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Cylinder air charge is an important parameter to reduce generation of visible emissions by adjusting the amount of fuel injected into a diesel engine. In this study, we propose a cylinder air charge estimation algorithm for a diesel engine equipped with variable geometry turbocharger (VGT), exhaust gas recirculation (EGR), and swirl control valve (SCV). The estimation algorithm predicts the cylinder air charge using a mean value air path model and measurable signals available in mass produced engines. The estimation algorithm addresses effects of the VGT, EGR, and SCV on the cylinder air charge. The proposed estimation algorithm was validated with a 1-D engine model simulation.

In a multi-cylinder variable valve lift (VVL) engine, in spite of its high efficiency and low emission performance, operation of the variable valve lift brings about not only variation of the air-fuel ratio at the exhaust manifold, but also individual cylinder air-fuel ratio maldistribution. In this study, in order to reduce the air-fuel ratio variation and maldistribution, we propose an individual cylinder air-fuel ratio estimation algorithm for individual cylinder air-fuel ratio control. For the purpose of the individual cylinder air-fuel ratio estimation, air charging dynamics are modeled according to valve lift conditions. In addition, based on the air charging model, individual cylinder air-fuel ratios are estimated by multi-rate sampling from single universal exhaust gas oxygen (UEGO) sensor located on the exhaust manifold. Estimation results are validated with a one-dimensional engine simulation tool.

A control method using an in-cylinder pressure sensor can directly and precisely control engine combustion, lowering harmful emissions and fuel consumption levels. However, this method cannot be applied to a conventional engine management system because of its inaccuracy and the high cost of the pressure sensor, as well as the high computational load. In this study, we propose a real-time IMEP estimation method for a common rail direct injection diesel engine using the difference pressure integral as a cylinder pressure variable. The proposed method requires less computational load, enabling the IMEP to be estimated in real-time. In addition, we validated the estimation algorithm through simulation and engine experiments. The IMEP was accurately estimated with a small root mean square error of below 0.2305 bar.

Electromechanical relays that are coupled with fuses have been used for controlling electrical loads in vehicles. In the past decade, semiconductor power switches have been developed for overcoming the physical limits of relays and fuses. Semiconductor power switches can not only replace relays and fuses but can also improve a system's reliability and efficiency. In this study, we introduce the Smart Automotive Switch (SAS), which is a smart high side power switch of Fairchild Korea semiconductor. Functional capabilities, such as power switching, protection and self-diagnosis of SASs are presented in case studies involving, for example, headlights, glow plugs, and fuel pump control systems. Through these experimental studies, the suitability of SASs is validated for designing improved automotive electronic control systems.

Controlled Auto-Ignition (CAI) combustion is a new combustion concept. Unlike the conventional internal combustion engine, CAI combustion takes place homogeneously throughout the fuel/air mixture with self ignition, and the mixture is burned without flame propagation. The start of combustion (SOC) is a critical factor in the combustion because SOC affects exhaust gas emissions, engine power, fuel economy and combustion characteristics. This paper presents a control oriented SOC detection method using a 10 bar of difference pressure, and proposes 50 percent normalized difference pressure for SOC detection parameter. Difference pressure is defined as the difference between the in-cylinder firing pressure and the in-cylinder motoring pressure. These methods were determined by CAI combustion experiments. Managing the difference pressure is a fast and precise method for SOC detection.

In CRDI diesel engines, the piezo injector is gradually replacing the solenoid injector due to the quick response of the actuator. Operating performance of the injectors in the CRDI diesel engine has an influence on engine emissions. Therefore, accurate injector control is one of the most important parts of the CRDI engine control. The objective of this paper is the development of a piezo injector driver for CRDI diesel engines. Electrical characteristics of the piezo injector were analyzed. A control strategy for charging and discharging the actuator are proposed. The developed injector driver is verified by experiments under various fuel pressures, injection durations and driving circuit voltages.

The successful monitoring of the combustion process depends on the accurate measurement of in-cylinder pressure. Piezoelectric transducers are normally used for in-cylinder pressure measurement. However, rapid changes in the temperature of the transducer housing and the quartz sensing element can change the transducer offset voltage. Therefore, piezoelectric transducers require referencing the output to the absolute pressure (pegging). This study reviews several pegging methods and proposes a modified method based on a variable polytropic coefficient. The feasibility of the proposed method was validated using both the simulated and the experimental pressure data from a common-rail direct injection (CRDI) diesel engine.

This paper presents a start of combustion (SOC) control for a common rail direct injection (CRDI) diesel engine, which is achieved by utilizing in-cylinder pressure signals. The difference pressure (DP), which is the difference between the in-cylinder firing pressure and motoring pressure, is selected as the variable for SOC detection. An adaptive feedforward controller was applied in order to improve the performance of the feedback controller. The feedforward controller consists of the radial basis function network (RBFN) and the feedback error learning method that is for training of the network. In this paper, the RBFN has two inputs which are engine speed and target SOC, and has one output, start of energizing. The feasibility and performance of the proposed controller were validated by transient engine operation experiments.