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Abstract List of Reviewers

2020-2021 Reviewers

Abstract Regulations limiting GreenHouse Gases (GHG) from Heavy-Duty (HD) commercial vehicles in the United States (US) and European Union will phase in between the 2024 and 2030 model years. These mandates require efficiency improvements at both the engine and vehicle levels, with the most stringent reductions required in the heaviest vehicles used for long-haul applications. At the same time, a 90% reduction in oxides of nitrogen (NOx) will be required as part of new regulations from the California Air Resources Board. Any technologies applied to improve engine efficiency must therefore not come at the expense of increased NOx emissions. Research into advanced engine architectures and components has identified improved turbomachine efficiency as one of the largest potential contributors to engine efficiency improvement. However this comes at the cost of a reduced capability to drive high-pressure Exhaust Gas Recirculation (EGR).

Abstract The predictive control of commercial vehicle energy management systems, such as vehicle thermal management or waste heat recovery (WHR) systems, are discussed on the basis of information sources from the field of environment recognition and in combination with the determination of the vehicle system condition. In this article, a mathematical method for predicting the exhaust gas mass flow and the exhaust gas temperature is presented based on driving data of a heavy-duty vehicle. The prediction refers to the conditions of the exhaust gas at the inlet of the exhaust gas recirculation (EGR) cooler and at the outlet of the exhaust gas aftertreatment system (EAT). The heavy-duty vehicle was operated on the motorway to investigate the characteristic operational profile.

Abstract Performing an uncertainty analysis for complex measurement tasks, such as those found in engine research, presents unique challenges. Also, because of the excessive computational costs, modeling-based approaches, such as a Monte Carlo approach, may not be practical. This work provides a traditional statistical approach to uncertainty analysis that incorporates the uncertainty tree, which is a graphical tool for complex uncertainty analysis. Approaches to calculate the required sensitivities are discussed, including issues associated with numerical differentiation, numerical integration, and post-processing. Trimming of the uncertainty tree to remove insignificant contributions is discussed. The article concludes with a best practices guide in the Appendix to uncertainty propagation in experimental engine combustion post-processing, which includes suggested post-processing techniques and down-selected functional relationships for uncertainty propagation.

Abstract The 2010 Environmental Protection Agency (EPA) Emission Standard for heavy-duty engines required 0.2 g/bhp-hr over certification cycles (cold and hot Federal Test Procedure [FTP]), and the California Air Resources Board (CARB) standards require 0.02 g/bhp-hr for the same cycles leading to a 90% reduction of overall oxides of nitrogen (NOx) emissions. Similar reductions may be considered by the EPA through its Cleaner Trucks Initiative program. In this article, aftertreatment system components consisting of a diesel oxidation catalyst (DOC); a selective catalytic reduction (SCR) catalyst on a diesel particulate filter (DPF), or SCR-F; a second DOC (DOC2); and a SCR along with two urea injectors have been analyzed, which could be part of an aftertreatment system that can achieve the 0.02 g/bhp-hr standard.

Abstract Three-dimensional patterns representing crosshatched plateau-honed cylinder bores based on two-dimensional Fast Fourier Transform (FFT) of measured surfaces were generated and used to calculate pressure flow, shear-driven flow, and shear stress factors. Later, the flow and shear stress factors obtained by numerical simulations for various surface patterns were used to calculate lubricant film thickness and friction force between piston ring and cylinder bore contact in typical diesel engine conditions using a mixed lubrication model. The effects of various crosshatch honing angles, such as 30°, 45°, and 60°, and texture heights on engine friction losses, wear, and oil consumption were discussed in detail. It is observed from numerical results that lower lubricant film thickness values are generated with higher honing angles, particularly in mixed lubrication regime where lubricant film thickness is close to the roughness level, mainly due to lower resistance to pressure flow.

Abstract To solve the problem that it is difficult for drivers to control the vehicle at low speed, a new setting scheme of pedal map is proposed to ensure that the vehicle has the speed controllability in the full speed range. In this scheme, based on obtaining the maximum and minimum driving characteristics of the vehicle and the driving resistance characteristics of the vehicle, the pedal map is divided into a sensitive area and insensitive area. In the insensitive area, acceleration hysteresis is formed, which ensures that the throttle is slightly fluctuated and has good speed stability. At the same time, the sensitive area of the accelerator pedal is formed far away from the driving resistance curve to ensure that the vehicle has a great acceleration ability. To verify the effectiveness of the proposed scheme, the data of a commercial vehicle is selected for the design of the pedal map, and the driver-vehicle closed-loop test based on the driving simulator is conducted.

Abstract This article describes the real-time simulation of a tire model for the off-highway sector. The off-highway area is characterized by soft surfaces. The additional deformation of the ground can result in more complex interactions between the tires and ground than in the on-highway area. The basics for these relationships are explained using normal and shear stress models. Aspects such as elastic tires, sinking due to slip, and multipass are also described. It is explained how soft soil modeling is used by a height field model to calculate the deformations of the soil and the resulting tire forces. Particular emphasis is placed on the calculation time and the numerical stability. The implementation in an existing real-time-capable vehicle model is described, which is important to provide a comprehensive simulation solution. During the validation it could be shown that the implemented height field can correctly map the soft soil properties.

Abstract Numerous researchers are committed to finding solutions to the path planning problem of intelligence-based vehicles. How to select the appropriate algorithm for path planning has always been the topic of scholars. To analyze the advantages of existing path planning algorithms, the intelligence-based vehicle path planning algorithms are classified into conventional path planning methods, intelligent path planning methods, and reinforcement learning (RL) path planning methods. The currently popular RL path planning techniques are classified into two categories: model based and model free, which are more suitable for complex unknown environments. Model-based learning contains a policy iterative method and value iterative method. Model-free learning contains a time-difference algorithm, Q-learning algorithm, state-action-reward-state-action (SARSA) algorithm, and Monte Carlo (MC) algorithm.

Abstract Autonomous vehicle technology has become an unprecedented trend in the development of the automobile industry, which can ensure highly efficient use of resources, effectively improve the driving experience, and greatly reduces the driver’s burden. As one of the key technologies of autonomous vehicles, path planning has an important impact on the practical applications of autonomous vehicles. Planning a proper and efficient path is a prerequisite, which can improve the driving experience of autonomous vehicles. Therefore, in-depth research and development on applications of AI technology in path planning definitely have significant value in academic research. In this article, we will introduce a variety of path planning approaches for autonomous vehicles. We summarize the attributes of these path planning algorithms; simultaneously, we analyze the improvements to these algorithms. Then, we have a preliminary discussion on the applications in vehicle positioning and navigation.

Abstract Particulates are a major source of emission from diesel engine. They consist of particles of carbon, sulfates, oil, fuel, and water. These constituents are measured by filtering a sample diluted in a partial- or full-flow tunnel and weighing them. It is a general trend for measuring particulate matter (PM) on cycle basis. But 1-D simulation needs complete PM 3-D contour map considering all engine operating region. It is very tedious work for generating PM on each steady-state point on engine test bed. Hence, Filter smoke meter or opacimeter measurements can be used for estimating PM. Filter smoke meters measured the light reflected from a filter paper through which a known volume of exhaust gas was passed. Opacity meters measure light absorbed by a standard column of exhaust. Both equipments measure visible black smoke comparatively at lower expenditure cost. They are designed to control measurement noise, resolution and repeatability with acceptable accuracy level.

Abstract The selective catalytic reduction (SCR) of nitrogen oxides seems to be the most promising technique to meet prospective emission regulations of diesel-driven commercial vehicles. In the case of developing cost-effective catalytic converters with comparably high activity, selectivity, and resistance against aging, ion-exchanged zeolites play a major role. This study presents, firstly, a brief literature review and subsequently a discussion of an extensive conversion analysis of exemplary Cu/ and Fe/zeolites, as well as a homogeneous admixture of both. The aging stages of SCR catalysts deserve particular attention in this study. In addition, the aging condition of the diesel oxidation catalyst (DOC) was analyzed, which influences the nitrogen dioxide (NO2) formation, because the NO2/nitrogen oxides (NOx) ratio upstream from the SCR converter could be identified as a key factor for low temperature NOx conversion.

Abstract In this experimental study, a novel combustion technique, “reactivity-controlled compression ignition” (RCCI), has been investigated using alcohols acting as low-reactivity fuel (LRF) and mineral diesel acting as high-reactivity fuel (HRF). Combustion experiments were performed in a single-cylinder research engine at a constant engine speed of 1500 rpm and a low engine load of 3 bar brake mean effective pressure (BMEP). RCCI combustion is a practical low-temperature combustion (LTC) concept, which was achieved using three primary alcohols: Methanol, Ethanol, and Butanol in different premixed ratios (rp = 0.25, 0.50, and 0.75) with mineral diesel. Results showed a relatively superior performance and emissions characteristics of RCCI combustion compared to conventional compression ignition (CI) combustion. The influence of LRF was visible in RCCI combustion, which exhibited a more stable combustion compared to the baseline CI combustion.

Abstract Direct dual fuel stratification (DDFS) strategy benefits the advantages of the RCCI and PPC strategies simultaneously. DDFS has improved control over the heat release rate, by injecting a considerable amount of fuel near TDC, compared to RCCI. In addition, the third injection (near TDC) is diffusion-limited. Consequently, piston bowl geometry directly affects the formation of emissions. The modified piston geometry was developed and optimized for RCCI by previous scholars. Since all DDFS experimental tests were performed with the modified piston profile, the other piston profiles need to be investigated for this strategy. In this article, first, a comparative study between the three conventional piston profiles, including the modified, stock, and scaled pistons, was performed. Afterward, the gasoline injector position was shifted to the head cylinder center for the stock piston. NOX emissions were improved; however, soot was increased slightly.

Abstract The transportation industry is currently in a transition toward the use of zero-emission vehicles; however, reaching it will take a considerable amount of time. In the meantime, a diesel powertrain will remain the workhorse for most heavy-duty transportation. In order to reduce the engine’s environmental impact, biofuels, such as biodiesel, are used as drop-in fuels or fuel blends. The use of drop-in fuels may create challenges for the fuel system since sticky deposits can precipitate and cause injector malfunctioning or premature fuel filter plugging. It has been concluded in the past that these deposits have been caused by soft particles. In this article, soft particles created through the degradation of biodiesel and their effect on filters are studied. The article aims to analyze fuel filters and investigate the materials responsible for soft particle separation. The study includes three pre filters and three main filters that are commercially available truck filters.

Abstract Commercial vehicles require advanced engine and aftertreatment (AT) systems to meet upcoming nitrogen oxides (NOx) and carbon dioxide (CO2) regulations. This article focuses on the development and calibration of a model-based controller (MBC) for an advanced diesel AT system. The MBC was first applied to a standard AT system including a diesel particulate filter (DPF) and selective catalytic reduction (SCR) catalyst. Next, a light-off SCR (LO-SCR) was added upstream of the standard AT system. The MBC was optimized for both catalysts for a production engine where the diesel exhaust fluid (DEF) was unheated for both SCRs. This research shows that the tailpipe (TP) NOx could be reduced by using MBC on both catalysts. The net result was increased NOx conversion efficiency by one percentage point on both the LO-SCR and the primary SCR. The CO2 emissions were slightly reduced, but this effect was not significant.

Abstract As emissions regulations continue to tighten, both from lower imposed limits of pollutants, such as nitrous oxides (NOx), and in-use and real-world testing, the importance of quickly heating the aftertreatment to operating temperature during a cold start, as well as maintaining this temperature during periods of low engine load, is of increasing importance. Perhaps the best method of providing the necessary heating of the aftertreatment is to direct hot exhaust gasses to it directly from the engine. For heavy-duty diesel engines that utilize turbochargers, this is achieved by fully bypassing the exhaust flow around the turbine directly to the aftertreatment. However, this disables a conventional turbocharger, limiting engine operation to near-idle conditions during the bypass period.

Abstract In current study, the combustion and emission characteristics of hydrotreated vegetable oil (HVO) were studied and compared to those of conventional marine gas oil (MGO). The main goal was to verify its applicability as an alternative marine fuel. All experiments were performed using generator set and propeller-law test cycles, i.e., standardized E2 and E3 cycles respectively. Additional emphasis was paid to the particulate matter (PM) emissions combining gravimetric and particle number measurements. The obtained results indicate average 10-15 % reduction in nitrogen oxides (NOx) emissions, while total unburned hydrocarbons (THC) emissions were reduced by 50-55 %. It is believed that a much higher cetane number of HVO together with its superior chemical composition (overall higher H/C ratio, absence of aromatics, and heavy-boiling compounds) plays a vital role here.

Abstract This article presents a multistage, coupled thermal management simulation approach, informed by physical testing where available, to aid design decisions for PACCAR’s SuperTruck II hybrid truck cabin concept. Focus areas include cabin insulation, battery sizing, and sleeper curtain position, as well as heating, ventilating, and air-conditioning (HVAC) component and accessory configurations, to maintain or improve thermal comfort while saving energy. The authors analyzed weather data and determined the national vehicle miles traveled weighted temperature and solar conditions for long-haul trucks. Example weather day profiles were selected to approximate the 5th and 95th percentile weighted conditions. A daylong drive cycle was developed to impose appropriate external wind conditions during rest and driving periods.