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The steam reforming of CH4 plays a crucial role in the high-temperature activity of natural gas three-way catalysts. Despite existing reports on sulfur inhibition in CH4 steam reforming, there is a limited understanding of sulfur storage and removal dynamics under various lambda conditions. In this study, we utilize a 4-Mode sulfur testing approach to elucidate the dynamics of sulfur storage and removal and their impact on three-way catalyst performance. We also investigate the influence of sulfur on CH4 steam reforming by analyzing CH4 conversions under dithering, rich, and lean reactor conditions. In the 4-Mode sulfur test, saturating the TWC with sulfur at low temperatures emerges as the primary cause of significant three-way catalyst performance degradation. After undergoing a deSOx treatment at 600 °C, NOx conversions were fully restored, while CH4 conversions did not fully recover.

Because of the long driving range and good power performance, plug-in hybrid electric vehicles (PHEV) have drawn much attention. And the current fuel-saving effect of PHEV still has a lot of room for improvement. The complex powertrain structure of PHEV makes the requirements for control strategy be increasing. Therefore, it is crucial to develop an efficient control strategy to ensure that the PHEV operates at optimal performance with an improved driving range. This paper establishes a mathematical model for fuel economy control of PHEV, by treating the torque distribution problem as a multi-stage decision optimization problem, and establishes a global energy management strategy based on a dynamic programming (DP) algorithm. Based on the actual physical model, this paper creatively solves the correction range of battery SOC value according to the charge and discharge power of the motor, which greatly reduces the calculation time of the DP algorithm.

Diesel oxidation catalyst (DOC) is one of the critical catalyst components in modern diesel aftertreatment systems. It mainly converts unburned hydrocarbon (HC) and CO to CO2 and H2O before they are released to the environment. In addition, it also oxidizes a portion of NO to NO2, which improves the NOx conversion efficiency via fast SCR over the downstream selective catalytic reduction (SCR) catalyst. HC light-off tests, with or without the presence of NOx, has been typically used for DOC evaluation in laboratory. In this work, we aim to understand the influences of DOC light-off experimental conditions, such as initial temperature, initial holding time, HC species, with or without the presence of NOx, on the DOC HC light-off behavior. The results indicate that light-off test with lower initial temperature and longer initial holding time (at its initial temperature) leads to higher DOC light-off temperature.

The prediction accuracy of a three-way catalyst (TWC) model is highly associated with the ability of the model to incorporate the reaction kinetics of the emission process as a lambda function. In this study, we investigated the O2 and H2 concentration profiles of TWC reactions and used them as critical inputs for the development of a global TWC model. We presented the experimental data and global kinetic model showing the impact of thermal degradation on the performance of the TWC. The performance metrics investigated in this study included CH4, NOx, and CO conversions under lean, rich, and dithering light-off conditions to determine the kinetics of oxidation reactions and reduction/reforming/water-gas shift reactions as a function of thermal aging. The O2 and H2 concentrations were measured using mass spectrometry to track the change in the oxidation state of the catalyst and to determine the mechanism of the reactions under these light-off conditions.

Upcoming, stricter diesel exhaust emissions standards will likely require aftertreatment architectures with multiple diesel exhaust fluid (DEF) introduction locations. Managing NH3 slip with technologies such as an ammonia slip catalyst (ASC) will continue to be critical in these future aftertreatment systems. In this study, we evaluate the impact of SO2 exposure on a state-of-the-art commercially available ASC. SO2 is co-fed at 0.5 or 3 ppmv to either approximate or accelerate a real-world exhaust SO2 impact. ASC performance during sulfur co-feeding is measured under a wide variety of simulated real-world conditions. Results indicate that the loss of NO conversion during SCR is dependent on the cumulative SO2 exposure, regardless of the inlet SO2 concentration. Meanwhile, N2O formation under SCR conditions is nonlinearly affected by SO2 exposure, with formation increasing during 0.5 ppmv SO2 exposure but decreasing in the presence of 3 ppmv SO2.

Stoichiometric natural gas engines with three-way catalysts emit less NOx and CH4 due to their higher efficiency compared to lean-burn natural gas engines. Although hydrothermal aging of three-way catalysts has been extensively studied, a deeper understanding beyond hydrothermal aging is needed to explain real-world performance, especially for natural gas engines with near-zero NOx emissions. In this investigation, field-aged three-way catalysts were characterized to identify the contribution of chemical aging to their overall performance. It was found that the sulfur species on the field-aged TWCs were entirely distributed along the catalyst length, showing a decreasing trend, whereas phosphorous contamination was mainly observed at the inlet section of the three-way catalysts, and the phosphorous concentration declined sharply along the axial length.

The plug-in hybrid electric vehicle (PHEV) gradually moves into the mainstream market with its excellent power and energy consumption control, and has become the research target of many researchers. The energy management strategy of plug-in hybrid vehicles is more complicated than conventional gasoline vehicles. Therefore, there are still many problems to be solved in terms of power source distribution and energy saving and emission reduction. This research proposes a new solution and realizes it through simulation optimization, which improves the energy consumption and emission problems of PHEV to a certain extent. First, on the basis that MATLAB software has completed the modeling of the key components of the vehicle, the fuzzy controller of the vehicle is established considering the principle of the joint control of the engine and the electric motor.

Safety, fuel economy and uptime are key requirements for the operation of heavy-duty line-haul trucks within a fleet. With the penetration of connectivity and automation technologies, energy optimal and safe operation of the trucks are further improved through Advanced Driver Assistance System (ADAS) features and automated technologies as in truck platooning. Understanding the braking capability of the vehicle is very important for optimal ADAS and platooning control system design and integration. In this paper, the importance of tire connectivity and tire conditions on truck stopping distance are demonstrated through testing. The test data is further utilized to develop tire models for integration in an optimal vehicle automation for platooning. New ways to produce and use the tire related information in real-time optimal control of platooning trucks are proposed and the contribution of tire information in fuel economy is quantified through simulations.

For series hybrid electric vehicles (SHEV), rule-based strategies are realistic and powerful in real-time applications. However, the previous rule-based strategy cannot strike a balance between the best fuel economy and the best battery performance while maintaining the advantages of real-time applications. In order to obtain higher efficiency and reduce battery consumption, we have developed an adaptive hybrid thermostat strategy. On the basis of maintaining the load leveling of the thermostat strategy, the threshold-changing mechanism is added to realize the adaptive adjustment of the engine starting power under different SOC conditions, so as to achieve the goal of prolonging the battery life. In addition, the more fuel-efficient emergency handling rules designed to further reduce comprehensive fuel consumption.

Heavy commercial vehicle drivers may frequently shift gears when they are running on long and downhill roads in mountainous area. In order to improve driving safety and fuel economy, it is necessary to predict the slope of the road ahead in real time and correct the driver's shift strategy in time. At present, the road slope estimation is mainly based on the real-time estimation of the road slope at the current position of the vehicle based on the vehicle driving information obtained by the sensors, but the road slope of the road section that the vehicle is about to reach has not been predicted. In this paper, based on the road slope information of the road section that the driver has driven through, combined with Geographic Information System (GIS) information and road design standards, the slope of the road section ahead is predicted.

Lane changing manoeuvers is an essential rudiment in vehicle driving and has a significant impact on the characteristics of traffic flow. In the case of traditional cars, the driver operates the vehicle to complete the lane change whilst for autonomous vehicles, completing the lane change requires planning the lane change trajectory and controlling the vehicle speed during the lane change. Unreasonable lane change trajectory and vehicle speed may cause the vehicle to lose stability, threaten driving safety, increase energy consumption and waste energy. This paper considers the safety and economy of the lane changing process, and proposes a new lane changing method for vehicles.

There are a large number of curves and slopes in the mountainous areas. Unreasonable acceleration and deceleration in these areas will increase the burden of the brake system and the fuel consumption of the vehicle. The main purpose of this paper is to introduce a speed planning and promotion system for commercial vehicles in mountainous areas. The wind, slope, curve, engine brake, and rolling resistances are analyzed to establish the thermal model of the brake system. Based on the thermal model, the safe speed of the brake system is acquired. The maximum safe speed on the turning section is generated by the vehicle dynamic model. And the economic speed is calculated according to the fuel consumption model. The planning speed is provided based on these models. This system can guide the driver to handle the vehicle speed more reasonably.

The application of cooperative adaptive cruise control (CACC) to heavy-duty trucks known as truck platooning has shown fuel economy improvements over test track ideal driving conditions. However, there are limited test data available to assess the performance of CACC under real-world driving conditions. As part of the Cummins-led U.S. Department of Energy Funding Opportunity Announcement award project, truck platooning with CACC has been tested under real-world driving conditions and the results are presented in this paper. First, real-world driving conditions are characterized with the National Renewable Energy Laboratory’s Fleet DNA database to define the test factors. The key test factors impacting long-haul truck fuel economy were identified as terrain and highway traffic with and without advanced driver-assistance systems (ADAS).

Evaluation of the platooning legislative space suggests a limited near-term opportunity for autonomous vehicles as currently only nine states have platooning and autonomous favorable legislations. An extensive closed-loop vehicle model simulation was conducted to quantify two-truck platooning fuel economy entitlement benefits across all United States (US) interstate routes (I-xx) spanning over 40,000 miles as compared to a single truck. A simultaneous study was carried out to identify the density of Class 8 heavy-duty trucks on these interstates, using the Freight Analysis Framework (FAF) 4 database. These two studies were combined to ascertain interstates that foresee the least fuel consumption due to platooning and thus identifying states with the most platooning benefits. Identification of states with most platooning benefits provides realistic data to push for autonomous driving and platooning legislations.

To study the mechanism of the effect of low-viscosity oils on engine friction loss reduction so as to improve the vehicle fuel economy of the Worldwide harmonized Light vehicles Test Cycle (WLTC) by upgrading the Society of Automotive Engineers (SAE) viscosity grade of the factory fill oil from 5W30 to 0W20, eight 0W20 oil samples were blended with different doses of base oil, viscosity modifier (VM), and friction modifier (FM). Theoretical analysis by AVL-EXCITE simulation of the key friction pairs combined with practical engine friction torque test and vehicle WLTC fuel consumption tests were carried out. The results showed that 0W20 oils can effectively reduce the engine friction torque by 5.64 Nm and the friction loss by 11.95% with the throttle fully opened; while with the throttle closed, the friction torque decreased by 3.53 Nm and the friction loss by 11.26%, resulting to the improvement of the vehicle WLTC fuel economy by 2.08%.

In the intelligent speed planning system, real-time estimation of road slope is the key to calculate slope resistance and realize the vehicles’ active safety control. However, if the road slope is measured by the sensor while the commercial vehicle is driving, the vibration of the vehicle body will affect its measurement accuracy. Therefore, the relevant algorithm is used to estimate the real-time slope of the road when the commercial vehicle is driving. At present, many domestic and foreign scholars have analyzed and tested the estimation of road slope by the least square method or Kalman filter algorithm. Although the two methods both can achieve the estimation, the real-time performance and accuracy still need to be improved. In this paper, for traditional fuel commercial vehicle, the Kalman filter algorithm based on the kinematics and the extended Kalman filter algorithm based on the longitudinal dynamics are respectively used to estimate the road slope.

A head gasket is a component that sits between the engine block/liner and cylinder head(s) in an internal combustion engine. Its purpose is to seal high pressure combustion gasses in the cylinders and to seal coolant and engine oil. It is the most critical sealing application in an engine. As a general practice, the load deflection(L/D) characteristic is generated by the gasket manufacturer for edge molded or composite gasket types. However, in the case of a solid-sheet metallic gasket, where the gasket is expected to undergo localized yielding to provide adequate conformance and sealing, usually supplier may not be able to provide the required L/D curve due to difficulties to experimentally separate the large loads and small displacements from the elastic loads and deflections of the experimental apparatus. In absence of L/D curve, the typical analysis approach is to model gasket as 3D continuum elements available in ansys by considering nonlinear material and frictional contacts.

Fuel usage negatively impacts the environment and is a significant portion of operational costs of moving freight globally. Reducing fuel consumption is key to lessening environmental impacts and maximizing freight efficiency, thereby increasing the profit margin of logistic operators. In this paper, fuel economy improvements of a cab-over style 49T heavy duty Foton truck powered by a Cummins 12-liter engine are studied and systematically applied for the China market. Most fuel efficiency improvements are found within the vehicle design when compared to opportunities available at the engine level. Vehicle design (improved aerodynamics), component selection/matching (low rolling resistance tires), and powertrain electronic features integration (shift schedule/electronic trim) offer the largest opportunities for lowering fuel consumption.

The automotive industry drives some of the most stringent product requirements to ensure long product life and customer satisfaction. To demonstrate compliance with these requirements new and more accurate evaluation methods are needed. Thermal fatigue life in EGR coolers for heavy duty diesel applications have historically been a critical focus for engine OEMs. Being able to accurately evaluate product return rates due to thermal fatigue failures gives the OEM confidence that all end users will be satisfied, and allows program management to properly make fiscal decisions. Additionally, weight and cost optimization can be conducted with greater confidence. This is accomplished by accounting for product variation and application variation in thermal fatigue life evaluations. Including these variations requires a simplified numerical method to calculate product life, as tens of thousands of samples will be run through the analysis to represent real life random variation.

Accumulation of lubricant and fuel derived ash in the diesel particulate filter (DPF) during vehicle operation results in a significant increase of pressure drop across the after-treatment system leading to loss of fuel economy and reduced soot storage capacity over time. Under certain operating conditions, the accumulated ash and/or soot cake layer can collapse resulting in ash deposits upstream from the typical ash plug section, henceforth termed mid-channel ash deposits. In addition, ash particles can bond (either physically or chemically) with neighboring particles resulting in formation of bridges across the channels that effectively block access to the remainder of the channel for the incoming exhaust gas stream. This phenomenon creates serious long-term durability issues for the DPF, which often must be replaced. Mid-channel deposits and ash bridges are extremely difficult to remove from the channels as they often sinter to the substrate.