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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.

The introduction of inexpensive cylinder pressure sensors provides new opportunities for precise engine control. This paper presents a control strategy of spark advance and air-fuel ratio based upon cylinder pressure for spark ignition engines. In order to extend the cylinder pressure based engine control to a wide range of engine speeds, the appropriate choice of control parameters is important as well as essential. For this control scheme, peak pressure and its location for each cylinder during every engine cycle are the major parameters for controlling the air-fuel ratio and spark timing. However, the conventional method requires the measurement of cylinder pressure at every crank angle degree to determine the peak pressure and its location. In this study, the peak pressure and its location were estimated, using a multi-layer feedforward neural network, which needs only five cylinder pressure samples at -40°, -20°, 0°, 20°, and 40° after TDC.

The electrical power system is the vital lifeline to most of the control systems on modern vehicles. The demands on the system are highly complex, and a detailed understanding of the system behavior is necessary both to the process of systems integration and to the economic design of a specific control system or actuator. The vehicle electric power system, which consists of two major components: a generator and a battery, has to provide numerous electrical and electronic systems with enough electrical energy. A detailed understanding of the characteristics of the electric power system, electrical load demands, and the driving environment such as road, season, and vehicle weight are required when the capacities of the generator and the battery are to be determined for a vehicle. An easy-to-use and inexpensive simulation program may be needed to avoid the over/under design problem of the electric power system. A vehicle electric power simulator is developed in this study.