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The traditional method of engine knock detection is to compare the knock intensity with a predetermined threshold. The calibration of this threshold is complex and difficult. A statistical knock detection method is proposed in this paper to reduce the effort of calibration. This method dynamically calculates the knock threshold to determine the knock event. Theoretically, this method will not only adapt to different fuels but also cope with engine aging and engine-to-engine variation without re-calibration. This method is demonstrated by modeling and evaluation using real-time engine dynamometer test data.

Internal combustion engines are designed to maximize power subject to meeting exhaust emission requirements and minimizing fuel consumption. Maximizing engine power and fuel economy is limited by engine knock for a given air-to-fuel charge. Therefore, the ability to detect engine knock and run the engine at its knock limit is a key for the best power and fuel economy. This paper shows inaudible knock detection ability using in-cylinder ionization signals over the entire engine speed and load map. This is especially important at high engine speed and high EGR rates. The knock detection ability is compared between three sensors: production knock (accelerometer) sensor, in-cylinder pressure and ionization sensors. The test data shows that the ionization signals can be used to detect inaudible engine knock while the conventional knock sensor cannot under some engine operational conditions.

In an effort to understand steering systems performance and properties at the microscopic level, we developed Multibody simulations that include multiple three-dimensional gear surfaces that are in a dynamic state of contact and separation. These validated simulations capture the dynamics of high-speed impact of gears traveling small distances of 50 microns in less than 10 milliseconds. We exploited newly developed analytic, numeric, and computer tools to gain insight into steering gear forces, specifically, the mechanism behind the inception of mechanical knock in steering gear. The results provided a three dimensional geometric view of the sequence of events, in terms of gear surfaces in motion, their sudden contact, and subsequent force generation that lead to steering gear mechanical knock. First we briefly present results that show the sequence of events that lead to knock.

Knock correction is the spark angle retard applied to the optimum ignition timing to eliminate knock. In adaptive knock control, this amount of spark retard at an operating point (i.e. Speed, load) is stored in a speed/load characteristic map. It will be reused when the engine is operated in this range once more. In this paper, a method to learn the knock correction values into a speed/load characteristic map is described. This method proportionally distributes the knock correction into the characteristic map according to the distance between the speed/load of these nodes and the current operating point. The distributed knock correction value is filtered and accumulated in its adjacent nodes. Simulation examples demonstrate that the retrieved values from the map by the proposed method are smoother than those produced by the method of [2][3]. The mathematical basis for this method is developed. The one and two independent variable cases are illustrated.

Maximum Brake Torque (MBT) timing for an internal combustion engine is the minimum advance of spark timing for best torque. Traditionally, MBT timing is an open loop feedforward control whose values are experimentally determined by conducting spark sweeps at different speed, load points and at different environmental operating conditions. Almost every calibration point needs a spark sweep to see if the engine can be operated at the MBT timing condition. If not, a certain degree of safety margin is needed to avoid pre-ignition or knock during engine operation. Open-loop spark mapping usually requires a tremendous amount of effort and time to achieve a satisfactory calibration. This paper shows that MBT timing can be achieved by regulating a composite feedback measure derived from the in-cylinder ionization signal referenced to a top dead center crank angle position. A PI (proportional and integral) controller is used to illustrate closed-loop control of MBT timing.

Spark timing of an Internal Combustion (IC) engine is often limited by engine knock in the advanced direction. The ability to operate the engine at its advanced (borderline knock) spark limit is the key for improving output power and fuel economy. Due to combustion cycle-to-cycle variations, IC engine combustion behaves similar to a random process and so does the engine performance criteria, such as IMEP (Indicated Mean Effective Pressure), and knock intensity. The combustion stability measure COVariance of IMEP assumes the IMEP is a random process. Presently, the spark limit control of IC engines is deterministic in nature. The controller does not utilize any stochastic information associated with control parameters such as knock intensity for borderline spark limit control. This paper proposes a stochastic limit control strategy for borderline knock control. It also develops a simple stochastic model for evaluating the proposed stochastic controller.

To obtain the maximum output power and fuel economy from an internal combustion engine, it is often necessary to detect engine knock and operate the engine at its knock limit. This paper presents the ability to detect knock using in-cylinder ionization signals on a large displacement, air-cooled, “V” twin motorcycle engine over the engine operational map. The knock detection ability of three different sensors is compared: production knock (accelerometer) sensor, in-cylinder pressure sensor, and ionization sensor. The test data shows that the ionization sensor is able to detect knock better than the production knock sensor when there is high mechanical noise present in the engine.