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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).

Greenhouse gas (GHG) emission targets are becoming more stringent for both automakers and electricity generators. With the introduction of plug-in hybrid and electric vehicles, transportation and electricity generation sectors become connected. This provides an opportunity for both sectors to work together to achieve the cost efficient reduction of CO2 emission. In addition, the abundant natural gas (NG) in USA is drawing increased attention from both policy makers and various industries due to its low cost and low carbon content. NG has the potential to ease the pressure from CO2 emission constraints for both the light duty vehicle (LDV) and the electricity generation sectors while simultaneously reducing their fuel costs. To quantify the benefit of this collaboration, an analytical model is developed to evaluate the total societal cost and CO2 emission for both sectors.

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.

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.

The effects of combining premixed, low temperature combustion (LTC) with biodiesel are relatively unknown to this point. This mode allows simultaneously low soot and NOx emissions by using high rates of EGR and increasing ignition delay. This paper compares engine performance and emissions of neat, soy-based methyl ester biodiesel (B100), B20, B50, pure ultra low sulfur diesel (ULSD) and a Swedish, low aromatic diesel in a multi-cylinder diesel engine operating in a late-injection premixed LTC mode. Using heat release analysis, the progression of LTC combustion was explored by comparing fuel mass fraction burned. B100 had a comparatively long ignition delay compared with Swedish diesel when measured by start of ignition (SOI) to 10% fuel mass fraction burned (CA10). Differences were not as apparent when measured by SOI to start of combustion (SOC) even though their cetane numbers are comparable.

A method for detection of ethanol content in fuel for an engine equipped with direct injection (DI) is presented. The methodology is based on in-cylinder pressure measurements during the compression stroke and exploits the different charge cooling properties of ethanol and gasoline. The concept was validated using dynamometer data of a 2.0L DI turbocharged engine with variable valve timing (VVT). An algorithm was developed to process the experimental data and generate a residue from the complex cycle-to-cycle in-cylinder pressure evolution which captures the charge cooling effect. The experimental results show that there is a monotonic correlation between the residues and the fuel ethanol percentage in the majority of the cases. However, the correlation varies for different engine operating parameters; such as, speed, load, valve timing, fuel rail pressure, intake and exhaust temperature and pressure.

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.

A single-cylinder Direct Injection Spark Ignition (DISI) engine with optical access was used to investigate the effects of ethanol/gasoline blends on in-cylinder formation of particulate matter (PM) and fuel spray characteristics. Indolene was used as a baseline fuel and two blends of 50% and 85% ethanol (by volume, balance indolene) were investigated. Time resolved thermal radiation (incandescence/natural luminosity) of soot particles and fuel spray characteristics were recorded using a high speed camera. The images were analyzed to quantify soot formation in units of relative image intensity as a function of important engine operating conditions, including ethanol concentration in the fuel, fuel injection timing (250, 300 and 320° bTDC), and coolant temperature (25°C and 90°C). Spatially-integrated incandescence was used as a metric to quantify the level of in-cylinder PM formed at the different operating conditions.

A detailed chemical kinetic mechanism, consisting of 22 species and 104 elementary reactions, has been used in conjunction with the multi-dimensional reactive flow code KIVA-3 to study autoignition of natural gas injected under compression ignition conditions. Calculations for three different blends of natural gas are performed on a three-dimensional computational grid by modeling both the injection and ignition processes. Ignition delay predictions at pressures and temperatures typical of top-dead-center conditions in compression ignition engines compare well with the measurements of Naber et al. [1] in a combustion bomb. Two different criteria, based on pressure rise and mass of fuel burned, are used to detect the onset of ignition. Parametric studies are conducted to show the effect of additives like ethane and hydrogen peroxide in increasing the fuel consumption rate.

Belt drives have long been utilized in engine applications to power accessories such as alternators, pumps, compressors and fans. The first belt drives consisted of one or more V-belts powering fixed-centered pulleys and were pre-tensioned by statically adjusting the pulley center separation distances. In recent years, such drives have been replaced by a single, flat, ‘serpentine belt’ tensioned by an ‘automatic tensioner.’ The automatic tensioner consists of a spring-loaded, dry friction damped, tensioner arm that contacts the belt through an idler pulley. The tensioner's major function is to maintain constant belt tension in the presence of changing engine speeds and accessory loads. The engine crankshaft supplies both the requisite power to drive the accessories as well as the (unwanted) dynamic excitation that can adversely affect the accessories and the noise and vibration performance of the belt.

Digital human modeling (DHM) progress worldwide will be much faster and cohesive if the diverse community now developing simulations has a global blueprint for DHM, and is able to work together efficiently. DHM developers and users can save time by building on each other's work. This paper highlights a panel discussion on DHM goals and strategic plans for the next decade to begin formulating the international blueprint. Four subjects are chosen as the starting points: (1) moving DHM into the public safety and internet arenas, (2) role of DHM in computer assisted surgery and automotive safety, (3) DHM in defense applications, and (4) DHM to improve workplace ergonomics.

This paper investigates how reaching and grasping are affected by various object properties and conditions. While previous studies have examined the effect of object attributes such as size, shape, and distance from the subject, there is a need for quantitative models of finger motions. To accomplish this, the experiment was performed with six subjects where the 3D-coordinates of the finger joints and the wrist of one hand were recorded during reaching and grasping tasks. Finger joint angles at final posture were found to depend on both object size and orientation while wrist postures were changed primarily depending on object orientation. Also, each object orientation caused alteration in relative object location with respect to the hand at final posture. In addition, analysis of temporal variables revealed that it took from 1.06 to 1.30 seconds depending on the object distance to start reaching and complete grasping of the object.

This paper reviews and analyzes the current and future battery technologies suitable for transportation applications. The success of battery-enabled hybridization of gasoline and diesel power-trains in the past decade has clearly established it as the most credible alternative to the conventional propulsion systems. The current enthusiasm for electric vehicles further accentuates this success. In this paper, we compare the performance of a number of established and emerging battery technologies against the now well-established performance targets for electric-drive vehicles. Lithium-ion cells' superior performance and life are described, as are requirements for supplantation of NiMH cells in vehicles. Trends are discussed in technology development, which has largely been achieved through insertion of Li technologies in consumer electronics. Recent developments have given rise to several variants of the Li ion chemistry.

This paper proposes a simulation based methodology to assess plug-in hybrid vehicle (PHEV) behavior over 24-hour periods. Several representative 24-hour missions comprise naturalistic cycle data and information about vehicle resting time. The data were acquired during Filed Operational Tests (FOT) of a fleet of passenger vehicles carried out by the University of Michigan Transportation Research Institute (UMTRI) for safety research. Then, PHEV behavior is investigated using a simulation with two different charging scenarios: (1) Charging overnight; (2) Charging whenever possible. Charging/discharging patterns of the battery as well as trends of charge depleting (CD) and charge sustaining (CS) modes at each scenario were assessed. Series PHEV simulation is generated using Powertrain System Analysis Toolkit (PSAT) developed by Argonne National Laboratory (ANL) and in-house Matlab codes.

This paper assesses the technical potential, costs and benefits of improving the fuel economy of light-duty trucks over the next five to ten years in the United States using conventional technologies. We offer an in-depth analysis of several technology packages based on a detailed vehicle system modeling approach. Results are provided for fuel economy, cost, oil savings and reductions in greenhouse gas emissions. We examine a range of refinements to body, powertrain and electrical systems, reflecting current best practice and emerging technologies such as lightweight materials, high-efficiency IC engines, integrated starter-generator, 42 volt electrical system and advanced transmission. In this paper, multiple technological pathways are identified to significantly improve fleet average light-duty-truck fuel economy to 27.0 MPG or higher with net savings to consumers.

Natural gas quality, in terms of the volume fraction of higher hydrocarbons, strongly affects the auto-ignition characteristics of the air-fuel mixture, the engine performance and its controllability. The influence of natural gas composition on engine operation has been investigated both experimentally and through chemical kinetic based cycle simulation. A range of two component gas mixtures has been tested with methane as the base fuel. The equivalence ratio (0.3), the compression ratio (19.8), and the engine speed (1000 rpm) were held constant in order to isolate the impact of fuel autoignition chemistry. For each fuel mixture, the start of combustion was phased near top dead center (TDC) and then the inlet mixture temperature was reduced. These experimental results have been utilized as a source of data for the validation of a chemical kinetic based full-cycle simulation.

The Honda Particulate Matter Index (PMI) is a very helpful tool which provides an indication of a fuel’s sooting tendency. Currently, the index is being used by various laboratories and vehicle OEMs as a metric to understand a fuels impact on automotive engine sooting, in preparation for new global emissions regulations. The calculation of the index involves generating detailed hydrocarbon analysis (hydrocarbon molecular speciation) using gas chromatography laboratory equipment and the PMI calculation requires the exact list of compounds and correct naming conventions to work properly. The analytical methodology can be cumbersome, when the gas chromatography methodology has to be adjusted for new compounds that are not in the method, or if the compounds are not matching the list for quantification. Also, the method itself is relatively expensive, and not easily transferrable between labs.

With increasingly stringent light duty particulate emissions regulations, it is of great interest to better understand particulate matter formation. Helping to build the knowledge base for a thorough understanding of particulate matter formation will be an essential step in developing effective control strategies. It is especially important to do this in such a way as to emulate real driving behaviors, including cold starts and transients. To this end, this study examined particulate emissions during transient operation in a recent model year vehicle equipped with a GDI engine. Three of the major federal test cycles were selected as evaluation schemes: the FTP, the HWFET, and the US06. These cycles capture much of the driving behaviors likely to be observed in typical driving scenarios. Measurements included particle size distributions from a TSI EEPS fast-response particle spectrometer, as well as real-time soot emissions from an AVL MSS soot sensor.

Numerous studies have demonstrated the benefits of ethanol in increasing the thermal efficiency of gasoline-fueled spark ignition engines via the higher enthalpy of vaporization and higher knock resistance of ethanol compared with gasoline. This study expands on previous work by considering a split fuel injection strategy with a boosted direct injection spark ignition engine fueled with E0 (100% by volume reference grade gasoline; with research octane number = 91 and motor octane number = 83), E100 (100% by volume anhydrous ethanol), and various splash-blends of the two fuels. Experiments were performed using a production 3-cylinder Ford Ecoboost engine where two cylinders were de-activated to create a single-cylinder engine with a displacement of 0.33 L. The engine was operated over a range of loads with boosted intake manifold absolute pressure (MAP) from 1 bar to 1.5 bar.

Military vehicles are typically armored, hence the open surface area for heat rejection is limited. Hence, the cooling parasitic load for a given heat rejection can be considerably higher and important to consider upfront in the system design. Since PEMFCs operate at low temp, the required cooling flow is larger to account for the smaller delta temperature to the air. This research aims to address the combined problem of optimal sizing of the lithium ion battery and PEM Fuel Cell stack along with development of the scalable power split strategy for small a PackBot robot. We will apply scalable physics-based models of the fuel cell stack and balance of plant that includes a realistic and scalable parasitic load from cooling integrated with existing scalable models of the lithium ion battery. This model allows the combined optimization that captures the dominant trends relevant to component sizing and system performance.