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Model-based methodologies for the engine calibration process, employing engine cycle simulation and polynomial regression analysis, have been developed and the reliability of the proposed method was confirmed by validating the model predictions with dynamometer test data. From the results, it was clear that the predictions by the engine cycle simulation with a knock model, which considers the two-stage hydrocarbon ignition characteristics of gasoline, were in good agreement with the dynamometer test data if the model tuning parameters were strictly adjusted. Physical model tuning and validation were done, followed by the creation of a dataset for the regression analysis of charging efficiency, EGR mass, and MBT using a 4th order polynomial equation. The stepwise method was demonstrated to yield a logarithm likelihood ratio and its false probability at each term in the polynomial equation.

In recent years, integrated vehicle control systems have been developed to improve fuel economy and safety. As a result, engine control is shifting to torque-based systems for throttle / fuel / ignition control, to realize an engine torque demand from the system. This paper describes torque-based engine control technologies for SI (Spark Ignition) engine to improve torque control accuracy using a feedback control algorithm and an airflow sensor.

An automatic matching method for engine control parameters is described which can aid efficient development of new engine control systems. In a spark-ignition engine, fuel is fed to a cylinder in proportion to the air mass induced in the cylinder. Air flow meter characteristics and fuel injector characteristics govern fuel control. The control parameters in the electronic controller should be tuned to the physical characteristics of the air flow meter and the fuel injectors during driving. Conventional development of the engine control system requires a lot of experiments for control parameter matching. The new matching method utilizes the deviation of feedback coefficients for stoichiometric combustion. The feedback coefficient reflects errors in control parameters of the air flow meter and fuel injectors. The relationship between the feedback coefficients and control parameters has been derived to provide a way to tune control parameters to their physical characteristics.

The increasing number of controllable parameters in modern engine systems has led to increasingly complicated and enlarged engine control software. This in turn has created dramatic increases in software development time and cost. Model-based control design seems to be an effective way to reduce development time and costs and also to enable engineers to understand the complex relationship between the many controllable parameters and engine performance. In the present study, we have developed model-based methodologies for the engine calibration process, employing engine cycle simulation and regression analysis. The reliability of the proposed method was investigated by validating the regression model predictions with measured data.

Most automatic transmissions are controlled in compliance with a predetermined program. Transient control during gear shift is also carried out according to a predetermined process. In this method a lot of labor is required to tune data tables. So we developed a tuning free system by feedback control using torque estimation technology and the experimental result is reported. Torque fluctuation during shift is detected and fed back to compare the torque reference, which is generated from the estimated torque itself. The engine torque is decreased by means of retarding the ignition spark advance, according to the comparison deviation. As a consequence of the feedback, the transient torque control is carried out without any tuning trouble, and better than usual torque fluctuation is obtained.

The increasing number of controllable parameters in modern engine systems leads to complicated and enlarged engine control software. This in turn has led to dramatic increases in software development time and costs in recent years. Model-based control design seems to be an effective way to reduce development time and costs. In the present study, we have developed model-based methodologies for the engine calibration process using an engine cycle simulation technique combined with a regression analysis of engine responses. From the results it was clear that the engine cycle simulation technique was useful in the engine calibration process, if the empirical parameters included in physical models were adjusted at typical sampling-points in several engine speeds and loads. The cycle simulation produced a multi-dimensional MBT map, and a response surface method was employed in the modeling of the engine map dataset using a polynomial equation.

An automotive powertrain total control system using estimated output shaft torque has been investigated in order to enhance drivability and improve fuel economy. The system provides efficient control for both the engine and transmission which leads to an enhancement in drivability by reducing shocks during gear shifts. This paper describes a new smooth gear shift control method using the total control system. By use of the estimated output shaft torque, it is possible to detect accurately the fluctuation condition and the start time of the inertia phase, which are important factors affecting shock occurrence. Torque feedback, got from estimated torque, was applied to the control of engine output shaft torque during shifts. The optimum hydraulic pressure, also got from estimated torque, was applied to the clutch of the transmission during shifts.

An automatic transmission without a one-way clutch for a small sized, light weight automatic transmission is presented. The factor of torque fluctuation occurrence during shifting of the transmission increases so that the shifting is executed by controlling two wet clutches electronically in place of the one-way clutch and the wet clutch. Therefore, it is necessary to develop a new smooth gear shift control technology for clutch-to-clutch shifting on an automatic transmission without a one-way clutch. The control technology has desirable clutch-to-clutch shift control, learning control and robust control which apply to accurate signals obtained by an observation method. Smooth shifts during clutch-to-clutch shifting can be realized by recognizing clutch change-over time using a calculated acceleration and an input/output speed ratio of the transmission.