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A mean value turbocharged engine model is useful in terms of accuracy and convenience for fuel economy strategies or engine controller development. Turbocharging process is a feedback system with a positive gain, i.e. increasing exhaust work leads to increasing a cycle work. The gain of the feedback system is determined mainly by exhaust work ratio in a cycle and inertia of the turbine. The work ratio was investigated based on engine test with EGR. A turbocharging process model was obtained using the work ratio in a cycle and theoretical equations. The model is applied to investigate manifold absolute pressure response with EGR.

Gasoline engines have the trace-knock phenomena induced by the fast combustion which happens a few times during 100 cycles. And that constrains the thermal efficiency improvement due to limiting the ignition timing advance. So the authors have been dedicating a trace-knock simulation so that we could obtain any pieces of information associated with trace-knock characteristics. This simulation consists of a turbulent combustion model, a cycle-by-cycle variation model and a chemical calculation subprogram. In the combustion model, a combustion zone is considered in order to obtain proper turbulent combustion speed through wide range of engine speed. From a cycle-by-cycle variation analysis of an actual gasoline engine, some trace-knock features were detected, and they were involved in the cycle-by-cycle variation model. And a reduced elementary reaction model of gasoline PRF (primary reference fuel) was customized to the knocking prediction, and it was used in the chemical calculation.

The automotive refrigerant system can occasionally exhibit an excessive noise out of air-conditioner (A/C) vents during vehicle’s developments. If the vehicle has been parked for long hours in summer and the A/C system is turned on, sometimes hissing noise is induced by the refrigerant flow. In order to understand the mechanism, a lot of bench and vehicle tests were conducted. However, there is still not enough to understand the physical behavior in detail. Therefore, for the first step, the visualization method to capture the behavior of multi-phased refrigerant flow jet inside the pipe was proposed with a high-speed camera, some light devices and acrylic test piece. In addition, image analysis to quantify the flow regime from a series of observed snapshots. Using proposed method, the correlation study between flow and noise was performed at A/C bench test. As a result, different flow features such as the velocity can be observed in the occurrence of the noise or not.

Improving fuel efficiency often affects NVH performance. Modifying a vehicle’s design in the latter stages of development to improve NVH performance is often costly. Therefore, to optimize the cost performance, a Multi-Attribute Balancing (MAB) approach should be employed in the early design phases. This paper proposes a solution based on a unified 1D system simulation model across different vehicle performance areas. In the scope of this paper the following attributes are studied: Fuel economy, Booming, Idle, Engine start and Drivability. The challenges to be solved by 1D simulation are the vehicle performance predictions, taking into account the computation time and accuracy. Early phase studies require a large number of scenarios to evaluate multiple possible parameter combinations employing a multi-attribute approach with a systematic tool to ease setup and evaluation according to the determined performance metrics.

The strong focus on reducing brake drag, driven by a historic ramp-up in global fuel economy and carbon emissions standards, has led to renewed research on brake caliper drag behaviors and how to measure them. However, with the increased knowledge of the range of drag behaviors that a caliper can exhibit comes a particularly vexing problem - how should this complex range of behaviors be represented in the overall road load of the vehicle? What conditions are encountered during coastdown and fuel economy testing, and how should brake drag be measured and represented in these conditions? With the Environmental Protection Agency (amongst other regulating agencies around the world) conducting audit testing, and the requirement that published road load values be repeatable within a specified range during these audits, the importance of answering these questions accurately is elevated. This paper studies these questions, and even offers methodology for addressing them.

Without engine noise, the cabin of an electric vehicle is quiet, but on the other hand, it becomes easy to perceive refrigerant-induced noise in the automotive air-conditioning (A/C) system. When determining the A/C system at the design stage, it is crucial to verify whether refrigerant-induced noise occurs in the system or not before the real A/C systems are made. If refrigerant-induced noise almost never occurs during the design stage, it is difficult to evaluate by vehicle testing at the development stage. This paper presents a 1D modeling methodology for the assessment of refrigerant-induced noise such as self-excitation noise generated by pressure pulsation through the thermal expansion valve (TXV). The GT-SUITE commercial code was used to develop a refrigerant cycle model consisting of a compressor, condenser, evaporator, TXV and the connecting pipe network.

Recently, the evaluation of the thermal environment of an engine compartment has become more difficult because of the increased employment and installation of turbochargers. This paper proposes a new prediction model of the momentum source for the turbine of a turbocharger, which is applicable to three-dimensional thermal fluid analyses of vehicle exhaust systems during the actual vehicle development phase. Taking the computational cost into account, the fluid force given by the turbine blades is imitated by adding an external source term to the Navier-Stokes equations corresponding to the optional domain without the computational grids of the actual blades. The mass flow rate through the turbine, blade angle, and number of blade revolutions are used as input data, and then the source is calculated to satisfy the law of the conservation of angular momentum.

Torque profile control is one of required technologies for propulsion engines. A smaller parametric model is more preferable for control algorithm design and evaluation. Mean value engine torque can be obtained from throttle opening change using a transfer function. A transfer function for a turbocharged engine was investigated with thermo-dynamic equations for a turbine and a compressor and test data. A small turbocharged engine was tested to model the air transfer process. Turbine speed was measured with temperatures, pressures and air mass flow. Turbine speed response is like a first order system to air mass flow into a combustion chamber. The pressure ratio at the compressor is approximated by a curve proportional to the turbine speed square. Based on those findings, a reduced order model for describing dynamic air transfer process with a turbocharger was constructed. The proposed model is compact and suitable for engine torque control design and controller implementation.

Downsizing engines with a turbocharging system have been widely applied to passenger cars to improve fuel economy. Engine torque response to accelerator operation is one of important features in addition to steady state performance of the system. Torque profile management for turbocharged internal combustion engines is one of required technologies. A turbocharging system for a car is a system with a positive feedback loop in which compressed air drives the compressor after the combustion process. A reduced order model was derived for the charging system. Pressure ratio of a compressor is proportional to square of turbine speed and the turbine speed is a first order delay system to throttle opening in the model. Model structure was designed from mathematical equations that describe turbine and compressor works. Model parameters were identified from measured data. An output torque profile control strategy based on the derived model is investigated.

A KIVA code which is customized for passenger car's diesel engines is linked with an engine performance simulator and demonstrated with our optimizing calculation system. Aiming to fulfill our target calculation speed, the combustion model of the KIVA code is changed from a chemical reaction calculation method to a chemical equilibrium calculation method which is introduced a unique technique handling chemical species maps. Those maps contain equilibrium mole fraction data of chemical species according to equivalence ratio and temperature. Linking the KIVA code to the engine simulator helps to evaluate engine performance by indicated mean effective pressure (IMEP). The optimizing calculation system enables to obtain response surfaces. Observing the response surfaces, clear views of engine performance characteristics can be seen. The overview of this calculation system and some examples of the calculation are shown in this paper.

Compression ratio of newly developed gasoline engines has been increased in order to improve fuel efficiency. But in-cylinder pressure around top dead center (TDC) before spark ignition timing is higher than expectation, because the low temperature oxidization (LTO) generates some heat. The overview of introduced calculation method taking account of the LTO heat of unburned gas, how in-cylinder pressure is revised and some knowledge of knocking prediction using chemical kinetics are shown in this paper.

Driving car means to control a vehicle according to a target path, e.g. road and speed, with some constraints. Human driving models have been proposed and applied for simulations. However, human control in driving has not been analyzed sufficiently comparing with that of machine control system in term of control theory. Input - output property with internal information processing is not easily measured and described. Response of human driving is not as quicker as that of machine controller but human can learn vehicle response to driving operation and predict target changes. Driving behavior of an expert driver and a beginner in an emission test cycle was measured and difference in target speed tracking was looked into with performance indices. The beginner's operation was less stable than that of the expert. Transfer function of the vehicle system was derived based on linearized model to investigate human driving behavior as a tracking controller in the system.

When pickup trucks are driven on concrete paved freeways, freeway hop shake is a major complaint. Freeway hop shake occurs when the vehicle passes over the concrete joints of the freeway which impose in-phase harmonic road inputs. These road inputs excite vehicle modes that degrade ride comfort. The worst shake level occurs when the vehicle speed is such that the road input excites the vehicle 1st bending mode and/or the rear wheel hop mode. The hop and bending mode are very close in frequency. This phenomenon is called freeway hop shake. Automotive manufacturers are searching for ways to mitigate freeway hop shake. There are several ways to reduce the shake amplitude. This paper documents a new approach using hydraulic body mounts to reduce the shake. A full vehicle analytical model was used to determine the root cause of the freeway hop shake.

This study involves an application of Principal Component Analysis (PCA) conducted in support of a Design for Six Sigma (DFSS) project. Primary focus of the project is to optimize seat parameters that influence Low Speed Rear Impact (LSRI) whiplash performance. During the DFSS study, the project team identified a need to rank order critical design factors statistically and establish their contribution to LSRI performance. It is also required to develop a transfer function for the LSRI rating in terms of test response parameters that can be used for optimization. This statistical approach resulted in a reliable transfer function that can applied across all seat designs and enabled us to separate vital few parameters from several many.

For fuel economy improvement by lean-burn gasoline engines, extension of their lean operation range to higher loads is desirable as more fuel is consumed during acceleration. Urgently needed therefore is development of emission control systems having as high NOx conversion efficiency as three-way catalysts (TWC) even with more frequent lean operation. The authors conducted a study using catalysts loaded with potassium (K) as the only NOx trapping agent in an emission control system of a lean-burn gasoline engine.

Homogeneous Charge Compression Ignition (HCCI) combustion shows a high potential of reducing both fuel consumption and exhaust gas emissions. Many works have been devoted to extend the HCCI operation range in order to maximize its fuel economy benefit. Among them, fuel injection strategies that use fuel reforming to increase the cylinder charge temperature to facilitate HCCI combustion at low engine loads have been proposed. However, to estimate and control an optimal amount of fuel reforming in the cylinder of an HCCI engine proves to be challenging because the fuel reforming process depends on many engine variables. It is conceivable that the amount of fuel reforming can be estimated since it correlates with the combustion phasing which in turn can be measured using a cylinder pressure sensor.

General Motors recently demonstrated two driveable test vehicles powered by a Homogeneous Charge Compression Ignition (HCCI) engine. HCCI combustion has the potential of a significant fuel economy benefit with reduced after-treatment cost. However, the biggest challenge of realizing HCCI in vehicle applications is controlling the combustion process. Without a direct trigger mechanism for HCCI's flameless combustion, the in-cylinder mixture composition and temperature must be tightly controlled in order to achieve robust HCCI combustion. The control architecture and strategy that was implemented in the demo vehicles is presented in this paper. Both demo vehicles, one with automatic transmission and the other one with manual transmission, are powered by a 2.2-liter HCCI engine that features a central direct-injection system, variable valve lift on both intake and exhaust valves, dual electric camshaft phasers and individual cylinder pressure transducers.

Model-based design is a collection of practices in which a system model is at the center of the development process, from requirements definition and system design to implementation and testing. This approach provides a number of benefits such as reducing development time and cost, improving product quality, and generating a more reliable final product through the use of computer models for system verification and testing. Model-based design is particularly useful in automotive control applications where ease of calibration and reliability are critical parameters. A novel application of the model-based design approach is demonstrated by The Ohio State University (OSU) student team as part of the Challenge X advanced vehicle development competition. In 2008, the team participated in the final year of the competition with a highly refined hybrid-electric vehicle (HEV) that uses a through-the-road parallel architecture.

Diesel engines offer better fuel economy compared to their gasoline counterpart, but simultaneous control of NOx and particulates is very challenging. The blended 2-way SCR/DPF is recently emerging as a compact and cost-effective technology to reduce NOx and particulates from diesel exhaust using a single aftertreatment device. By coating SCR catalysts on and inside the walls of the conventional wall-flow filter, the 2-way SCR/DPF eliminates the volume and mass of the conventional SCR device. Compared with the conventional diesel aftertreatment system with a SCR and a DPF, the 2-way SCR/DPF technology offers the potential of significant cost saving and packaging flexibility. In this study, an engine dynamometer test cell was set up to repeatedly load and regenerate the SCR/DPF devices to mimic catalyst aging experienced during periodic high-temperature soot regenerations in the real world.

This paper demonstrates the benefit of using simulation and robust optimization for the problem of balancing vehicle noise, vibration, and ride performance over road impacts. The psychophysics associated with perception of vehicle performance on an impact is complex because the occupants encounter both tactile and audible stimuli. Tactile impact vibration has multiple dimensions, such as impact hardness and memory shake. Audible impact sound also affects occupant perception of the vehicle quality. This paper uses multiple approaches to produce the similar, robust, optimized tuning strategies for impact performance. A Design for Six Sigma (DFSS) project was established to help identify a balanced, optimized solution. The CAE simulations were combined with software tools such as iSIGHT and internally developed Kriging software to identify response surfaces and find optimal tuning.