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Abstract Carbon fiber reinforced plastic (CFRP) has been used in automobiles as well as airplanes. Because of its light weight and high strength, CFRP is a good choice for making vehicle bodies lighter, which would improve fuel economy. Conventional metal bodies provide a convenient body return for electric wiring and offer good shielding against electromagnetic fields. Although CFRP is a conductor, its conductivity is much lower than that of metals. Therefore, CFRP bodies are usually not useful for electric wiring. In thunderstorms, an automotive body is considered to be a Faraday cage that protects the vehicle’s occupants from the potential harms of lightning. Before CFRP becomes widely applied to automotive bodies, its electric and electromagnetic properties need to be investigated in order to determine whether it also works as a Faraday cage against lightning. In this article, CFRP and metal body vehicles were tested under artificial lightning.

Abstract The objective of this work is to develop an integrated HVAC-VEHICLE model for climate control studies. A published lumped parameter based HVAC model has been used as the framework for the HVAC modeling with some modifications to realize the climate control and to improve the robustness of the model. R134a (1,1,2,2-Tetrafluoroethane) has been used as the refrigerant fluid in this study. The stand-alone HVAC model has been compared qualitatively with the experimental works available in the literature. The experimental trends of the thermodynamic and performance related parameters of HVAC are reasonably well captured by the HVAC model. In particular, Coefficient of Performance (CoP) was found to decrease with increase in compressor speed and increase in ambient temperature but increase with increase in evaporator blower mass flow rate.

Abstract Exhaust manifolds are one of the most important components on the engine assembly, which is mounted on engine cylinder head. Exhaust manifolds connect exhaust ports of cylinders to the turbine for turbocharged diesel engine therefore they play a significant role in the performance of engine system. Exhaust manifolds are subjected to very harsh thermal loads; extreme heating under very high temperatures and cooling under low temperatures. Therefore designing a durable exhaust manifold is a challenging task. Computer aided engineering (CAE) is an effective tool to drive an exhaust manifold design at the early stage of engine development. Thus advanced CAE methodologies are required for the accurate prediction of temperature distribution. However, at the end of the development process, for the design verification purposes, various tests have to be carried out in engine dynamometer cells under severe operating conditions.

Abstract The mechanical efficiency of the current continuously variable transmission (CVT) suffers from high pump loss induced by a high-pressure system. A novel wedge mechanism is designed into the CVT clamp actuation system to generate the majority of clamp force mechanically. Therefore, the hydraulic system can operate at a low-pressure level most of the time, and the pump loss is greatly reduced to improve the CVT’s mechanical efficiency. Through dynamic analysis and design optimization, 90% of clamp force is contributed by the wedge mechanism and the rest of the 10% is generated by a conventional hydraulic system. The optimal design is validated through dynamic modeling using Siemens Virtual.Lab software by simulating the wedge clamp force generation, ratio change dynamics, and system response under tip-in conditions. After that, we built prototype components that target 70% of the clamp force contributed by the wedge mechanism and tested them on a transmission dynamometer.

Abstract To reduce fuel consumption and carbon dioxide (CO2) emissions from mobile air conditioning (A/C) systems, “U.S. Light-Duty Vehicle Greenhouse Gas Emissions and Corporate Average Fuel Economy Standards” identified solar/thermal technologies such as solar control glazings, solar reflective paint, and active and passive cabin ventilation in an off-cycle credit menu. National Renewable Energy Laboratory (NREL) researchers developed a sophisticated analysis process to calculate U.S. light-duty A/C fuel use that was used to assess the impact of these technologies, leveraging thermal and vehicle simulation analysis tools developed under previous U.S. Department of Energy projects. Representative U.S. light-duty driving behaviors and weighting factors including time-of-day of travel, trip duration, and time between trips were characterized and integrated into the analysis.

Abstract More than a decade ago, we proposed combined use of direct injection (DI) and jet ignition (JI) to produce high efficiency, high power-density, positive-ignition (PI), lean burn stratified, internal combustion engines (ICEs). Adopting this concept, the latest FIA F1 engines, which are electrically assisted, turbocharged, directly injected, jet ignited, gasoline engines and work lean stratified in a highly boosted environment, have delivered peak power fuel conversion efficiencies well above 46%, with specific power densities more than 340 kW/liter. The concept, further evolved, is here presented for unmanned aerial vehicle (UAV) applications. Results of simulations for a new DI JI ICE with rotary valve, being super-turbocharged and having gasoline or methanol as working fuel, show the opportunity to achieve even larger power densities, up to 430 kW/liter, while delivering a near-constant torque and, consequently, a nearly linear power curve over a wide range of speeds.

Abstract Although ground grading is one of the most common tasks that hydraulic excavators perform in typical work sites, proper grading is not easy for less-skilled operators as it requires coordinated manipulation of multiple hydraulic cylinders. In order to help alleviate this difficulty, automated grading systems are considered as an effective alternative to manual operations of hydraulic excavators. In this article, a sliding mode controller design is presented for automated grading control of a hydraulic excavator. First, an excavator manipulator model is developed in Simulink by using SimMechanics and SimHydraulics toolboxes. Then, a sliding mode controller is designed to control the manipulator to trace a predefined trajectory for a grading task. For a comparison study, a PI controller is used to control the manipulator to perform a grading task following the same desired trajectory and the performance is compared with those obtained by the sliding mode controller.

Abstract Vehicle rolling resistance and weight are two of the factors that affect fuel economy. The vehicle tire rolling resistance has a more significant influence than aerodynamics drags on fuel economy at lower vehicle speeds, particularly true for medium- and heavy-duty trucks. Less vehicle weight reduces inertia loads, uphill grade resistance, and rolling resistance. The influence of weight on the fuel economy can be considerable particularly in light- to medium-duty truck classes because the weight makes up a larger portion of gross vehicle weight. This article presents an empirical investigation and a numerical analysis of the influences of rolling resistance and weight on the fuel economy of medium-duty trucks. The experimental tests include various tires and payloads applied on a total of 21vehicle configurations over three road profiles. These tests are used to assess the sensitivity of rolling resistance and weight to the vehicle fuel economy.

Abstract With increased consumer demand for fuel efficient vehicles as well as more stringent greenhouse gas regulations and/or Corporate Average Fuel Economy (CAFE) standards from governments around the globe, the automotive industry, including the OEM (Original Equipment Manufacturers) and suppliers, is working diligently to innovate in all areas of vehicle design. In addition to improving aerodynamics, enhancing internal combustion engines and transmission technologies, and developing alternative fuel vehicles, mass reduction has been identified as an important strategy in future vehicle development. In this article, the development, analysis, and experiment of multi-cornered structures are presented. To achieve mass reduction, two non-traditional multi-cornered structures, with twelve- and sixteen-cornered cross-sections, were developed separately by using computer simulations.

Abstract The preliminary gas turbine combustor design process uses a huge amount of empirical correlations to achieve more optimized designs. Combustion efficiency, in relation to the basic dimensions of the combustor, is one of the most critical performance parameters. In this study, semi-empirical correlations for combustion efficiencies are examined and correlation coefficients have been revised using an experimental air-blasted tubular combustor that uses JP8 kerosene aviation fuel. Besides, droplet diameter and effective evaporation constant parameters have been investigated for different operating conditions. In the study, it is observed that increased air velocity significantly improves the atomization process and decreases droplet diameters, while increasing the mass flow rate has a positive effect on the atomization—the relative air velocity in the air-blast atomizer increases and the fuel droplets become finer.

Abstract When commercial vehicles drive in a mountainous area, the complex road condition and long slopes cause frequent acceleration and braking, which will use 25% more fuel. And the brake temperature rises rapidly due to continuous braking on the long-distance downslopes, which will make the brake drum fail with the brake temperature exceeding 308°C [1]. Meanwhile, the kinetic energy is wasted during the driving progress on the slopes when the vehicle rolls up and down. Our laboratory built a model that could calculate the distance from the top of the slope, where the driver could release the accelerator pedal. Thus, on the slope, the vehicle uses less fuel when it rolls up and less brakes when down. What we do in this article is use this model in a real vehicle and measure how well it works.

Abstract The pursuit of improved fuel economy through weight reduction, reduced manufacturing costs, and improved crash safety can result in increased compliance in automobile structures. However, with compliance comes an increased susceptibility to aerodynamic and vibratory loads. The hood in particular withstands considerable aerodynamic force at highway speeds, creating the potential for significant aeroelastic response that may adversely impact customer satisfaction and perception of vehicle quality. This work seeks an improved understanding in computational and experimental study of fluid-structure interactions between automobile hoods and the surrounding internal and external flow. Computational analysis was carried out using coupled CFD-FEM solvers with detailed models of the automobile topology and structural components. The experimental work consisted of wind tunnel tests using a full-scale production vehicle.

Abstract Modern vehicles have incorporated numerous safety-focused advanced driver-assistance systems (ADAS) in the last decade including smart cruise control and object avoidance. In this article, we aim to go beyond using ADAS for safety and propose to use ADAS technology to enable predictive optimal energy management and improve vehicle fuel economy (FE). We combine ADAS sensor data with a previously developed prediction model, dynamic programming (DP) optimal energy management control, and a validated model of a 2010 Toyota Prius to explore FE. First, a unique ADAS detection scope is defined based on optimal vehicle control prediction aspects demonstrated to be relevant from the literature. Next, during real-world city and highway drive cycles in Denver, Colorado, a camera is used to record video footage of the vehicle environment and define ADAS detection ground truth. Then, various ADAS algorithms are combined, modified, and compared to the ground truth results.

Abstract Due to the increasing requirements for efficiency, the wide range of characteristics and the improved possibilities of modern development and production processes, compressors in turbochargers have become more individualized in order to adapt to the requirements of internal combustion engines. An understanding of the working mechanisms as well as an understanding of the way that losses occur in the flow allows a reduced development effort during the optimization process. This article presents three-dimensional (3D) Computational Fluid Dynamics (CFD) investigations of the loss mechanisms and quantitative calculations of individual losses. The 3D-CFD method used in this article will reduce the drawbacks of one-dimensional calculation as far as possible. For example, the twist of the blades is taken into account and the “discrete” method is used for loss calculation instead of the “average” method.

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Abstract In this article, an adaptive state estimation algorithm for precise air-fuel ratio (AFR) control is presented. AFR control is a critical part of internal combustion engine (ICE) control, and tight AFR control delivers lower engine emissions, better engine fuel economy, and better engine transient performance. The proposed control algorithm significantly improves transient AFR control to eliminate and reduce the amplitude of the lean and rich spikes during transients. The new algorithm is first demonstrated in simulation (using Matlab/SimulinkTM and GT-PowerTM) and then verified on a test engine. The engine tests are conducted using the European Transient Cycle (ETC) with HoribaTM double-ended dynamometer. The developed algorithm utilizes a nonlinear physics-based engine model in the observer and advanced control principles with modifications to solve real industrial control issues.

Abstract An energy management strategy based on model predictive control (MPC) was proposed for the hybrid bus. For the series configuration, MPC was used for power distribution among transmission components. Real-time optimization of the control strategy was achieved, which improved the fuel economy. First, a rule-based energy management strategy was proposed, and the logical thresholds of the stage of charge (SOC) and the demand power were formulated to underlie the subsequent study of the control strategy. Second, an energy management strategy based on global optimization was established where the dynamic programming algorithm was used to determine the SOC optimal reference curve and the limitation of fuel economy. In this way, the target and reference can be provided for the subsequent control strategy. Third, a radial basis neural network speed prediction model based on wavelet transform was formulated.

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 Hybrid Electric Vehicles (HEVs) achieve better fuel economy than conventional vehicles by utilizing two different power sources: an internal combustion engine and an electrical motor. The power distribution between these two components must be controlled using some algorithm, be it rule based, optimization based, or reinforcement learning based. In the design of such control algorithms, it is important to evaluate the impact that variations of certain design parameters will have on the system performance, in this case, fuel economy. Traditional methods of sensitivity analysis have been applied to various power flow control algorithms to determine their robustness to the variations of HEV design parameters. This article presents a sensitivity analysis of three power flow control algorithms: twin delayed deep deterministic policy gradient (TD3), deep deterministic policy gradient (DDPG), and adaptive equivalent consumption minimization strategy (A-ECMS).

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.