposed a comprehensive numerical study in which the original diesel injector design would be modified with the goal of suppressing the in-nozzle cavitation that occurs when gasoline fuels are used.

The cooling system of a Class 8 truck engine was modeled using the Flowmaster computer code. Numerical simulations were performed replacing the standard coolant, 50/50 mixture of ethylene-glycol and water, with nanofluids comprised of CuO nanoparticles suspended in a base fluid of a 50/50 mixture of ethylene-glycol and water. By using engine and cooling system parameters from the standard coolant case, the higher heat transfer coefficients of the nanofluids resulted in lower engine and coolant temperatures. These temperature reductions introduced flexibility in system parameters - three of which were investigated for performance improvement: engine power, coolant pump speed and power, and radiator air-side area.

A new concept for an efficient radiator-cooling system is presented for reducing the size or increasing the cooling capacity of vehicle coolant radiators. Under certain conditions, the system employs active evaporative cooling in addition to conventional finned air cooling. In this regard, it is a hybrid radiator-cooling system comprised of the combination of conventional air-side finned surface cooling and active evaporative water cooling. The air-side finned surface is sized to transfer required heat under all driving conditions except for the most severe. In the later case, evaporative cooling is used in addition to the conventional air-side finned surface cooling. Together the two systems transfer the required heat under all driving conditions. However, under most driving conditions, only the air-side finned surface cooling is required. Consequently, the finned surface may be smaller than in conventional radiators that utilize air-side finned surface cooling exclusively.

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.

Cyclic variability in internal combustion engines (ICEs) arises from multiple concurrent sources, many of which remain to be fully understood and controlled. This variability can, in turn, affect the behavior of the engine resulting in undesirable deviations from the expected operating conditions and performance. Shot-to-shot variation during the fuel injection process is strongly suspected of being a source of cyclic variability. This study focuses on the shot-to-shot variability of injector needle motion and its influence on the internal nozzle flow behavior using diesel fuel. High-speed x-ray imaging techniques have been used to extract high-resolution injector geometry images of the sac, orifices, and needle tip that allowed the true dynamics of the needle motion to emerge. These measurements showed high repeatability in the needle lift profile across multiple injection events, while the needle radial displacement was characterized by a much higher degree of randomness.

Diesel Oxidation Catalysts (DOC) are used on heavy duty diesel engine applications and experience large internal temperature variations from 150 to 600°C. The DOC oxidizes the CO and HC in the exhaust to CO2 and H2O and oxidizes NO to NO2. The oxidation reactions are functions of its internal temperatures. Hence, accurate estimation of internal temperatures is important both for onboard diagnostic and aftertreatment closed loop control strategies. This paper focuses on the development of a reduced order model and an Extended Kalman Filter (EKF) state estimator for a DOC. The reduced order model simulation results are compared to experimental data. This is important since the reduced order model is used in the EKF estimator to predict the CO, NO, NO2 and HC concentrations in the DOC and at the outlet. The estimator was exercised using transient drive cycle engine data. The closed loop EKF improves the temperature estimate inside the DOC compared to the open loop estimator.

Fan and fan-shroud design is critical for underhood air flow management. The objective of this work is to demonstrate a method to optimize fan-shroud shape in order to maximize cooling air mass flow rates through the heat exchangers using the Adjoint Solver in STAR-CCM+®. Such techniques using Computational Fluid Dynamics (CFD) analysis enable the automotive/transport industry to reduce the number of costly experiments that they perform. This work presents the use of CFD as a simulation tool to investigate and assess the various factors that can affect the vehicle thermal performance. In heavy-duty trucks, the cooling package includes heat exchangers, fan-shroud, and fan. In this work, the STAR-CCM+® solver was selected and a java macro built to run the primal flow and the Adjoint solutions sequentially in an automated fashion.

This study presents a process to quantify the fuel saving potential of electrified powertrains for medium and heavy duty vehicles. For this study, equivalent vehicles with electrified powertrains are designed with the underlying principle of not compromising on cargo carrying capacity or performance. Several performance characteristics, that are relevant for all types of medium and heavy duty vehicles, were identified for benchmarking based on the feedback from the industry. Start-stop hybrids, parallel pre-transmission hybrids, plug-in hybrids, and battery electric vehicles are the technology choices in this study. This paper uses one vehicle as an example, explains the component sizing process followed for each powertrain, and examines each powertrain’s fuel saving potential. The process put forth in this paper can be used for evaluating vehicles that belong to all medium and heavy duty classes.

Dual-fuel combustion using port-injected gasoline with a direct diesel injection has been shown to achieve low-temperature combustion with moderate peak pressure rise rates, low engine-out soot and NOx emissions, and high indicated thermal efficiency. A key requirement for extending high-load operation is moderating the reactivity of the premixed charge prior to the diesel injection. Reducing compression ratio, in conjunction with a higher expansion ratio using alternative valve timings, decreases compressed charge reactivity while maintain a high expansion ratio for maximum work extraction. Experimental testing was conducted on a 13L multi-cylinder heavy-duty diesel engine modified to operate dual-fuel combustion with port gasoline injection to supplement the direct diesel injection. The engine employs intake variable valve actuation (VVA) for early (EIVC) or late (LIVC) intake valve closing to yield reduced effective compression ratio.

A novel approach to the Integration of Turbocompounding/WHR, Electrification and Supercharging technologies (ITES) to reduce fuel consumption in a medium heavy-duty diesel engine was previously published by FEV. This paper describes a modified approach to ITES to reduce fuel consumption on a heavy-duty diesel engine applied in a Class 8 tractor. The original implementation of the ITES incorporated a turbocompound turbine as the means for waste heat recovery. In this new approach, the turbocompound unit connected to the sun gear of the planetary gear set has been replaced by an organic Rankine cycle (ORC) turbine expander. The secondary compressor and the electric motor-generator are connected to the ring gear and the carrier gear respectively. The ITES unit is equipped with dry clutch and band brake allowing flexibility in mechanical and electrical integration of the ORC expander, secondary compressor and electric motor-generator to the engine.

The combustion system of a heavy-duty diesel engine operated in a gasoline compression ignition mode was optimized using a CFD-based response surface methodology and a machine learning genetic algorithm. One common dataset obtained from a CFD design of experiment campaign was used to construct response surfaces and train machine learning models. 128 designs were included in the campaign and were evaluated across three engine load conditions using the CONVERGE CFD solver. The design variables included piston bowl geometry, injector specifications, and swirl ratio, and the objective variables were fuel consumption, criteria emissions, and mechanical design constraints. In this study, the two approaches were extensively investigated and applied to a common dataset. The response surface-based approach utilized a combination of three modeling techniques to construct response surfaces to enhance the performance of predictions.