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Battery temperature variations have a strong effect on both battery aging and battery performance. Significant temperature variations will lead to different battery behaviors. This influences the performance of the Hybrid Electric Vehicle (HEV) energy management strategies. This paper investigates how variations in battery temperature will affect Lithium-ion battery aging and fuel economy of a HEV. The investigated energy management strategy used in this paper is the Equivalent Consumption Minimization Strategy (ECMS) which is a well-known energy management strategy for HEVs. The studied vehicle is a Honda Civic Hybrid and the studied battery, a BLS LiFePO4 3.2Volts 100Ah Electric Vehicle battery cell. Vehicle simulations were done with a validated vehicle model using multiple combinations of highway and city drive cycles. The battery temperature variation is studied with regards to outside air temperature.

This paper considers optimal power management during the establishment of an expeditionary outpost using battery and vehicle assets for electrical generation. The first step in creating a new outpost is implementing the physical protection and barrier system. Afterwards, facilities that provide communications, fires, meals, and moral boosts are implemented that steadily increase the electrical load while dynamic events, such as patrols, can cause abrupt changes in the electrical load profile. Being able to create a fully functioning outpost within 72 hours is a typical objective where the electrical power generation starts with batteries, transitions to gasoline generators and is eventually replaced by diesel generators as the outpost matures. Vehicles with power export capability are an attractive supplement to this electrical power evolution since they are usually on site, would reduce the amount of material for outpost creation, and provide a modular approach to outpost build-up.

This paper investigates an optimal design of a diesel engine and after-treatment systems for a series hybrid electric forklift application. A holistic modeling approach is developed in GT-Suite® to establish a model-based hardware definition for a diesel engine and an after-treatment system to accurately predict engine performance and emissions. The used engine model is validated with the experimental data. The engine design parameters including compression ratio, boost level, air-fuel ratio (AFR), injection timing, and injection pressure are optimized at a single operating point for the series hybrid electric vehicle, together with the performance of the after-treatment components. The engine and after-treatment models are then coupled with a series hybrid electric powertrain to evaluate the performance of the forklift in the standard VDI 2198 drive cycle.

Increasing regulatory demand for efficiency has led to development of novel combustion modes such as HCCI, GCI and RCCI for gasoline light duty engines. In order to realize HCCI as a compression ignition combustion mode system, in-cylinder compression temperatures must be elevated to reach the autoignition point of the premixed fuel/air mixture. This should be co-optimized with appropriate fuel formulations that can autoignite at such temperatures. CFD combustion modeling is used to model the auto ignition of gasoline fuel under compression ignition conditions. Using the fully detailed fuel mechanism consisting of thousands of components in the CFD simulations is computationally expensive. To overcome this challenge, the real fuel is represented by few major components of create a surrogate fuel mechanism. In this study, 9 variations of gasoline fuel sets were chosen as candidates to run in HCCI combustion mode.

Past experimental studies conducted by the current authors on a 13 liter 16.7:1 compression ratio heavy-duty diesel engine have shown that diesel-Compressed Natural Gas (CNG) Reactivity Controlled Compression Ignition (RCCI) combustion targeting low NOx emissions becomes progressively difficult to control as the engine load is increased. This is mainly due to difficulty in controlling reactivity levels at higher loads. For the current study, CFD investigations were conducted in CONVERGE using the SAGE combustion solver with the application of the Rahimi mechanism. Studies were conducted at a load of 5 bar BMEP to validate the simulation results against RCCI experimental data. In the low load study, it was found that the Rahimi mechanism was not able to predict the RCCI combustion behavior for diesel injection timings advanced beyond 30 degCA bTDC. This poor prediction was found at multiple engine speed and load points.

Gasoline compression ignition (GCI) technology shows the potential to obtain high thermal efficiencies while maintaining low soot and NOx emissions in light-duty engine applications. Recent experimental studies and numerical simulations have indicated that high reactivity gasoline-like fuels can further enable the benefits of GCI combustion. However, there is limited empirical data in the literature studying the gasoline compression ignition process at relevant in-cylinder conditions, which are required for further optimizing combustion system designs. This study investigates the temporal and spatial evolution of the compression ignition process of various high reactivity gasoline fuels with research octane numbers (RON) of 71, 74 and 82, as well as a conventional RON 97 E10 gasoline fuel. A ten-hole prototype gasoline injector specifically designed for GCI applications capable of injection pressures up to 450 bar was used.

In this paper, a model-based linear estimator and a non-linear control law for an Fe-zeolite urea-selective catalytic reduction (SCR) catalyst for heavy duty diesel engine applications is presented. The novel aspect of this work is that the relevant species, NO, NO2 and NH3 are estimated and controlled independently. The ability to target NH3 slip is important not only to minimize urea consumption, but also to reduce this unregulated emission. Being able to discriminate between NO and NO2 is important for two reasons. First, recent Fe-zeolite catalyst studies suggest that NOx reduction is highly favored by the NO 2 based reactions. Second, NO2 is more toxic than NO to both the environment and human health. The estimator and control law are based on a 4-state model of the urea-SCR plant. A linearized version of the model is used for state estimation while the full nonlinear model is used for control design.

Research into the estimation of diesel engine combustion metrics via non-intrusive means, typically referred to as “remote combustion sensing” has become an increasingly active area of combustion research. Success in accurately estimating combustion metrics with low-cost non-intrusive transducers has been proven and documented by multiple sources on small scale diesel engines (2-4 cylinders, maximum outputs of 67 Kw, 210 N-m). This paper investigates the application of remote combustion sensing technology to a larger displacement inline 6-cylinder diesel with substantially higher power output (280 kW, 1645 N-m) than previously explored. An in-depth frequency analysis has been performed with the goal of optimizing the estimated combustion signature which has been computed based upon the direct relationship between the combustion event measured via a pressure transducer, and block vibration measured via accelerometers.

This paper studies the hardware-in-the-loop (HiL) design of a power-split hybrid electric vehicle (HEV) for the research of HEV lithiumion battery aging. In this paper, an electrochemical model of a lithium-ion battery pack with the characteristics of battery aging is built and integrated into the vehicle model of Autonomie® software from Argonne National Laboratory. The vehicle model, together with the electrochemical battery model, is designed to run in a dSPACE real-time simulator while the powertrain power distribution is managed by a dSPACE MicroAutoBoxII hardware controller. The control interface is designed using dSPACE ControlDesk to monitor the real-time simulation results. The HiL simulation results with the performance of vehicle dynamics and the thermal aging of the battery are presented and analyzed.

Exhaust emissions were characterized from a Cummins LTA10 heavy-duty diesel engine operated at two EPA steady-state modes with and without an uncatalyzed Corning ceramic particulate trap. The regulated emissions of nitrogen oxides (NOx), hydrocarbons (HC), and total particulate matter (TPM) and its components as well as the unregulated emissions of PAH, nitro-PAH, mutagenic activity and particle size distributions were measured. The consistently significant effects of the trap on regulated emissions included reductions of TPM and TPM-associated components. There were no changes in NOx and HC were reduced only at one operating condition. Particle size distribution measurements showed that nuclei-mode particles were formed downstream of the trap, which effectively removed accumulation-mode particles. All of the mutagenicity was direct-acting and the mutagenic activity of the XOC was approximately equivalent to that of the SOF without the trap.

This paper describes a study to demonstrate the feasibility of developing an acoustic encapsulation to reduce airborne noise from a commercial diesel engine. First, the various sources of noise from the engine were identified using Nearfield Acoustical Holography (NAH). Detailed NAH measurements were conducted on the four sides of the engine in an engine test cell. The main sources of noise from the engine were ranked and identified within the frequency ranges of interest. Experimental modal analysis was conducted on the oil pan and front cover plate of the engine to reveal correlations of structural vibration results with the data from the NAH. The second phase of the study involved the design and fabrication of the acoustical encapsulation (noise covers) for the engine in a test cell to satisfy the requirements of space, cost and performance constraints. The acoustical materials for the enclosure were selected to meet the frequency and temperature ranges of interest.

Dual-fuel pilot ignited natural gas engines have several intrinsic advantages relative to spark ignited; mainly higher thermal efficiency and lower conversion costs. The major drawback is associated with light loads. This paper discusses objectives, approaches, methods and results of the development of strategies which overcome the drawbacks and enhance the advantages. Development of a pilot fuel injection system, having a delivery of only 1 mm3 at a duration of 0.6 ms, was described in a previous paper. This paper concentrates on the results of strategies to reduce unburned methane in the exhaust and to increase the substitution of gas at light loads through skip-fire, by-passing boost air and exhaust gas recirculation techniques. Engine tests proved that with these strategies, diesel fuel replacement of more than 95% over the entire engine operating map, including idle, can be achieved and current and anticipated future emission standards satisfied.

Through the joint efforts of BKM, SPI, AFS and Belarus, an advanced, all- electronic dual fuel system has been developed for retrofit applications on the Belarus D-144, four-cylinder, 4.15 liter, 44.7 KW diesel engine. The system features all electronic control on both full diesel or up to 90 % gas with automatic and instant changeover capability. The existing mechanical diesel injection system was replaced with an all electronic, hydraulically actuated, diesel injection system coupled with timed multi-point electronic injection for the gas system. The control strategy does not utilize inlet throttling typically used on gas fueled engines. The effectiveness of this simplified control system is assumed to be the result of a degree of charge stratification. The D-144 engine is utilized in a wide variety of industrial, farm and highway applications. Special application requirements can be accommodated by programming the EPROM control chip.

A previously developed CFD-based optimization tool is utilized to find optimal engine operating conditions with respect to fuel consumption and emissions. The optimization algorithm employed is based on the steepest descent method where an adaptive cost function is minimized along each line search using an effective backtracking strategy. The adaptive cost function is based on the penalty method, where the penalty coefficient is increased after every line search. The parameter space is normalized and, thus, the optimization occurs over the unit cube in higher-dimensional space. The application of this optimization tool is demonstrated for the Sulzer S20, a central-injection, non-road DI diesel engine. The optimization parameters are the start of injection of the two pulses of a split injection system, the duration of each pulse, the exhaust gas recirculation rate, the boost pressure and the compression ratio.

A global optimization method has been developed for an engine simulation code and utilized in the search of optimal fuel injection strategies. This method uses a Lagrange interpolation function which interpolates engine output data generated at the vertices and the intermediate points of the input parameters. This interpolation function is then used to find a global minimum over the entire parameter set, which in turn becomes the starting point of a CFD-based optimization. The CFD optimization is based on a steepest descent method with an adaptive cost function, where the line searches are performed with a fast-converging backtracking algorithm. The adaptive cost function is based on the penalty method, where the penalty coefficient is increased after every line search. The parameter space is normalized and, thus, the optimization occurs over the unit cube in higher-dimensional space.

The capability to detect combustion in a diesel engine has the potential of being an important control feature to meet increasingly stringent emission regulations and for the development of alternative combustion strategies such as HCCI and PCCI. In this work, block mounted accelerometers are investigated as potential feedback sensors for detecting combustion characteristics in a high-speed, high pressure common rail (HPCR), 1.9L diesel engine. Accelerometers are positioned in multiple placements and orientations on the engine, and engine testing is conducted under motored, single and pilot-main injection conditions. Engine tests are then conducted at varying injection timings to observe the resulting time and frequency domain changes of both the pressure and acceleration signals.

Hydraulically intensified medium pressure common rail (MPCR) electronic fuel injection systems are an attractive concept for heavy-duty diesel engine applications. They offer excellent packaging flexibility and thorough engine management system integration. Two different concepts were evaluated in this study. They are different in how the pressure generation and injection events are related. One used a direct principle, where the high-pressure generation and injection events occur simultaneously producing a near square injection rate profile. Another concept was based on an indirect principle, where potential energy (pressure) is first stored inside a hydraulic accumulator, and then released during injection, as a subsequent event. A falling rate shape is typically produced in this case. A unit pump, where the hydraulic intensifier is separated from the injector by a high-pressure line, and a unit injector design are considered for both concepts.

Transient engine operations are modeled and simulated with a 1-D code (GT Power) using heat release and emission data computed by a 3-D CFD code (Kiva3). During each iteration step of a transient engine simulation, the 1-D code utilizes the 3-D data to interpolate the values for heat release and emissions. The 3-D CFD computations were performed for the compression and combustion stroke of strategically chosen engine operating points considering engine speed, torque and excess air. The 3-D inlet conditions were obtained from the 1-D code, which utilized 3-D heat release data from the previous 1-D unsteady computations. In most cases, only two different sets of 3-D input data are needed to interpolate the transient phase between two engine operating points. This keeps the computation time at a reasonable level. The results are demonstrated on the load response of a generator which is driven by a medium-speed diesel engine.

Steady-state particulate loading experiments were conducted on an advanced production catalyzed particulate filter (CPF), both with and without a diesel oxidation catalyst (DOC). A heavy-duty diesel engine was used for this study with the experiments conducted at 20, 40, 60 and 75 % of full load (1120 Nm) at rated speed (2100 rpm). The data obtained from these experiments were used and are necessary for calibrating the MTU 1-D 2-Layer CPF model. These experimental and modeling results were compared to previous research conducted at MTU that used the same engine but an earlier development version of the combination of DOC and CPF. The motivation for the comparison of the two systems was to determine whether the reformulated production catalysts performed as good or better than the early development catalysts. The results were compared to understand the filtration and oxidation differences between the two DOC+CPF and the CPF-only aftertreatment systems.

A methodology to estimate the mass of particulate retained in a catalyzed particulate filter as a function of measured total pressure drop, volumetric flow rate, exhaust temperature, exhaust gas viscosity and cake and wall permeability applicable to real-time computation is discussed. This methodology is discussed from the view point of using it to indicate when to initiate active regeneration and as an On-Board Diagnostic tool to detect filter failures. Steady-state loading characterization experiments were conducted on a catalyzed diesel particulate filter (CPF) in a Johnson Matthey CCRT® (catalyzed continuously regenerating trap) system. The experiments were performed using a 10.8 L 2002 Cummins ISM heavy-duty diesel engine. Experiments were conducted at 20, 60 and 75% of full engine load (1120 Nm) and rated speed (2100 rpm) to measure the pressure drop, transient filtration efficiency, particulate mass balance, and gaseous emissions.