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ERRATUM: In the article Reference 24 should read as follows: 24. Han, T., Booth, A., Song, S., Styles, D., and Hoard, J., “Review and A Conceptual Model of Exhaust Gas Recirculation (EGR) Cooler Fouling Deposition and Removal Mechanism” Proceedings of the Int. Conf. on Heat Exchanger Fouling and Cleaning, 2015”

Premixed Charge Compression Ignition (PCCI), a Low Temperature Combustion (LTC) strategy for diesel engines is of increasing interest due to its potential to simultaneously reduce soot and NOx emissions. However, the influence of mixture preparation on combustion phasing and heat release rate in LTC is not fully understood. In the present study, the influence of injection timing on mixture preparation, combustion and emissions in PCCI mode is investigated by experimental and computational methods. A sequential coupling approach of 3D CFD with a Stochastic Reactor Model (SRM) is used to simulate the PCCI engine. The SRM accounts for detailed chemical kinetics, convective heat transfer and turbulent micro-mixing. In this integrated approach, the temperature-equivalence ratio statistics obtained using KIVA 3V are mapped onto the stochastic particle ensemble used in the SRM.

EGR coolers are effective to reduce NOx emissions from diesel engines due to lower intake charge temperature. EGR cooler fouling reduces heat transfer capacity of the cooler significantly and increases pressure drop across the cooler. Engine coolant provided at 40–90 C is used to cool EGR coolers. The presence of a cold surface in the cooler causes particulate soot deposition and hydrocarbon condensation. The experimental data also indicates that the fouling is mainly caused by soot and hydrocarbons. In this study, a 1-D model is extended to simulate particulate soot and hydrocarbon deposition on a concentric tube EGR cooler with a constant wall temperature. The soot deposition caused by thermophoresis phenomena is taken into account the model. Condensation of a wide range of hydrocarbon molecules are also modeled but the results show condensation of only heavy molecules at coolant temperature.

Engine and flow reactor experiments were conducted to determine the impact of biodiesel relative to ultra-low-sulfur diesel (ULSD) on inhibition of the selective catalytic reduction (SCR) reaction over an Fe-zeolite catalyst. Fe-zeolite SCR catalysts have the ability to adsorb and store unburned hydrocarbons (HC) at temperatures below 300°C. These stored HCs inhibit or block NOx-ammonia reaction sites at low temperatures. Although biodiesel is not a hydrocarbon, similar effects are anticipated for unburned biodiesel and its organic combustion products. Flow reactor experiments indicate that in the absence of exposure to HC or B100, NOx conversion begins at between 100° and 200°C. When exposure to unburned fuel occurs at higher temperatures (250°-400°C), the catalyst is able to adsorb a greater mass of biodiesel than of ULSD. Experiments show that when the catalyst is masked with ULSD, NOx conversion is inhibited until it is heated to 400°C.

Since transient vehicle HVAC computational fluids (CFD) simulations take too long to solve in a production environment, the goal of this project is to automatically create a lumped-parameter flow network from a steady-state CFD that solves nearly instantaneously. The data mining algorithm k-means is implemented to automatically discover flow features and form the network (a reduced order model). The lumped-parameter network is implemented in the commercial thermal solver MuSES to then run as a fully transient simulation. Using this network a “localized heat transfer coefficient” is shown to be an improvement over existing techniques. Also, it was found that the use of the clustering created a new flow visualization technique. Finally, fixing clusters near equipment newly demonstrates a capability to track localized temperatures near specific objects (such as equipment in vehicles).

The study of spray-wall interaction is of great importance to understand the dynamics that occur during fuel impingement onto the chamber wall or piston surfaces in internal combustion engines. It is found that the maximum spreading length of an impinged droplet can provide a quantitative estimation of heat transfer and energy transformation for spray-wall interaction. Furthermore, it influences the air-fuel mixing and hydrocarbon and particle emissions at combusting conditions. In this paper, an analytical model of a single diesel droplet impinging on the wall with different inclined angles (α) is developed in terms of βm (dimensionless maximum spreading length, the ratio of maximum spreading length to initial droplet diameter) to understand the detailed impinging dynamic process.

Exhaust gas recirculation (EGR) coolers are used on diesel engines to reduce peak in-cylinder flame temperatures, leading to less NOx formation during the combustion process. There is an ongoing concern with soot and hydrocarbon fouling inside the cold surface of the cooler. The fouling layer reduces the heat transfer efficiency and causes pressure drop to increase across the cooler. A number of experimental studies have demonstrated that the fouling layer tends to asymptotically approach a critical height, after which the layer growth ceases. One potential explanation for this behavior is the removal mechanism derived by the shear force applied on the soot and hydrocarbon deposit surface. As the deposit layer thickens, shear force applied on the fouling surface increases due to the flow velocity growth. When a critical shear force is applied, deposit particles start to get removed.

Control of vehicle powertrain thermal management systems is becoming more challenging as the number of components is growing, and as a result, advanced control methods are being investigated. Model predictive control (MPC) is particularly interesting in this application because it provides a suitable framework to manage actuator and temperature constraints, and can potentially leverage preview information if available in the future. In previous SAE publications (2015-01-0336 and 2016-01-0215), a robust MPC control formulation was proposed, and both simulation and powertrain thermal lab test results were provided. In this work, we discuss the controller deployment in a vehicle; where controller validation is done through road driving and on a wind tunnel chassis dynamometer. This paper discusses challenges of linear MPC implementation related to nonlinearities in this over-actuated thermal system.

With the trending electrification of vehicle accessory drives brings new control concepts useful in many cases to optimize energy management within the powertrain system. Considering that direct engine drives do not have as much flexibility as independent electric drives, it is apparent that several advantages are to be expected from electric drives. New developed high efficient electric drives can be implemented when considering many vehicle sub-systems. Combinations of continuous varying and discrete flow control devices offer thermal management opportunities across several vehicle attributes including fuel economy, drivability, performance, and cabin comfort. Often new technologies are integrated with legacy systems to deliver maximum value. Leveraging both electrical and mechanical actuators in some cases presents control challenges in optimizing energy management while delivering robust system operation.

Hybrid Electric Vehicles (HEV) utilize a High Voltage (HV) battery pack to improve fuel economy by maximizing the capture of vehicle kinetic energy for reuse. Consequently, these HV battery packs experience frequent and rapid charge-discharge cycles. The heat generated during these cycles must be managed effectively to maintain battery cell performance and cell life. The HV battery pack cooling system must keep the HV battery pack temperature below a design target value and maintain a uniform temperature across all of the cells in the HV battery pack. Herein, the authors discuss some of the design points of the air cooled HV battery packs in Ford Motor Company’s current model C-Max and Fusion HEVs. In these vehicles, the flow of battery cooling air was required to not only provide effective cooling of the battery cells, but to simultaneously cool a direct current high voltage to low voltage (DC-DC) converter module.

The airflow that enters the front grille of a ground vehicle for the purpose of component cooling has a significant effect on aerodynamic drag. This drag component is commonly referred to as cooling drag, which denotes the difference in drag measured between open grille and closed grille conditions. When the front grille is closed, the airflow that would have entered the front grille is redirected around the body. This airflow is commonly referred to as cooling interference airflow. Consequently, cooling interference airflow can lead to differences in vehicle component drag; this component of cooling drag is known as cooling interference drag. One mechanism that has been commonly utilized to directly influence the cooling drag, by reducing the engine airflow, is active grille shutters (AGS). For certain driving conditions, the AGS system can restrict airflow from passing through the heat exchangers, which significantly reduces cooling drag.

The purpose of this work was to examine gasoline particle filters (GPFs) at high mileages. Soot levels for gasoline direct injection (GDI) engines are much lower than diesel engines; however, noncombustible material (ash) can cause increased backpressure, reduced power, and lower fuel economy. In this study, a post mortem was completed of two GPFs, one at 130,000 mi and the other at 150,000 mi, from two production 3.5L turbocharged GDI vehicles. The GPFs were ceramic wall-flow filters containing three-way catalytic washcoat and located downstream of conventional three-way catalysts. The oil consumption was measured to be approaching 23,000 mpqt for one vehicle and 30,000 mpqt for the other. The ash contained Ca, P, Zn, S, Fe, and catalytic washcoat. Approximately 50 wt% of the collected ash was non-lubricant derived. The filter capture efficiency of lubricant-derived ash was about 50% and the non-lubricant metal (mostly Fe) deposition rate was 0.9 to 1.2 g per 10,000 mi.

Air quenching is a common manufacturing process in automotive industry to produce high strength metal component by cooling heated parts rapidly in a short period of time. With the advancement of finite element analysis (FEA) methods, it has been possible to predict thermal residual stress by computer simulation. Previous research has shown that heat transfer coefficient (HTC) for steady air quenching process is time and temperature independent but strongly flow and geometry dependent. These findings lead to the development of enhanced HTC method by performing CFD simulation and extracting HTC information from flow field. The HTC obtained in this fashion is a continuous function over the entire surface. In current part of the research, two patching algorithms are developed to divide entire surface into patches according to HTC profile and each patch is assigned a discrete HTC value.

To meet future particle mass and particle number standards, gasoline vehicles may require particle control, either by way of an exhaust gas filter and/or engine modifications. Soot levels for gasoline engines are much lower than diesel engines; however, non-combustible material (ash) will be collected that can potentially cause increased backpressure, reduced power, and lower fuel economy. The purpose of this work was to examine the ash loading of gasoline particle filters (GPFs) during rapid aging cycles and at real time low mileages, and compare the filter performances to both fresh and very high mileage filters. Current rapid aging cycles for gasoline exhaust systems are designed to degrade the three-way catalyst washcoat both hydrothermally and chemically to represent full useful life catalysts. The ash generated during rapid aging was low in quantity although similar in quality to real time ash. Filters were also examined after a low mileage break-in of approximately 3000 km.

Connected vehicles (CVs) have situational awareness that can be exploited for control and optimization of the powertrain system. While extensive studies have been carried out for energy efficiency improvement of CVs via eco-driving and planning, the implication of such technologies on the thermal responses of CVs (including those of the engine and aftertreatment systems) has not been fully investigated. One of the key challenges in leveraging connectivity for optimization-based thermal management of CVs is the relatively slow thermal dynamics, which necessitate the use of a long prediction horizon to achieve the best performance. Long-term prediction of the CV speed, unlike the short-range prediction based on vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communications-based information, is difficult and error-prone.

This paper investigates an optimal design of a diesel engine and after-treatment systems for a series hybrid electric forklift application. A holistic modeling approach is developed in GT-Suite® to establish a model-based hardware definition for a diesel engine and an after-treatment system to accurately predict engine performance and emissions. The used engine model is validated with the experimental data. The engine design parameters including compression ratio, boost level, air-fuel ratio (AFR), injection timing, and injection pressure are optimized at a single operating point for the series hybrid electric vehicle, together with the performance of the after-treatment components. The engine and after-treatment models are then coupled with a series hybrid electric powertrain to evaluate the performance of the forklift in the standard VDI 2198 drive cycle.

Passenger and light duty diesel vehicles will require up to 90% NOx conversion over the Federal Test Procedure (FTP) to meet future Tier 2 Bin 5 standards. This accomplishment is especially challenging for low exhaust temperature applications that mostly operate in the 200 - 350°C temperature regime. Selective catalytic reduction (SCR) catalysts formulated with Cu/zeolites have shown the potential to deliver this level of performance fresh, but their performance can easily deteriorate over time as a result of high temperature thermal deactivation. These high temperature SCR deactivation modes are unavoidable due to the requirements necessary to actively regenerate diesel particulate filters and purge SCRs from sulfur and hydrocarbon contamination. Careful vehicle temperature control of these events is necessary to prevent unintentional thermal damage but not always possible. As a result, there is a need to develop thermally robust SCR catalysts.

In this paper, a model-based linear estimator and a non-linear control law for an Fe-zeolite urea-selective catalytic reduction (SCR) catalyst for heavy duty diesel engine applications is presented. The novel aspect of this work is that the relevant species, NO, NO2 and NH3 are estimated and controlled independently. The ability to target NH3 slip is important not only to minimize urea consumption, but also to reduce this unregulated emission. Being able to discriminate between NO and NO2 is important for two reasons. First, recent Fe-zeolite catalyst studies suggest that NOx reduction is highly favored by the NO 2 based reactions. Second, NO2 is more toxic than NO to both the environment and human health. The estimator and control law are based on a 4-state model of the urea-SCR plant. A linearized version of the model is used for state estimation while the full nonlinear model is used for control design.

Selective catalytic reduction (SCR) is a viable option for control of oxides of nitrogen (NOx) from diesel engines. Currently, copper zeolite (Cu-zeolite) SCR catalysts are favored for configurations where the exhaust gas temperature is below 450°C for the majority of operating conditions, while iron zeolite (Fe-zeolite) SCR catalysts are preferred where NOx conversion is needed at temperatures above 450°C. The selection of Cu-zeolite or Fe-zeolite SCR catalysts is based on the different performance characteristics of these two catalyst types. Cu-zeolite catalysts are generally known for having efficient NOx reduction at low temperatures with little or no NO2, and they tend to selectively oxidize ammonia (NH3) to N2 at temperatures above 400°C, leading to poor NOx conversion at elevated temperatures.

A laboratory study was performed to assess the potential of using selective catalytic reduction (SCR) with NH3 to treat the NOx emissions from lean-burn gasoline engines. A primary concern was the potential for hot rich exhaust conditions on the vehicle, as such conditions could degrade the zeolite-based SCR catalysts being developed for automotive applications. Samples of an iron/zeolite formulation were aged for 34 hours behind samples of a three-way catalyst (TWC) on a pulse-flame combustion reactor using different A/F ratio schedules that exposed the catalysts to either continuously lean operation, mostly stoichiometric operation, or mostly rich operation. For each A/F ratio schedule, separate SCR samples were aged with inlet temperatures of 750°C, 800°C, or 850°C. The aged SCR samples were evaluated for NOx conversion at 25K hr-1 during lean temperature ramps with 500 ppm NO and NH3.