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This session covers topics regarding new CI and SI engines and components. This includes analytical, experimental, and computational studies covering hardware development as well as design and analysis techniques. Presenter Sung Hoon Lee, Hyundai Motor Co.

The development of PM and NOx reduction system with the combination of DOC included DPF and SCR catalyst in addition to the AOC sub-assembly for NH3 slip protection is described. DPF regeneration strategy and manual regeneration functionality are introduced with using ITH, HCI device on the EUI based EGR, VGT 12.3L diesel engine at the CVS full dilution tunnel test bench. With this system, PM and NOx emission regulation for JPNL was satisfied and DPF regeneration process under steady state condition and transient condition (JE05 mode) were successfully fulfilled. Manual regeneration process was also confirmed and HCI control strategy was validated against the heat loss during transient regeneration mode. Presenter Seung-il Moon

The original Table 2 includes incorrect data under the "Primary Energy" column for "multi-strike", "continuous" and "plasma" system types.

Noise concerns regarding snowmobiles have increased in the recent past. Current standards, such as SAE J192 are used as guidelines for government agencies and manufacturers to regulate noise emissions for all manufactured snowmobiles. Unfortunately, the test standards available today produce results with variability that is much higher than desired. The most significant contributor to the variation in noise measurements is the test surface. The test surfaces can either be snow or grass and affects the measurement in two very distinct ways: sound propagation from the source to the receiver and the operational behavior of the snowmobile. Data is presented for a known sound pressure speaker source and different snowmobiles on various test days and test surfaces. Relationships are shown between the behavior of the sound propagation and track interaction to the ground with the pass-by noise measurements.

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.

Wide attention to fuel cell electric vehicles (FCEVs) comes from two huge issues currently the world is facing with: the concern of the petroleum reserves depletion due to consequent oil dependence and the earth global warming due in some extent to vehicle emissions. In this background, Hyundai, along with its sister company Kia, has been building the FCEVs and operating their test fleet with several tens of units at home and abroad. Since 2004, 32 passenger vehicles have been offered for the Department of Energy's controlled hydrogen fleet and infrastructure demonstration and validation project in the U.S. In the meantime, from 2006, 30 passenger vehicles as well as four buses, featuring the in-house developed fuel cell stack and its associated components, are currently under the domestic operation for the FCEV learning demonstration led by the Ministry of Knowledge and Economy.

This research was to model a 6×4 tractor-trailer rig using TruckSim and simulate severe braking maneuvers with hardware in the loop and software in the loop simulations. For the hardware in the loop simulation (HIL), the tractor model was integrated with a 4s4m anti-lock braking system (ABS) and straight line braking tests were conducted. In developing the model, over 100 vehicle parameters were acquired from a real production tractor and entered into TruckSim. For the HIL simulation, the hardware consisted of a 4s4m ABS braking system with six brake chambers, four modulators, a treadle and an electronic control unit (ECU). A dSPACE simulator was used as the “interface” between the TruckSim computer model and the hardware.

This paper proposes a new integrated chassis control (ICC) using a predictive model-based control (MPC) for optimal allocation of sub-chassis control systems where a predictive model has 6 Degree of Freedom (DoF) for rigid body dynamics. The 6 DoF predictive vehicle model consists of longitudinal, lateral, vertical, roll, pitch, and yaw motions while previous MPC research uses a 3 DoF maximally predictive model such as longitudinal, lateral and yaw motions. The sub-chassis control systems in this paper include four wheel individual braking torque control, four wheel individual driving torque control and four corner active suspension control. Intermediate control inputs for sub-chassis control systems are simplified as wheel slip ratio changes for driving and braking controls and vertical suspension force changes for an active suspension control.

A variety of methodologies to use embedded multicore controllers efficiently has been discussed in the last years. Several assumptions are usually made in the automotive domain, such as static assignment of tasks to the cores. This paper shows an approach for efficient task allocation depending on different system modes. An engine management system (EMS) is used as application example, and the performance improvement compared to static allocation is assessed. The paper is structured as follows: First the control algorithms for the EMS will be classified according to operating modes. The classified algorithms will be allocated to the cores, depending on the operating mode. We identify mode transition points, allowing a reliable switch without neglecting timing requirements. As a next step, it will be shown that a load distribution by mode-dependent task allocation would be better balanced than a static task allocation.

Numerical durability analysis is the only approach that can be used to assess the durability of vehicles in early stages of development. In these stages, where there are no physical prototypes available, the road wheel forces (or spindle forces) for durability testing on Belgian PG (Proving Ground) must be predicted by VPG (Virtual Proving Ground) or derived from the measured forces of predecessor vehicles. In addition, the tuning parts and geometry are not fixed at these stages. This results in the variation of spindle forces during the development stages. Therefore, it is not reasonable to choose the forces predicted at a specific tuning condition as standard forces. It is more reasonable to determine the standard forces stochastically using the DB of the measured forces of predecessor vehicles. The spindle forces measured or predicted on Belgian PG are typically stationary random.

High pressure diesel sprays were visualized under vaporizing and combusting conditions in a constant-volume combustion vessel. Near-simultaneous visualization of vapor and liquid phase fuel distribution were acquired using a hybrid shadowgraph/Mie-scattering imaging setup. This imaging technique used two pulsed LED's operating in an alternative manner to provide proper light sources for both shadowgraph and Mie scattering. In addition, combustion cases under the same ambient conditions were visualized through high-speed combustion luminosity measurement. Two single-hole diesel injectors with same nozzle diameters (100μm) but different k-factors (k0 and k1.5) were tested in this study. Detailed analysis based on spray penetration rate curves, rate of injection measurements, combustion indicators and 1D model comparison have been performed.

This paper presents an adaptation method of equivalent factor in equivalent consumption minimization strategy (ECMS) of fuel cell hybrid electric vehicle (FCHEV) using hilly road information. Instantaneous optimization approach such as ECMS is one of real-time controllers. Furthermore, it is widely accepted that ECMS achieves near-optimum results with the selection of the appropriate equivalent factor. However, a lack of hilly road information no longer guarantees near-optimum results as well as charge-sustaining of ECMS under hilly road conditions. In this paper, first, an optimal control problem is formulated to derive ECMS analytical solution based on simplified models. Then, we proposed updating method of equivalent factor based on sensitivity analysis. The proposed method tries to mimic the globally optimal equivalent factor trajectory extracted from dynamic programming solutions.

Since transient vehicle HVAC computational fluids (CFD) simulations take too long to solve in a production environment, the goal of this project is to automatically create a lumped-parameter flow network from a steady-state CFD that solves nearly instantaneously. The data mining algorithm k-means is implemented to automatically discover flow features and form the network (a reduced order model). The lumped-parameter network is implemented in the commercial thermal solver MuSES to then run as a fully transient simulation. Using this network a “localized heat transfer coefficient” is shown to be an improvement over existing techniques. Also, it was found that the use of the clustering created a new flow visualization technique. Finally, fixing clusters near equipment newly demonstrates a capability to track localized temperatures near specific objects (such as equipment in vehicles).

Due to magnesium alloy's poor weldability, other joining techniques such as laser assisted self-piercing rivet (LSPR) are used for joining magnesium alloys. This research investigates the fatigue performance of LSPR for magnesium alloys including AZ31 and AM60. Tensile-shear and coach peel specimens for AZ31 and AM60 were fabricated and tested for understanding joint fatigue performance. A structural stress - life (S-N) method was used to develop the fatigue parameters from load-life test results. In order to validate this approach, test results from multijoint specimens were compared with the predicted fatigue results of these specimens using the structural stress method. The fatigue results predicted using the structural stress method correlate well with the test results.

A turbocharger is currently widely used to boost performance of an internal combustion engine. Generally, a turbocharger consists of a compressor which typically is driven by an exhaust turbine. The compressor will influence how the low frequency engine pulsation propagates in the intake system. The compressor will also produce broad-band flow induced sound due to the turbulence flow and high frequency narrowband tonal sound which is associated with rotating blade pressures. In this paper, a practical simulation procedure based on a computational fluid dynamics (CFD) approach is developed to predict the flow induced sound of a turbocharger compressor. In the CFD model of turbocharger compressor, the unsteady, moving wheel, detached eddy simulation (DES) approach are utilized. In this manner, both the broad-band and narrow-band flow induced sound are directly resolved in the CFD computation.

The highly transient operational nature of passenger car engines makes cylinder pressure based feedback control of combustion phasing difficult. The problem is further complicated by cycle-to-cycle combustion variation. A method for fast and accurate differentiation of normal combustion variations and true changes in combustion phasing is addressed in this research. The proposed method combines the results of a feed forward combustion phasing prediction model and “noisy” measurements from cylinder pressure using an iterative estimation technique. A modified version of an Extended Kalman Filter (EKF) is applied to calculate optimal estimation gain according to the stochastic properties of the combustion phasing measurement at the corresponding engine operating condition. Methods to improve steady state CA50 estimation performance and adaptation to errors are further discussed in this research.

Autoignition delay times of two full blend gasoline fuels (high and low RON) were explored in a rapid compression machine. CO2 dilution by mass was introduced at 0%, 15%, and 30% levels with the O2:N2 mole ratio fixed at 1:3.76. This dilution strategy is used to represent exhaust gas recirculation (EGR) substitution in spark ignition (SI) engines by using CO2 as a surrogate for major EGR constituents(N2, CO2, H2O). Experiments were conducted over the temperature range of 650K-900K and at 10 bar and 20 bar compressed pressure conditions for equivalence ratios of (Φ =) 0.6-1.3. The full blend fuels were admitted directly into the combustion chamber for mixture preparation using the direct test chamber (DTC) approach. CO2 addition retarded the autoignition times for the fuels studied here. The retarding effect of the CO2 dilution was more pronounced in the NTC region when compared to the lower and higher temperature range.

Accurate prediction of in-vehicle powertrain bounce mode is necessary to ensure optimum responses are achieved at driver’s touch points during 4post shake or rough road shake events. But, during the early stages of vehicle development, building a detailed vehicle finite element (FE) model is not possible and often powertrain bounce modes are computed assuming the powertrain to be a stand-alone unit. Studies conducted on FE models of a large SUV with body on frame architecture showed that the stand-alone approach overestimates the powertrain bounce mode. Consequently, there is a need for a simplified version of vehicle model which can be built early on to compute powertrain modes. Previously, representing all the major components as rigid entities, simplified unibody vehicle models have been built to compute powertrain modes. But such an approach would be inaccurate here, for a vehicle with body on frame architecture due to the flexible nature of the frame (even at low frequencies).

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.

Internal combustion engine gets heated up due to continuous combustion of fuel. To keep engine working efficiently and prevent components damage due to very high temperature, the engine needs to be cooled down. Based on power output requirement and provision for cooling system, every engine has it’s unique cooling system. Liquid based cooling systems are majorly implemented in automobile. It’s important to keep in mind that during design phase that, cooling the engine will lower the power to fuel consumption ratio. Therefore, during lower ambient conditions, the cooling system should be able to uniformly increase the temperature of the engine components, engine oil and transmission oil. This is achieved by circulating the coolant through cooling jacket, engine oil heater and transmission oil heater, which will be heated by the combustion heat.