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This paper proposes a framework to perform design optimization of a series PHEV and investigates the impact of using real-world driving inputs on final design. Real-World driving is characterized from a database of naturalistic driving generated in Field Operational Tests. The procedure utilizes Markov chains to generate synthetic drive cycles representative of real-world driving. Subsequently, PHEV optimization is performed in two steps. First the optimal battery and motor sizes to most efficiently achieve a desired All Electric Range (AER) are determined. A synthetic cycle representative of driving over a given range is used for function evaluations. Then, the optimal engine size is obtained by considering fuel economy in the charge sustaining (CS) mode. The higher power/energy demands of real-world cycles lead to PHEV designs with substantially larger batteries and engines than those developed using repetitions of the federal urban cycle (UDDS).

With ongoing concerns about the elevated levels of ambient air pollution in urban areas and the contribution from heavy-duty diesel vehicles, hybrid electric vehicles are considered as a potential solution as they are perceived to be more fuel efficient and less polluting than their conventional engine counterparts. However, recent studies have shown that real-world emissions may be substantially higher than those measured in the laboratory, mainly due to operating conditions that are not fully accounted for in dynamometer test cycles. At the U.S. EPA National Fuel and Vehicle Emissions Laboratory (NVFEL) the in-use criteria emissions and energy efficiency of heavy-duty class 8 vehicles (up to 36280 kg) can be evaluated under controlled conditions in the heavy-duty chassis dynamometer test.

Minimizing the stress concentrations around cutouts in a plate is often a design problem, especially in the Aerospace industry. A problem of optimizing spatially varying fiber paths in a symmetric, linear orthotropic composite laminate with a cutout, so as to achieve minimum stress concentration under remote unidirectional tensile loading is of interest in this study. A finite element (FE) model is developed to this extent, which constraints the fiber angles while optimizing the fiber paths, proving essential in manufacturing processes. The idea to be presented could be used to derive fiber paths that would drastically reduce the Stress Concentration Factor (SCF) in a symmetric laminate by using spatially varying fibers in place of unidirectional fibers. The model is proposed for a four layer symmetric laminate, and can be easily reproduced for any number of layers.

A direct trajectory optimization approach is developed to assess the capability of a GTDI-DCT Powertrain, with a Gasoline Turbocharged Direct Injection (GTDI) engine and Dual Clutch Transmission (DCT), to satisfy stringent drivability requirements during launch. The optimization is performed directly on a high fidelity black box powertrain model for which a single simulation of a launch event takes about 8 minutes. To address this challenging problem, an efficient parameterization of the control trajectory using Gaussian kernel functions and a Mesh Adaptive Direct Search optimizer are exploited. The results and observations are reported for the case of clutch torque optimization for launch at normal conditions, at high altitude conditions and at non-zero grade conditions. The results and observations are also presented for the case of simultaneous optimization of multiple actuator trajectories at normal conditions.

This paper addresses scheduling of quantized power levels (including part load operation and startup/shutdown periods) for a propane powered solid oxide fuel cell (SOFC) hybridized with a lithium-ion battery for a tracked mobile robot. The military requires silent operation and long duration missions, which cannot be met by batteries alone due to low energy density or with combustion engines due to noise. To meet this need we consider an SOFC operated at a few discrete power levels where maximum system efficiency can be achieved. The fuel efficiency decreases during transients and resulting thermal gradients lead to stress and degradation of the stack; therefore switching power levels should be minimized. Excess generated energy is used to charge the battery, but when it’s fully charged the SOFC should be turned off to conserve fuel.

Design of military vehicle needs to meet often conflicting requirements such as high mobility, excellent fuel efficiency and survivability, with acceptable cost. In order to reduce the development cost, time and associated risk, as many of the design questions as possible need to be addressed with advanced simulation tools. This paper describes a methodology to design a fuel efficient powerpack unit for a series hybrid electric military vehicle, with emphasis on the e-machine design. The proposed methodology builds on previously published Finite element based analysis to capture basic design features of the generator with three variables, and couples it with a model reduction technique to rapidly re-design the generator with desired fidelity. The generator is mated to an off the shelf engine to form a powerpack, which is subsequently evaluated over a representative military drive cycles.

Wet clutch packs are widely used in today’s automatic transmission systems for gear-ratio shifting. The frictional interfaces between the clutch plates are continuously lubricated with transmission fluid for both thermal and friction management. The open clutch packs shear transmission fluid across the rotating plates, contributing to measurable energy losses. A typical multi-speed transmission includes as many as 5 clutch packs. Of those, two to three clutches are open at any time during a typical drive cycle, presenting an opportunity for fuel economy gain. However, reducing open clutch drag is very challenging, while meeting cooling requirements and shift quality targets. In practice, clutch design adjustment is performed through trial-and-error evaluation of hardware on a test bench. The use of analytical methodologies is limited for optimizing clutch design features due to the complexity of fluid-structure interactions under rotating conditions.

This study uses full drive cycle simulation to compare the fuel consumption of a vehicle with a turbocharged (TC) engine to the same vehicle with an alternative boosting technology, namely, a hybrid supercharger, in which a planetary gear mechanism governs the power split to the supercharger between the crankshaft and a 48 V 5 kW electric motor. Conventional mechanically driven superchargers or electric superchargers have been proposed to improve the dynamic response of boosted engines, but their projected fuel efficiency benefit depends heavily on the engine transient response and driver/cycle aggressiveness. The fuel consumption benefits depend on the closed-loop engine responsiveness, the control tuning, and the torque reserve needed for each technology. To perform drive cycle analyses, a control strategy is designed that minimizes the boost reserve and employs high rates of combustion dilution via exhaust gas recirculation (EGR).

Syngas (synthesis gas) aided combustion from various fuel reforming strategies is of increasing interest in boosted lean burn SI engines due to its impact on dilution tolerance and knock resistance. Due to the interest in reformed fuels, more concrete understanding of how to leverage syngas supplementation under various lean conditions is essential to optimize engine performance and derive the most benefit from the availability of syngas in the combustion process. While the impact of syngas supplementation on combustion stability has been studied adequately, detailed understanding of the impact of syngas on knocking is still limited. Hence, this study investigates the effect of syngas (H2/CO) addition on knock tendency under boosted EGR (Exhaust Gas Recirculation) and air diluted conditions. Syngas amount is controlled on an energy basis from 0% to 15% to compare the difference between EGR and air dilution.

This paper describes a novel design and verification process for analytical methods used in the development of advanced combustion strategies in internal combustion engines (ICE). The objective was to improve brake thermal efficiency (BTE) as part of the US Department of Energy SuperTruck program. The tools and methods herein discussed consider spray formation and injection schedule along with piston bowl design to optimize combustion efficiency, air utilization, heat transfer, emission, and BTE. The methodology uses a suite of tools to optimize engine performance, including 1D engine simulation, high-fidelity CFD, and lab-scale fluid mechanic experiments. First, a wide range of engine operating conditions are analyzed using 1-D engine simulations in GT Power to thoroughly define a baseline for the chosen advanced engine concept; secondly, an optimization and down-select step is completed where further improvements in engine geometries and spray configurations are considered.

Stringent fuel economy and emissions regulations have driven development of new mixture preparation technologies and increased spark-ignition engine complexity. Additional degrees of freedom, brought about by devices such as cam phasers and charge motion control valves, enable greater range and flexibility in engine control. This permits significant gains in fuel efficiency and emission control, but creates challenges related to proper engine control and calibration techniques. Accurate experimental characterization of high degree of freedom engines is essential for addressing the controls challenge. In particular, this paper focuses on the evaluation of three experimental residual gas fraction measurement techniques for use in a spark ignition engine equipped with dual-independent variable camshaft phasing (VVT).

In this paper the development of statistical metamodels and statistical fast running models is presented first. They are utilized for propagating uncertainties in a multi-discipline design optimization process. Two main types of uncertainty can be considered in this manner: uncertainty due to variability in design variables or in random parameters; uncertainty due to the utilization of metamodels instead of the actual simulation models during the optimization process. The value of the new developments and their engagement in multi-discipline design optimization is demonstrated through a case study. An underwater vehicle is designed under four different disciplines, namely, noise radiation, self-noise due to TBL excitation, dynamic response due to propulsion impact loads, and response to an underwater detonation.

This simulation study explores the potential synergy between the HCCI engine system and three hybrid electric vehicle (HEV) configurations, and proposes the supervisory control strategy that maximizes the benefits of combining these two technologies. HCCI operation significantly improves fuel efficiency at part load, while hybridization aims to reduce low load/low speed operation. Therefore, a key question arises: are the effects of these two technologies additive or overlapping? The HEV configurations include two parallel hybrids with varying degrees of electrification, e.g. with a 5kW integrated starter/motor (“Mild”) and with a 10 kW electric machine (“Medium”), and a power-split hybrid. The engine is a dual-mode, SI-HCCI system and the engine map reflects the impact of HCCI on brake specific fuel consumption.

Electrification and hybridization have great potential for improving fuel economy and reducing visual signature or soot emissions in military vehicles. Specific challenges related to military applications include severe duty cycles, large and uncertain energy flows through the system and high thermal loads. A novel supervisory control strategy is proposed to simultaneously mitigate severe engine transients and to reduce high electric current in the battery without oversizing the battery. The described objectives are accomplished by splitting the propulsion power demand through filtering in the frequency domain. The engine covers only low frequency power demand profile while the battery covers high frequency components. In the proposed strategy, the separation filter is systematically designed to identify different frequency components with the consideration of fuel consumption, aggressive engine transients, and battery electric loads.

Suspension design is influenced by many factors, especially by vehicle dynamics performance in ride, handling and durability. In the global automotive industry it is common to “customize” or tune suspension parameters so that a vehicle is more acceptable to a different customer base and in a different driving environment. This paper seeks to objectively quantify certain aspects of tuning via ride optimization, taking account of market differences in road surface spectral properties and loading conditions. A computationally efficient methodology for suspension optimization is developed using stochastic techniques. A small (B-class) vehicle is chosen for the study and the following main suspension parameters are selected for optimization - spring stiffness, damping rate and vertical tire stiffness. The road is characterized as a stationary random process, using scaling and shaping filters representative of comparable roads in India and the USA.

The U.S. Department of Energy's Office of Energy Efficiency & Renewable Energy initiated a study that conducted coastdown testing and chassis dynamometer testing of three vehicles, each at multiple test weights, in an effort to determine the impact of a vehicle's mass on road load force and energy consumption. The testing and analysis also investigated the sensitivity of the vehicle's powertrain architecture (i.e., conventional internal combustion powertrain, hybrid electric, or all-electric) on the magnitude of the impact of vehicle mass. The three vehicles used in testing are a 2012 Ford Fusion V6, a 2012 Ford Fusion Hybrid, and a 2011 Nissan Leaf. Testing included coastdown testing on a test track to determine the drag forces and road load at each test weight for each vehicle. Many quality measures were used to ensure only mass variations impact the road load measurements.

Homogenous Charge Compression Ignition (HCCI) engines offer a good potential for achieving high fuel efficiency while virtually eliminating NOx and soot emissions from the exhaust. However, realizing the full fuel economy potential at the vehicle level depends on the size of the HCCI operating range. The usable HCCI range is determined by the knock limit on the upper end and the misfire limit at the lower end. Previously proven high sensitivity of the HCCI process to thermal conditions leads to a hypothesis that combustion chamber deposits (CCD) could directly affect HCCI combustion, and that insight about this effect can be helpful in expanding the low-load limit. A combustion chamber conditioning process was carried out in a single-cylinder gasoline-fueled engine with exhaust re-breathing to study CCD formation rates and their effect on combustion. Burn rates accelerated significantly over the forty hours of running under typical HCCI operating conditions.

Super-knock has been a significant obstacle for the development of highly turbocharged (downsized) gasoline engines with spark ignition, due to the catastrophic damage super-knock can cause to the engine. According to previous research by the authors, one combustion process leading to super-knock may be described as hot-spot induced pre-ignition followed by deflagration which can induce detonation from another hot spot followed by high pressure oscillation. The sources of the hot spots which lead to pre-ignition (including oil films, deposits, gas-dynamics, etc.) may occur sporadically, which leads to super-knock occurring randomly at practical engine operating conditions. In this study, a spark plasma was used to induce preignition and the correlation between super-knock combustion and the thermodynamic state of the reactant mixture was investigated in a four-cylinder production gasoline engine.

High-pressure gasoline injection can improve combustion efficiency and lower engine-out emissions; however, the spray characteristics of high-pressure gasoline (>500 bar) are not well known. Effects of different injector nozzle geometry on high-pressure gasoline sprays were studied using a constant volume chamber. Five nozzles with controlled internal flow features including differences in nozzle inlet rounding, conicity, and outlet diameter were investigated. Reference grade gasoline was injected at fuel pressures of 300, 600, 900, 1200, and 1500 bar. The chamber pressure was varied using nitrogen at ambient temperature and pressures of 1, 5, 10, and 20 bar. Spray development was recorded using diffuse backlit shadowgraph imaging methods.

A study has been conducted in order to investigate the effect of the location of knock initiation on heat flux in a Spark-Ignition (SI) combustion chamber. Heat flux measurements were taken on the piston and cylinder head under different knock intensity levels, induced by advancing the spark timing. Tests were performed with two engine configurations, the first with the spark-plug located on the rear side of the chamber and the other having a second non-firing spark-plug placed at the front side of the chamber. The presence of the non-firing spark-plug consistently shifted the location of autoignition initiation from the surface of the piston to its vicinity, without causing a noticeable increase in knock intensity. By localizing the initiation of knock, changes induced in the secondary flame propagation pattern affected both the magnitude and the rate of change of peak heat flux under heavy knock.