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Direct injection offers a large number of degrees of freedom, as it strongly influences the mixture stratification process. Experiments on a single cylinder research engine fuelled by H2, carried out at Argonne National Laboratory, showed the influence of injection parameters (timing and geometry) on engine efficiency and combustion stability. At low load, when a late injection strategy was performed, an unstable engine behavior was detected varying the injection direction. In order to optimize the mixture stratification process in DI H2 engines, it is important to understand the physics underlying the experimental results. A spatially resolved representation of the in-cylinder processes is a useful tool to properly set the injection parameters. Also, the knowledge of the pre-injection flow field is of added value in optimizing the injection process.

Hydrogen is widely considered a promising fuel for future transportation applications for both, internal combustion engines and fuel cells. Due to their advanced stage of development and immediate availability hydrogen combustion engines could act as a bridging technology towards a wide-spread hydrogen infrastructure. Although fuel cell vehicles are expected to surpass hydrogen combustion engine vehicles in terms of efficiency, the difference in efficiency might not be as significant as widely anticipated [1]. Hydrogen combustion engines have been shown capable of achieving efficiencies of up to 45 % [2]. One of the remaining challenges is the reduction of nitric oxide emissions while achieving peak engine efficiencies. This paper summarizes research work performed on a single-cylinder hydrogen direct injection engine at Argonne National Laboratory.

For a series plug-in hybrid electric vehicle (PHEV), it is critical that batteries be sized to maximize vehicle performance variables, such as fuel efficiency, gasoline savings, and zero emission capability. The wide range of design choices and the cost of prototype vehicles calls for a development process to quickly and systematically determine the design characteristics of the battery pack, including its size, and vehicle-level control parameters that maximize the net present value (NPV) of a vehicle during the planning stage. Argonne National Laboratory has developed Autonomie, a modeling and simulation framework. With support from The MathWorks, Argonne has integrated an optimization algorithm and parallel computing tools to enable the aforementioned development process. This paper presents a study that utilized the development process, where the NPV is the present value of all the future expenses and savings associated with the vehicle.

This paper evaluates the impact of energy management strategy on the cost benefits of a plug-in hybrid electric vehicle (PHEV) by taking into account the impact of PHEV energy management on battery life and petroleum displacement over the life of the vehicle. Using Battery in the Loop (BIL), a real battery is subjected to transient power demands by a virtual vehicle. The vehicle energy management strategy is varied, resulting in different battery utilization scenarios. Battery life, which varies with battery utilization, is estimated for the different energy management scenarios. The same representative drive cycle is used over the different energy management strategies to isolate the impact of energy management on battery utilization. PHEV gasoline savings, in comparison to a charge sustaining hybrid, are calculated for each of the energy management strategies, for a fixed distance of 40 miles.

Using a 109.2 cm3, four-stroke, single-cylinder, two-valve gasoline engine, improvement of fuel economy by extension of lean burn range has been attempted with invented way to intensify tumble flow from a simple mechanical arrangement. With a part of the intake valve was jutted out beyond the perimeter of the cylinder bore, the masking effects from the valve recess on top of the cylinder sleeve created a strong tumble flow, which enabled lean burn at an air fuel ratio leaner than the conventional design by two points. The motorcycle equipped with this engine attained better fuel economy by 5.7% to the base model when measured in Indian Driving Cycle (IDC). The outward-laid intake valve also increased the clearance from the exhaust valve, which enabled use of a large-diameter intake valve to minimize the reduction of maximum power.

Research has been conducted on Controlled Auto-Ignition (CAI) engine with natural gas. CAI engine has the potential to be highly efficient and to produce low emissions. CAI engine is potentially applicable to automobile engine. However due to narrow operating range, CAI engine for automobile engine which require various speed and load in real world operation is still remaining at research level. In comparison some natural gas engines for electricity generation only require continuous operation at constant load. There is possibility of efficiency enhancement by CAI combustion which is running same speed at constant load. Since natural gas is primary consisting of methane (CH4), high auto-ignition temperature is required to occur stable auto-ignition. Usually additional intake heat required to keep stable auto-ignition. To keep high compression temperature, single cylinder natural gas engine with high compression ratio (CR=26) was constructed.

HCCI combustion can realize low NOx and particulate emissions and high thermal efficiency. Therefore, HCCI combustion has a possibility of many kinds of applications, such as an automotive powertrain, general-purpose engine, motorcycle engine and electric generator. However, the operational range using HCCI combustion in terms of speed and load is restricted because the onset of ignition and the heat release rate cannot be controlled directly. For the extension of the operational range using either an external supercharger or a turbocharger is promising. The objective of this research is to investigate the effect of the intake pressure on the HCCI high load limit and HCCI combustion characteristics with blowdown supercharging (BDSC) system. The intake pressure (Pin) and temperature (Tin) were varied as experimental parameters. The intake pressure was swept from 100 kPa (naturally aspirated) to 200 kPa using an external mechanical supercharger.

This paper includes analysis results for the control strategy of the Peugeot 3008 Hybrid4, a diesel-electric hybrid vehicle, under different thermal conditions. The analysis was based on testing results obtained under the different thermal conditions in the Advanced Powertrain Research Facility (APRF) at Argonne National Laboratory (ANL). The objectives were to determine the principal concepts of the control strategy for the vehicle at a supervisory level, and to understand the overall system behavior based on the concepts. Control principles for complex systems are generally designed to maximize the performance, and it is a serious challenge to determine these principles without detailed information about the systems. By analyzing the test results obtained in various driving conditions with the Peugeot 3008 Hybrid4, we tried to figure out the supervisory control strategy.

Production vehicles are commonly characterized and compared using fuel consumption (FC) and electric energy consumption (EC) metrics. Chassis dynamometer testing is a tool used to establish these metrics, and to benchmark the effectiveness of a vehicle's powertrain under numerous testing conditions and environments. Whether the vehicle is undergoing EPA Five-Cycle Fuel Economy (FE), component lifecycle, thermal, or benchmark testing, it is important to identify the vehicle and testing based variations of energy consumption results from these tests to establish the accuracy of the test's results. Traditionally, the uncertainty in vehicle test results is communicated using the variation. With the increasing complexity of vehicle powertrain technology and operation, a fixed energy consumption variation may no longer be a correct assumption.

Studying the kinetic and kinematics of the rim-tire combination is very important in full vehicle simulations, as well as for the tire design process. Tire maneuvers are either quasi-static, such as steady-state rolling, or dynamic, such as traction and braking. The rolling of the tire over obstacles and potholes and, more generally, over uneven roads are other examples of tire dynamic maneuvers. In the latter case, tire dynamic models are used for durability assessment of the vehicle chassis, and should be studied using high fidelity simulation models. In this study, a three-dimensional finite element model (FEM) has been developed using the commercial software package ABAQUS. The purpose of this study is to investigate the tire dynamic behavior in multiple case studies in which the transient characteristics are highly involved.

Manufacturers have been considering various technology options to improve vehicle fuel economy. Some of the most promising technologies are related to vehicle electrification. To evaluate the benefits of vehicle electrification to support the 2017-2025 CAFE regulations, a study was conducted to simulate many of the most common electric drive powertrains currently available on the market: 12V Micro Hybrid Vehicle (start/stop systems), Belt-integrated starter generator (BISG), Crank-integrated starter generator (CISG), Full Hybrid Electric Vehicle (HEV), PHEV with 20-mile all-electric range (AER) (PHEV20), PHEV with 40-mile AER (PHEV40), Fuel-cell HEV and Battery Electric vehicle with 100-mile AER (EV100). Different vehicle classes were also analyzed in the study process: Compact, Midsize, Small SUV, Midsize SUV and Pickup. This paper will show the fuel displacement benefit of each powertrain across vehicle classes.

A full understanding and characterization of the near-field of diesel sprays is daunting because the dense spray region inhibits most diagnostics. While x-ray diagnostics permit quantification of fuel mass along a line of sight, most laboratories necessarily use simple lighting to characterize the spray spreading angle, using it as an input for CFD modeling, for example. Questions arise as to what is meant by the “boundary” of the spray since liquid fuel concentration is not easily quantified in optical imaging. In this study we seek to establish a relationship between spray boundary obtained via optical diffused backlighting and the fuel concentration derived from tomographic reconstruction of x-ray radiography. Measurements are repeated in different facilities at the same specified operating conditions on the “Spray A” fuel injector of the Engine Combustion Network, which has a nozzle diameter of 90 μm.

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.

It is widely understood that cold ambient temperatures increase vehicle fuel consumption due to heat transfer losses, increased friction (increased viscosity lubricants), and enrichment strategies (accelerated catalyst heating). However, relatively little effort has been dedicated to thoroughly quantifying these impacts across a large set of real world drive cycle data and ambient conditions. This work leverages experimental dynamometer vehicle data collected under various drive cycles and ambient conditions to develop a simplified modeling framework for quantifying thermal effects on vehicle energy consumption. These models are applied over a wide array of real-world usage profiles and typical meteorological data to develop estimates of in-use fuel economy. The paper concludes with a discussion of how this integrated testing/modeling approach may be applied to quantify real-world, off-cycle fuel economy benefits of various technologies.

Designing a lightweight and durable engine is universally important from the standpoints of fuel economy, vehicle dynamics and cost. However, it is challenging to theoretically find an optimal solution which meets both requirements in products such as the cylinder head, to which various thermal loads and mechanical loads are simultaneously applied. In our research, we focused on “non-parametric optimization” and attempted to establish a new design approach derived from the weight reduction of a cylinder head. Our optimization process consists of topology optimization and shape optimization. In the topology optimization process, we explored an optimal structure with the theoretically-highest stiffness in the given design space. This is to provide an efficient structure for pursuing both lightweight and durable characteristics in the subsequent shape optimization process.

The process for setting the marketability targets and achievement methods for automotive interior quietness (as related to air borne noise above 400Hz, considered the high frequency range) was established. With conventional methods it is difficult to disseminate the relationship between the performance of individual parts and the overall vehicle performance. Without new methods, it is difficult to propose detailed specifications for the optimal sound proof packages. In order to make it possible to resolve the individual components performance targets, the interior cavity was divided into a number of sections and the acoustic performance of each section is evaluated separately. This is accomplished by evaluating the acoustical energy level of each separate interior panel with the unit power of the exterior speaker excitation. The applicability of the method was verified by evaluating result against predicted value, using the new method, during actual vehicle operation.

In this study, we developed a simulation method for rough road running condition to reproduce the behaviors of a vehicle body and to precisely estimate the input loads to the frame. We designed the simulation method focusing on a front fork model and a rider model optimized for this type of analysis. In the suspension model development, we conducted detailed measurement of the suspension characteristics on a test bench. Based on the yielded results, the friction force, as well as the spring reaction force and the damping force, was reproduced in the suspension model. The friction of the suspension varies depending on the magnitude of the reaction force associated with bending and this effect was also implemented in the model. Regarding the rider model, the actual behavior of a rider was investigated through the recorded motion video data and used to define the necessary degrees of freedom.

The mounting of lithium-ion batteries (LIB) in hybrid electric vehicles (HEV) calls for the configuration of highly robust control systems. When mounting LIBs in the vehicle, it is important to accurately ascertain and precisely control the state of the battery. In order to achieve high durability, it is important to configure highly reliable systems capable of dependably preventing overcharging as well as to have control technology based on software that can contribute to extended battery life. The system configuration applies an overcharge prevention system that uses voltage detection with an emphasis on reliability. Furthermore, a method for varying the range of state of charge (SOC) control in the vehicle according to the battery state is implemented to assure durability. In order to achieve this, battery-state detection technology was developed for the purpose of correctly detecting and judging the battery state.

Multi-mode combustion strategies may provide a promising pathway to improve thermal efficiency in light-duty spark ignition (SI) engines by enabling switchable combustion modes, wherein an engine may operate under advanced compression ignition (ACI) at low load and spark-assisted ignition at high load. The extension from the SI mode to the ACI mode requires accurate control of intake charge conditions, e.g., pressure, temperature and equivalence ratio, in order to achieve stable combustion phasing and rapid mode-switches. This study presents results from computational fluid dynamics (CFD) analysis to gain insights into mixture charge formation and combustion dynamics pertaining to auto-ignition processes. The computational study begins with a discussion of thermal wall boundary condition that significantly impacts the combustion phasing.

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.